@Article{info:doi/10.2196/59570, author="Jansen, Carl-Philipp and Nijland, D{\'e}sir{\'e}e and Oppert, Jean-Michel and Alcan, Veysel and Keskinen, E. Kirsi and Matikainen-Tervola, Emmi and Pajalic, Zada and Rantakokko, Merja and Tomsone, Signe and Tuomola, Essi-Mari and Portegijs, Erja and Timmermans, J. Erik", title="The Role of Environmental Factors in Technology-Assisted Physical Activity Intervention Studies Among Older Adults: Scoping Review", journal="JMIR Mhealth Uhealth", year="2025", month="Mar", day="13", volume="13", pages="e59570", keywords="environmental factors", keywords="intervention", keywords="older adults", keywords="physical activity", keywords="technology", keywords="PRISMA", abstract="Background: The rapidly emerging integration of both technological applications and environmental factors in physical activity (PA) interventions among older adults highlights the need for an overarching investigation. Objective: This scoping review compiled the current literature and aimed to provide an overview of the role of physical, social, socioeconomic, and systemic environmental factors in technology-assisted PA interventions for older adults. Methods: We systematically searched 6 common databases up to September 16, 2024, for original longitudinal studies (with at least one preintervention measurement and one postintervention measurement) that reported on the role of environmental factors in technology-assisted PA interventions for independently living, community-dwelling older adults. In a stepwise process, data on study characteristics (step 1), environmental factors and their role in the included studies (step 2), and intervention outcomes and effects by type of environmental factor (step 3) were summarized. Results: A total of 8020 articles were screened, and 25 (0.31\%) were included. Most studies were conducted in Europe (11/25, 44\%), followed by North America (5/25, 20\%), Asia (5/25, 20\%), and Oceania (4/25, 16\%). Social environmental factors were most often considered (19/25, 76\%), followed by factors from the physical (8/25, 32\%), socioeconomic (1/25, 4\%), and systemic environment (1/25, 4\%). Environmental factors were used as the outcome (8/25, 32\%), setting variable (7/25, 28\%), moderator or facilitator (8/25, 32\%), and intervention component (3/25, 12\%). In most studies (19/25, 76\%), the intervention had a beneficial effect on the outcome of interest, and the included environmental factor played a supportive role in achieving this effect. In some studies, no effect (3/25, 12\%), mixed effects (2/25, 8\%), or adverse effects (1/25, 4\%) of the interventions were reported. Conclusions: This is the first comprehensive description of how environmental factors interact with technology-assisted interventions to increase or optimize PA in older adults. It was found that the investigation of environmental factors in this field is at an early stage. Environmental factors were found to play a supportive role in achieving beneficial effects of technology-assisted PA interventions, but the findings were based on a heterogeneous empirical platform. Still, certain aspects such as the application of virtual reality environments and social (or peer) comparison have shown significant potential that remains to be leveraged. A better understanding of intervention results and support in tailoring intervention programs can be provided through the inclusion of environmental aspects in technology-assisted PA interventions for older adults. ", doi="10.2196/59570", url="https://mhealth.jmir.org/2025/1/e59570" } @Article{info:doi/10.2196/59660, author="Woll, Simon and Birkenmaier, Dennis and Biri, Gergely and Nissen, Rebecca and Lutz, Luisa and Schroth, Marc and Ebner-Priemer, W. Ulrich and Giurgiu, Marco", title="Applying AI in the Context of the Association Between Device-Based Assessment of Physical Activity and Mental Health: Systematic Review", journal="JMIR Mhealth Uhealth", year="2025", month="Mar", day="6", volume="13", pages="e59660", keywords="machine learning", keywords="mental health", keywords="wearables", keywords="physical behavior", keywords="artificial intelligence", keywords="mobile phone", keywords="smartphone", abstract="Background: Wearable technology is used by consumers worldwide for continuous activity monitoring in daily life but more recently also for classifying or predicting mental health parameters like stress or depression levels. Previous studies identified, based on traditional approaches, that physical activity is a relevant factor in the prevention or management of mental health. However, upcoming artificial intelligence methods have not yet been fully established in the research field of physical activity and mental health. Objective: This systematic review aims to provide a comprehensive overview of studies that integrated passive monitoring of physical activity data measured via wearable technology in machine learning algorithms for the detection, prediction, or classification of mental health states and traits. Methods: We conducted a review of studies processing wearable data to gain insights into mental health parameters. Eligibility criteria were (1) the study uses wearables or smartphones to acquire physical behavior and optionally other sensor measurement data, (2) the study must use machine learning to process the acquired data, and (3) the study had to be published in a peer-reviewed English language journal. Studies were identified via a systematic search in 5 electronic databases. Results: Of 11,057 unique search results, 49 published papers between 2016 and 2023 were included. Most studies examined the connection between wearable sensor data and stress (n=15, 31\%) or depression (n=14, 29\%). In total, 71\% (n=35) of the studies had less than 100 participants, and 47\% (n=23) had less than 14 days of data recording. More than half of the studies (n=27, 55\%) used step count as movement measurement, and 44\% (n=21) used raw accelerometer values. The quality of the studies was assessed, scoring between 0 and 18 points in 9 categories (maximum 2 points per category). On average, studies were rated 6.47 (SD 3.1) points. Conclusions: The use of wearable technology for the detection, prediction, or classification of mental health states and traits is promising and offers a variety of applications across different settings and target groups. However, based on the current state of literature, the application of artificial intelligence cannot realize its full potential mostly due to a lack of methodological shortcomings and data availability. Future research endeavors may focus on the following suggestions to improve the quality of new applications in this context: first, by using raw data instead of already preprocessed data. Second, by using only relevant data based on empirical evidence. In particular, crafting optimal feature sets rather than using many individual detached features and consultation with in-field professionals. Third, by validating and replicating the existing approaches (ie, applying the model to unseen data). Fourth, depending on the research aim (ie, generalization vs personalization) maximizing the sample size or the duration over which data are collected. ", doi="10.2196/59660", url="https://mhealth.jmir.org/2025/1/e59660", url="http://www.ncbi.nlm.nih.gov/pubmed/40053765" } @Article{info:doi/10.2196/52887, author="Wang, Shirlene and Yang, Chih-Hsiang and Brown, Denver and Cheng, Alan and Kwan, W. Matthew Y.", title="Participant Compliance With Ecological Momentary Assessment in Movement Behavior Research Among Adolescents and Emerging Adults: Systematic Review", journal="JMIR Mhealth Uhealth", year="2025", month="Feb", day="11", volume="13", pages="e52887", keywords="compliance", keywords="ecological momentary assessment", keywords="mobile health", keywords="adolescents", keywords="emerging adults", keywords="physical activity", keywords="movement behavior", keywords="systematic review", keywords="cognitive", keywords="social", keywords="development", keywords="youth", keywords="literature search", keywords="inclusion", keywords="data quality", keywords="mobile phone", abstract="Background: Adolescence through emerging adulthood represents a critical period associated with changes in lifestyle behaviors. Understanding the dynamic relationships between cognitive, social, and environmental contexts is informative for the development of interventions aiming to help youth sustain physical activity and limit sedentary time during this life stage. Ecological momentary assessment (EMA) is an innovative method involving real-time assessment of individuals' experiences and behaviors in their naturalistic or everyday environments; however, EMA compliance can be problematic due to high participant burdens. Objective: This systematic review synthesized existing evidence pertaining to compliance in EMA studies that investigated wake-time movement behaviors among adolescent and emerging adult populations. Differences in EMA delivery scheme or protocol, EMA platforms, prompting schedules, and compensation methods---all of which can affect participant compliance and overall study quality---were examined. Methods: An electronic literature search was conducted in PubMed, PsycINFO, and Web of Science databases to select relevant papers that assessed movement behaviors among the population using EMA and reported compliance information for inclusion (n=52) in October 2022. Study quality was assessed using a modified version of the Checklist for Reporting of EMA Studies (CREMAS). Results: Synthesizing the existing evidence revealed several factors that influence compliance. The platform used for EMA studies could affect compliance and data quality in that studies using smartphones or apps might lessen additional burdens associated with delivering EMAs, yet most studies used web-based formats (n=18, 35\%). Study length was not found to affect EMA compliance rates, but the timing and frequency of prompts may be critical factors associated with missingness. For example, studies that only prompted participants once per day had higher compliance (91\% vs 77\%), but more frequent prompts provided more comprehensive data for researchers at the expense of increased participant burden. Similarly, studies with frequent prompting within the day may provide more representative data but may also be perceived as more burdensome and result in lower compliance. Compensation type did not significantly affect compliance, but additional motivational strategies could be applied to encourage participant response. Conclusions: Ultimately, researchers should consider the best strategies to limit burdens, balanced against requirements to answer the research question or phenomena being studied. Findings also highlight the need for greater consistency in reporting and more specificity when explaining procedures to understand how EMA compliance could be optimized in studies examining physical activity and sedentary time among youth. Trial Registration: PROSPERO CRD42021282093; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=282093 ", doi="10.2196/52887", url="https://mhealth.jmir.org/2025/1/e52887" } @Article{info:doi/10.2196/60521, author="Smits Serena, Ricardo and Hinterwimmer, Florian and Burgkart, Rainer and von Eisenhart-Rothe, Rudiger and Rueckert, Daniel", title="The Use of Artificial Intelligence and Wearable Inertial Measurement Units in Medicine: Systematic Review", journal="JMIR Mhealth Uhealth", year="2025", month="Jan", day="29", volume="13", pages="e60521", keywords="artificial intelligence", keywords="accelerometer", keywords="gyroscope", keywords="IMUs", keywords="time series data", keywords="wearable", keywords="systematic review", keywords="patient care", keywords="machine learning", keywords="data collection", abstract="Background: Artificial intelligence (AI) has already revolutionized the analysis of image, text, and tabular data, bringing significant advances across many medical sectors. Now, by combining with wearable inertial measurement units (IMUs), AI could transform health care again by opening new opportunities in patient care and medical research. Objective: This systematic review aims to evaluate the integration of AI models with wearable IMUs in health care, identifying current applications, challenges, and future opportunities. The focus will be on the types of models used, the characteristics of the datasets, and the potential for expanding and enhancing the use of this technology to improve patient care and advance medical research. Methods: This study examines this synergy of AI models and IMU data by using a systematic methodology, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, to explore 3 core questions: (1) Which medical fields are most actively researching AI and IMU data? (2) Which models are being used in the analysis of IMU data within these medical fields? (3) What are the characteristics of the datasets used for in this fields? Results: The median dataset size is of 50 participants, which poses significant limitations for AI models given their dependency on large datasets for effective training and generalization. Furthermore, our analysis reveals the current dominance of machine learning models in 76\% on the surveyed studies, suggesting a preference for traditional models like linear regression, support vector machine, and random forest, but also indicating significant growth potential for deep learning models in this area. Impressively, 93\% of the studies used supervised learning, revealing an underuse of unsupervised learning, and indicating an important area for future exploration on discovering hidden patterns and insights without predefined labels or outcomes. In addition, there was a preference for conducting studies in clinical settings (77\%), rather than in real-life scenarios, a choice that, along with the underapplication of the full potential of wearable IMUs, is recognized as a limitation in terms of practical applicability. Furthermore, the focus of 65\% of the studies on neurological issues suggests an opportunity to broaden research scope to other clinical areas such as musculoskeletal applications, where AI could have significant impacts. Conclusions: In conclusion, the review calls for a collaborative effort to address the highlighted challenges, including improvements in data collection, increasing dataset sizes, a move that inherently pushes the field toward the adoption of more complex deep learning models, and the expansion of the application of AI models on IMU data methodologies across various medical fields. This approach aims to enhance the reliability, generalizability, and clinical applicability of research findings, ultimately improving patient outcomes and advancing medical research. ", doi="10.2196/60521", url="https://mhealth.jmir.org/2025/1/e60521" } @Article{info:doi/10.2196/51994, author="Karoulla, Eirini and Matsangidou, Maria and Frangoudes, Fotos and Paspalides, Panayiotis and Neokleous, Kleanthis and Pattichis, S. Constantinos", title="Tracking Upper Limb Motion via Wearable Solutions: Systematic Review of Research From 2011 to 2023", journal="J Med Internet Res", year="2024", month="Dec", day="23", volume="26", pages="e51994", keywords="motion tracking", keywords="motion sensing", keywords="posture monitoring", keywords="wearable devices", keywords="upper limb rehabilitation", keywords="interactive feedback", keywords="real-time feedback", keywords="wearble technology", keywords="upper limb motion", abstract="Background: The development of wearable solutions for tracking upper limb motion has gained research interest over the past decade. This paper provides a systematic review of related research on the type, feasibility, signal processing techniques, and feedback of wearable systems for tracking upper limb motion, mostly in rehabilitation applications, to understand and monitor human movement. Objective: The aim of this article is to investigate how wearables are used to capture upper limb functions, especially related to clinical and rehabilitation applications. Methods: A systematic literature search identified 27 relevant studies published in English from 2011 to 2023, across 4 databases: ACM Digital Library, IEEE Xplore, PubMed,?and?ScienceDirect. We included papers focusing on motion or posture tracking for the upper limbs, wearable devices, feedback given to end users, and?systems having clinical or rehabilitation purposes. We excluded papers focusing on exoskeletons, robotics, prosthetics, orthoses, or activity recognition systems; reviews; and books. Results: The results from this research focus on wearable devices that are designed to monitor upper limb movement. More specifically, studies were divided into 2 distinct categories: clinical motion tracking (15/27, 56\%) and rehabilitation (12/27, 44\%), involving healthy individuals and patients, with a?total of 439 participants. Among the 27 studies, the majority (19/27) used inertial measurement units to track upper limb movement or smart textiles embedded with sensors. These devices were attached to the body with straps (mostly Velcro), providing flexibility and stability. The developed wearable devices positively influenced user motivation through the provided feedback, with visual feedback being the most common owing to the high level of independence provided. Moreover, a variety of signal processing techniques, such as Kalman and Butterworth filters, were applied to ensure data accuracy. However, limitations persist and include sensor positioning, calibration, and battery life, as well as a lack of clinical data on the effectiveness of these systems. The sampling rate of the data collection ranged from 50 Hz to 2000 Hz, which notably affected data quality and battery life. In addition, several findings were inconclusive, and thus, further future research is needed to understand and improve upper limb posture to develop progressive wearable systems. Conclusions: This paper offers a comprehensive overview of wearable monitoring systems, with a focus on upper limb motion tracking and rehabilitation. It emphasizes the various types of available solutions; their efficacy, wearability, and feasibility; and proposed processing techniques. Finally, it presents robust findings regarding feedback accuracy derived from experiments and outlines potential future research directions. ", doi="10.2196/51994", url="https://www.jmir.org/2024/1/e51994" } @Article{info:doi/10.2196/55189, author="Greenall-Ota, Josephine and Yapa, Manisha H. and Fox, J. Greg and Negin, Joel", title="Qualitative Evaluation of mHealth Implementation for Infectious Disease Care in Low- and Middle-Income Countries: Narrative Review", journal="JMIR Mhealth Uhealth", year="2024", month="Dec", day="13", volume="12", pages="e55189", keywords="mHealth", keywords="implementation", keywords="LMIC", keywords="infectious diseases", keywords="Tailored Implementation for Chronic Diseases", keywords="mobile phone", keywords="interventions", keywords="short messaging service", keywords="chronic disease", keywords="narrative review", keywords="barrier", keywords="mHealth intervention", keywords="infectious disease", keywords="screening", keywords="community", keywords="design", keywords="health system", keywords="SMS", keywords="app", abstract="Background: Mobile health (mHealth) interventions have the potential to improve health outcomes in low- and middle-income countries (LMICs) by aiding health workers to strengthen service delivery, as well as by helping patients and communities manage and prevent diseases. It is crucial to understand how best to implement mHealth within already burdened health services to maximally improve health outcomes and sustain the intervention in LMICs. Objective: We aimed to identify key barriers to and facilitators of the implementation of mHealth interventions for infectious diseases in LMICs, drawing on a health systems analysis framework. Methods: We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist to select qualitative or mixed methods studies reporting on determinants of already implemented infectious disease mHealth interventions in LMICs. We searched MEDLINE, Embase, PubMed, CINAHL, the Social Sciences Citation Index, and Global Health. We extracted characteristics of the mHealth interventions and implementation experiences, then conducted an analysis of determinants using the Tailored Implementation for Chronic Diseases framework. Results: We identified 10,494 titles for screening, among which 20 studies met our eligibility criteria. Of these, 9 studies examined mHealth smartphone apps and 11 examined SMS text messaging interventions. The interventions addressed HIV (n=7), malaria (n=4), tuberculosis (n=4), pneumonia (n=2), dengue (n=1), human papillomavirus (n=1), COVID-19 (n=1), and respiratory illnesses or childhood infectious diseases (n=2), with 2 studies addressing multiple diseases. Within these studies, 10 interventions were intended for use by health workers and the remainder targeted patients, at-risk individuals, or community members. Access to reliable technological resources, familiarity with technology, and training and support were key determinants of implementation. Additional themes included users forgetting to use the mHealth interventions and mHealth intervention designs affecting ease of use. Conclusions: Acceptance of the intervention and the capacity of existing health care system infrastructure and resources are 2 key factors affecting the implementation of mHealth interventions. Understanding the interaction between mHealth interventions, their implementation, and health systems will improve their uptake in LMICs. ", doi="10.2196/55189", url="https://mhealth.jmir.org/2024/1/e55189" } @Article{info:doi/10.2196/57708, author="Uzzaman, Nazim and Hammersley, Victoria and McClatchey, Kirstie and Sheringham, Jessica and Singh, Diksha and Habib, Monsur G. M. and Pinnock, Hilary", title="Effectiveness and Acceptability of Asynchronous Digital Health in Asthma Care: Mixed Methods Systematic Review", journal="J Med Internet Res", year="2024", month="Dec", day="3", volume="26", pages="e57708", keywords="digital health", keywords="asthma", keywords="asynchronous", keywords="asthma care", keywords="effectiveness", keywords="acceptability", keywords="mixed-methods review", keywords="systematic review", keywords="barrier", keywords="remote synchronous", keywords="chronic respiratory disease", keywords="self-management", keywords="digital technology", keywords="asynchronous consultation", keywords="caregiver", keywords="PRISMA", abstract="Background: Asynchronous digital health (eg, web-based portal, text, and email communication) can overcome practical barriers associated with in-person and remote synchronous (real-time) consultations. However, little is known about the effectiveness and acceptability of asynchronous digital health to support care for individuals with asthma (eg, asthma reviews). Objective: We aimed to systematically review the qualitative and quantitative evidence on the role of asynchronous digital health for asthma care. Methods: Following Cochrane methodology, we searched 6 databases (January 2001-July 2022; search update: September 2023) for quantitative, qualitative, or mixed methods studies supporting asthma care using asynchronous digital health. Screening and data extraction were duplicated. We assessed the risk of bias in the clinical outcomes of randomized controlled trials included in the meta-analysis using the revised Cochrane risk of bias tool. For the remaining studies, we evaluated the methodological quality using the Downs and Black checklist, critical appraisal skills program, and mixed methods appraisal tool for quantitative, qualitative, and mixed methods studies, respectively. We determined the confidence in the evidence using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) criteria. We conducted a meta-analysis of trial data and a thematic analysis of qualitative data. Results: We included 30 studies (20 quantitative, 6 qualitative, and 4 mixed methods) conducted in 9 countries involving individuals with asthma, their caregivers, and health care professionals. Asynchronous digital consultations linked with other functionalities, compared to usual care, improved asthma control (standardized mean difference 0.32, 95\% CI 0.02-0.63; P=.04) and reduced hospitalizations (risk ratio 0.36; 95\% CI 0.14-0.94; P=.04). However, there were no significant differences in quality of life (standardized mean difference 0.16; 95\% CI --0.12 to 0.43; P=.26) or emergency department visits (risk ratio 0.83; 95\% CI 0.33-2.09; P=.69). Patients appreciated the convenience of asynchronous digital health, though health care professionals expressed concerns. Successful implementation necessitated an organizational approach. Integrative synthesis underscored the ease of asking questions, monitoring logs, and medication reminders as key digital functionalities. Conclusions: Despite low confidence in evidence, asynchronous consultation supported by digital functionalities is an effective and convenient option for nonemergency asthma care. This type of consultation, well accepted by individuals with asthma and their caregivers, offers opportunities for those facing challenges with traditional synchronous consultations due to lifestyle or geographic constraints. However, efficient organizational strategies are needed to manage the associated workload. Trial Registration: PROSPERO CRD42022344224; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=344224 International Registered Report Identifier (IRRID): RR2-10.1371/journal.pone.0281538 ", doi="10.2196/57708", url="https://www.jmir.org/2024/1/e57708" } @Article{info:doi/10.2196/54826, author="Diez Alvarez, Sergio and Fellas, Antoni and Wynne, Katie and Santos, Derek and Sculley, Dean and Acharya, Shamasunder and Navathe, Pooshan and Giron{\`e}s, Xavier and Coda, Andrea", title="The Role of Smartwatch Technology in the Provision of Care for Type 1 or 2 Diabetes Mellitus or Gestational Diabetes: Systematic Review", journal="JMIR Mhealth Uhealth", year="2024", month="Dec", day="3", volume="12", pages="e54826", keywords="diabetes mellitus", keywords="flash glucose monitoring", keywords="digital health", keywords="smartwatch", keywords="smartphones", keywords="mHealth", keywords="mobile health", keywords="glucose monitoring", keywords="diabetes", keywords="gestational diabetes", keywords="systematic review", keywords="smartwatch technology", keywords="blood glucose", keywords="medication adherence", keywords="self-monitoring", keywords="usability", keywords="feasibility", keywords="mobile phone", abstract="Background: The use of smart technology in the management of all forms of diabetes mellitus has grown significantly in the past 10 years. Technologies such as the smartwatch have been proposed as a method of assisting in the monitoring of blood glucose levels as well as other alert prompts such as medication adherence and daily physical activity targets. These important outcomes reach across all forms of diabetes and have the potential to increase compliance of self-monitoring with the aim of improving long-term outcomes such as hemoglobin A1c (HbA1c). Objective: This systematic review aims to explore the literature for evidence of smartwatch technology in type 1, 2, and gestational diabetes. Methods: A systematic review was undertaken by searching Ovid MEDLINE and CINAHL databases. A second search using all identified keywords and index terms was performed on Ovid MEDLINE (January 1966 to August 2023), Embase (January 1980 to August 2023), Cochrane Central Register of Controlled Trials (CENTRAL, the Cochrane Library, latest issue), CINAHL (from 1982), IEEE Xplore, ACM Digital Libraries, and Web of Science databases. Type 1, type 2, and gestational diabetes were eligible for inclusion. Quantitative studies such as prospective cohort or randomized clinical trials that explored the feasibility, usability, or effect of smartwatch technology in people with diabetes were eligible. Outcomes of interest were changes in blood glucose or HbA1c, physical activity levels, medication adherence, and feasibility or usability scores. Results: Of the 8558 titles and abstracts screened, 5 studies were included for qualitative synthesis in this review. A total of 322 participants with either type 1 or type 2 diabetes mellitus were included in the review. A total of 4 studies focused on the feasibility and usability of smartwatch technology in diabetes management. One study conducted a proof-of-concept randomized clinical trial including smartwatch technology for exercise time prescriptions for participants with type 2 diabetes mellitus. Adherence of participants to smartwatch technology varied between included studies, with one reporting input submissions of 58\% and another reporting that participants logged 50\% more entries than they were required to. One study reported significantly improved glycemic control with integrated smartwatch technology, with increased exercise prescriptions; however, this study was not powered and required a longer observational period. Conclusions: This systematic review has highlighted the lack of robust randomized clinical trials that explore the efficacy of smartwatch technology in the management of patients with type 1, type 2, and gestational diabetes. Further research is required to establish the role of integrated smartwatch technology in important outcomes such as glycemic control, exercise participation, drug adherence, and diet monitoring in people with all forms of diabetes mellitus. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42019136825; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=136825 ", doi="10.2196/54826", url="https://mhealth.jmir.org/2024/1/e54826" } @Article{info:doi/10.2196/53236, author="Brocklehurst, P. Sarah and Morse, R. Alyssa and Cruwys, Tegan and Batterham, J. Philip and Leach, Liana and Robertson, M. Alysia and Sahib, Aseel and Burke, T. Colette and Nguyen, Jessica and Calear, L. Alison", title="Investigating the Effectiveness of Technology-Based Distal Interventions for Postpartum Depression and Anxiety: Systematic Review and Meta-Analysis", journal="J Med Internet Res", year="2024", month="Nov", day="19", volume="26", pages="e53236", keywords="postpartum", keywords="depression", keywords="anxiety", keywords="birth", keywords="adoptive", keywords="parents", keywords="mobile phone", abstract="Background: Postpartum anxiety and depression are common in new parents. While effective interventions exist, they are often delivered in person, which can be a barrier for some parents seeking help. One approach to overcoming these barriers is the delivery of evidence-based self-help interventions via websites, smartphone apps, and other digital media. Objective: This study aims to evaluate the effectiveness of technology-based distal interventions in reducing or preventing symptoms of postpartum depression or anxiety in male and female birth and adoptive parents, explore the effectiveness of technology-based distal interventions in increasing social ties, and determine the level of adherence to and satisfaction with technology-based distal interventions. Methods: A systematic review and series of meta-analyses were conducted. Three electronic bibliographic databases (PsycINFO, PubMed, and Cochrane Library) were searched for randomized controlled trials evaluating technology-based distal interventions for postpartum depression or anxiety in birth and adoptive parents. Searches were updated on August 1, 2023, before conducting the final meta-analyses. Data on trial characteristics, effectiveness, adherence, satisfaction, and quality were extracted. Screening and data extraction were conducted by 2 reviewers. Risk of bias was assessed using the Joanna Briggs Institute quality rating scale for randomized controlled trials. Studies were initially synthesized qualitatively. Where possible, studies were also quantitatively synthesized through 5 meta-analyses. Results: Overall, 18 articles met the inclusion criteria for the systematic review, with 14 (78\%) providing sufficient data for a meta-analysis. A small significant between-group effect on depression favored the intervention conditions at the postintervention (Cohen d=--0.28, 95\% CI --0.41 to --0.15; P<.001) and follow-up (Cohen d=--0.27, 95\% CI --0.52 to --0.02; P=.03) time points. A small significant effect on anxiety also favored the intervention conditions at the postintervention time point (Cohen d=--0.29, 95\% CI --0.48 to --0.10; P=.002), with a medium effect at follow-up (Cohen d=--0.47, 95\% CI --0.88 to --0.05; P=.03). The effect on social ties was not significant at the postintervention time point (Cohen d=0.04, 95\% CI --0.12 to 0.21; P=.61). Effective interventions tended to be web-based cognitive behavioral therapy programs with reminders. Adherence varied considerably between studies, whereas satisfaction tended to be high for most studies. Conclusions: Technology-based distal interventions are effective in reducing symptoms of postpartum depression and anxiety in birth mothers. Key limitations of the reviewed evidence include heterogeneity in outcome measures, studies being underpowered to detect modest effects, and the exclusion of key populations from the evidence base. More research needs to be conducted with birth fathers and adoptive parents to better ascertain the effectiveness of interventions in these populations, as well as to further assess the effect of technology-based distal interventions on social ties. Trial Registration: PROSPERO CRD42021290525; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=290525 ", doi="10.2196/53236", url="https://www.jmir.org/2024/1/e53236" } @Article{info:doi/10.2196/58127, author="Bowen-Forbes, Camille and Khondaker, Tilovatul and Stafinski, Tania and Hadizadeh, Maliheh and Menon, Devidas", title="Mobile Apps for the Personal Safety of At-Risk Children and Youth: Scoping Review", journal="JMIR Mhealth Uhealth", year="2024", month="Nov", day="5", volume="12", pages="e58127", keywords="children", keywords="youth", keywords="personal safety apps", keywords="smartphones", keywords="mobile apps", keywords="violence", keywords="bullying", keywords="suicide prevention", keywords="youth support", keywords="homeless support", keywords="mobile phone", abstract="Background: Personal safety is a widespread public health issue that affects people of all demographics. There is a growing interest in the use of mobile apps for enhancing personal safety, particularly for children and youth at risk, who are among the most vulnerable groups in society. Objective: This study aims to explore what is known about the use of mobile apps for personal safety among children and youth identified to be ``at risk.'' Methods: A scoping review following published methodological guidelines was conducted. In total, 5 databases (Scopus, SocINDEX, PsycINFO, Compendex, and Inspec Archive) were searched for relevant scholarly articles published between January 2005 and October 2023. The gray literature was searched using Google and Google Scholar search engines. The results were reported using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. For summarizing the features and users' experiences of the apps, a published framework for evaluating the quality of mobile health apps for youth was used. Results: A total of 1986 articles were identified, and 41 (2.1\%) were included in the review. Nine personal safety apps were captured and categorized into 4 groups based on the goals of the apps, as follows: dating and sexual violence prevention (n=4, 44\% of apps), bullying and school violence prevention (n=2, 22\% of apps), self-harm and suicide prevention (n=2, 22\% of apps), and homeless youth support (n=1, 11\% of apps). Of the 41 articles, 25 (61\%) provided data solely on app descriptions and features, while the remaining 16 (39\%) articles provided data on app evaluations and descriptions. Outcomes focused on app engagement, users' experiences, and effectiveness. Four articles reported on app use, 3 (75\%) of which reported relatively high app use. Data on users' experience were obtained from 13 studies. In general, participants found the app features to be easy to use and useful as educational resources and personal safety tools. Most of the views were positive. Negative perceptions included redundancy of app features and a lack of usefulness. Five apps were evaluated for effectiveness (n=2, 40\% dating and sexual violence prevention; n=2, 40\% self-harm and suicide prevention; and n=1, 20\% bullying and school violence prevention) and were all associated with a statistically significant reduction (P=.001 to .048) in harm or risk to participants at the 95\% CI. Conclusions: Although many personal safety apps are available, few studies have specifically evaluated those designed for youth. However, the evidence suggests that mobile safety apps generally appear to be beneficial for reducing harm to at-risk children and youth without any associated adverse events. Recommendations for future research have been made to strengthen the evidence and increase the availability of effective personal safety apps for children and youth. ", doi="10.2196/58127", url="https://mhealth.jmir.org/2024/1/e58127" } @Article{info:doi/10.2196/51875, author="Terhorst, Yannik and Knauer, Johannes and Philippi, Paula and Baumeister, Harald", title="The Relation Between Passively Collected GPS Mobility Metrics and Depressive Symptoms: Systematic Review and Meta-Analysis", journal="J Med Internet Res", year="2024", month="Nov", day="1", volume="26", pages="e51875", keywords="smart sensing", keywords="digital phenotyping", keywords="depression", keywords="GPS", keywords="global positioning system", keywords="meta-analysis", keywords="mobile phone", keywords="depressive symptoms", keywords="smartphone", keywords="systematic review", keywords="depressive disorders", keywords="treatment", keywords="mental disorder", keywords="mental health", keywords="wearable", abstract="Background: The objective, unobtrusively collected GPS features (eg, homestay and distance) from everyday devices like smartphones may offer a promising augmentation to current assessment tools for depression. However, to date, there is no systematic and meta-analytical evidence on the associations between GPS features and depression. Objective: This study aimed to investigate the between-person and within-person correlations between GPS mobility and activity features and depressive symptoms, and to critically review the quality and potential publication bias in the field. Methods: We searched MEDLINE, PsycINFO, Embase, CENTRAL, ACM, IEEE Xplore, PubMed, and Web of Science to identify eligible articles focusing on the correlations between GPS features and depression from December 6, 2022, to March 24, 2023. Inclusion and exclusion criteria were applied in a 2-stage inclusion process conducted by 2 independent reviewers (YT and JK). To be eligible, studies needed to report correlations between wearable-based GPS variables (eg, total distance) and depression symptoms measured with a validated questionnaire. Studies with underage persons and other mental health disorders were excluded. Between- and within-person correlations were analyzed using random effects models. Study quality was determined by comparing studies against the STROBE (Strengthening the Reporting of Observational studies in Epidemiology) guidelines. Publication bias was investigated using Egger test and funnel plots. Results: A total of k=19 studies involving N=2930 participants were included in the analysis. The mean age was 38.42 (SD 18.96) years with 59.64\% (SD 22.99\%) of participants being female. Significant between-person correlations between GPS features and depression were identified: distance (r=--0.25, 95\% CI --0.29 to --0.21), normalized entropy (r--0.17, 95\% CI --0.29 to --0.04), location variance (r--0.17, 95\% CI --0.26 to --0.04), entropy (r=--0.13, 95\% CI --0.23 to --0.04), number of clusters (r=--0.11, 95\% CI --0.18 to --0.03), and homestay (r=0.10, 95\% CI 0.00 to 0.19). Studies reporting within-correlations (k=3) were too heterogeneous to conduct meta-analysis. A deficiency in study quality and research standards was identified: all studies followed exploratory observational designs, but no study referenced or fully adhered to the international guidelines for reporting observational studies (STROBE). A total of 79\% (k=15) of the studies were underpowered to detect a small correlation (r=.20). Results showed evidence for potential publication bias. Conclusions: Our results provide meta-analytical evidence for between-person correlations of GPS mobility and activity features and depression. Hence, depression diagnostics may benefit from adding GPS mobility and activity features as an integral part of future assessment and expert tools. However, confirmatory studies for between-person correlations and further research on within-person correlations are needed. In addition, the methodological quality of the evidence needs to improve. Trial Registration: OSF Registeries cwder; https://osf.io/cwder ", doi="10.2196/51875", url="https://www.jmir.org/2024/1/e51875" } @Article{info:doi/10.2196/52383, author="Favara, Giuliana and Barchitta, Martina and Maugeri, Andrea and Magnano San Lio, Roberta and Agodi, Antonella", title="Sensors for Smoking Detection in Epidemiological Research: Scoping Review", journal="JMIR Mhealth Uhealth", year="2024", month="Oct", day="30", volume="12", pages="e52383", keywords="smoking", keywords="tobacco smoke", keywords="smoke exposure", keywords="cigarette smoking", keywords="wearable sensor", keywords="public health", abstract="Background: The use of wearable sensors is being explored as a challenging way to accurately identify smoking behaviors by measuring physiological and environmental factors in real-life settings. Although they hold potential benefits for aiding smoking cessation, no single wearable device currently achieves high accuracy in detecting smoking events. Furthermore, it is crucial to emphasize that this area of study is dynamic and requires ongoing updates. Objective: This scoping review aims to map the scientific literature for identifying the main sensors developed or used for tobacco smoke detection, with a specific focus on wearable sensors, as well as describe their key features and categorize them by type. Methods: According to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) protocol, an electronic search was conducted on the PubMed, MEDLINE, and Web of Science databases, using the following keywords: (``biosensors'' OR ``biosensor'' OR ``sensors'' OR ``sensor'' OR ``wearable'') AND (``smoking'' OR ``smoke''). Results: Among a total of 37 studies included in this scoping review published between 2012 and March 2024, 16 described sensors based on wearable bands, 15 described multisensory systems, and 6 described other strategies to detect tobacco smoke exposure. Included studies provided details about the design or application of wearable sensors based on an elastic band to detect different aspects of tobacco smoke exposure (eg, arm, wrist, and finger movements, and lighting events). Some studies proposed a system composed of different sensor modalities (eg, Personal Automatic Cigarette Tracker [PACT], PACT 2.0, and AutoSense). Conclusions: Our scoping review has revealed both the obstacles and opportunities linked to wearable devices, offering valuable insights for future research initiatives. Tackling the recognized challenges and delving into potential avenues for enhancement could elevate wearable devices into even more effective tools for aiding smoking cessation. In this context, continuous research is essential to fine-tune and optimize these devices, guaranteeing their practicality and reliability in real-world applications. ", doi="10.2196/52383", url="https://mhealth.jmir.org/2024/1/e52383" } @Article{info:doi/10.2196/49449, author="Hach, Sylvia and Alder, Gemma and Stavric, Verna and Taylor, Denise and Signal, Nada", title="Usability Assessment Methods for Mobile Apps for Physical Rehabilitation: Umbrella Review", journal="JMIR Mhealth Uhealth", year="2024", month="Oct", day="4", volume="12", pages="e49449", keywords="usability", keywords="quality evaluation", keywords="mobile health", keywords="physical exercise", keywords="rehabilitation", keywords="overview", keywords="umbrella review", keywords="psychometrics", abstract="Background: Usability has been touted as one determiner of success of mobile health (mHealth) interventions. Multiple systematic reviews of usability assessment approaches for different mHealth solutions for physical rehabilitation are available. However, there is a lack of synthesis in this portion of the literature, which results in clinicians and developers devoting a significant amount of time and effort in analyzing and summarizing a large body of systematic reviews. Objective: This study aims to summarize systematic reviews examining usability assessment instruments, or measurements tools, in mHealth interventions including physical rehabilitation. Methods: An umbrella review was conducted according to a published registered protocol. A topic-based search of PubMed, Cochrane, IEEE Xplore, Epistemonikos, Web of Science, and CINAHL Complete was conducted from January 2015 to April 2023 for systematic reviews investigating usability assessment instruments in mHealth interventions including physical exercise rehabilitation. Eligibility screening included date, language, participant, and article type. Data extraction and assessment of the methodological quality (AMSTAR 2 [A Measurement Tool to Assess Systematic Reviews 2]) was completed and tabulated for synthesis. Results: A total of 12 systematic reviews were included, of which 3 (25\%) did not refer to any theoretical usability framework and the remaining (n=9, 75\%) most commonly referenced the ISO framework. The sample referenced a total of 32 usability assessment instruments and 66 custom-made, as well as hybrid, instruments. Information on psychometric properties was included for 9 (28\%) instruments with satisfactory internal consistency and structural validity. A lack of reliability, responsiveness, and cross-cultural validity data was found. The methodological quality of the systematic reviews was limited, with 8 (67\%) studies displaying 2 or more critical weaknesses. Conclusions: There is significant diversity in the usability assessment of mHealth for rehabilitation, and a link to theoretical models is often lacking. There is widespread use of custom-made instruments, and preexisting instruments often do not display sufficient psychometric strength. As a result, existing mHealth usability evaluations are difficult to compare. It is proposed that multimethod usability assessment is used and that, in the selection of usability assessment instruments, there is a focus on explicit reference to their theoretical underpinning and acceptable psychometric properties. This could be facilitated by a closer collaboration between researchers, developers, and clinicians throughout the phases of mHealth tool development. Trial Registration: PROSPERO CRD42022338785; https://www.crd.york.ac.uk/prospero/\#recordDetails ", doi="10.2196/49449", url="https://mhealth.jmir.org/2024/1/e49449" } @Article{info:doi/10.2196/59587, author="Ortiz, L. Bengie and Gupta, Vibhuti and Kumar, Rajnish and Jalin, Aditya and Cao, Xiao and Ziegenbein, Charles and Singhal, Ashutosh and Tewari, Muneesh and Choi, Won Sung", title="Data Preprocessing Techniques for AI and Machine Learning Readiness: Scoping Review of Wearable Sensor Data in Cancer Care", journal="JMIR Mhealth Uhealth", year="2024", month="Sep", day="27", volume="12", pages="e59587", keywords="machine learning", keywords="artificial intelligence", keywords="preprocessing", keywords="wearables", keywords="mobile phone", keywords="cancer care", abstract="Background: Wearable sensors are increasingly being explored in health care, including in cancer care, for their potential in continuously monitoring patients. Despite their growing adoption, significant challenges remain in the quality and consistency of data collected from wearable sensors. Moreover, preprocessing pipelines to clean, transform, normalize, and standardize raw data have not yet been fully optimized. Objective: This study aims to conduct a scoping review of preprocessing techniques used on raw wearable sensor data in cancer care, specifically focusing on methods implemented to ensure their readiness for artificial intelligence and machine learning (AI/ML) applications. We sought to understand the current landscape of approaches for handling issues, such as noise, missing values, normalization or standardization, and transformation, as well as techniques for extracting meaningful features from raw sensor outputs and converting them into usable formats for subsequent AI/ML analysis. Methods: We systematically searched IEEE Xplore, PubMed, Embase, and Scopus to identify potentially relevant studies for this review. The eligibility criteria included (1) mobile health and wearable sensor studies in cancer, (2) written and published in English, (3) published between January 2018 and December 2023, (4) full text available rather than abstracts, and (5) original studies published in peer-reviewed journals or conferences. Results: The initial search yielded 2147 articles, of which 20 (0.93\%) met the inclusion criteria. Three major categories of preprocessing techniques were identified: data transformation (used in 12/20, 60\% of selected studies), data normalization and standardization (used in 8/20, 40\% of the selected studies), and data cleaning (used in 8/20, 40\% of the selected studies). Transformation methods aimed to convert raw data into more informative formats for analysis, such as by segmenting sensor streams or extracting statistical features. Normalization and standardization techniques usually normalize the range of features to improve comparability and model convergence. Cleaning methods focused on enhancing data reliability by handling artifacts like missing values, outliers, and inconsistencies. Conclusions: While wearable sensors are gaining traction in cancer care, realizing their full potential hinges on the ability to reliably translate raw outputs into high-quality data suitable for AI/ML applications. This review found that researchers are using various preprocessing techniques to address this challenge, but there remains a lack of standardized best practices. Our findings suggest a pressing need to develop and adopt uniform data quality and preprocessing workflows of wearable sensor data that can support the breadth of cancer research and varied patient populations. Given the diverse preprocessing techniques identified in the literature, there is an urgency for a framework that can guide researchers and clinicians in preparing wearable sensor data for AI/ML applications. For the scoping review as well as our research, we propose a general framework for preprocessing wearable sensor data, designed to be adaptable across different disease settings, moving beyond cancer care. ", doi="10.2196/59587", url="https://mhealth.jmir.org/2024/1/e59587", url="http://www.ncbi.nlm.nih.gov/pubmed/38626290" } @Article{info:doi/10.2196/55819, author="Kachimanga, Chiyembekezo and Zaniku, Robbins Haules and Divala, Henry Titus and Ket, C.F Johannes and Mukherjee, S. Joia and Palazuelos, Daniel and Kulinkina, V. Alexandra and Abejirinde, Omolade Ibukun-Oluwa and Akker, den Thomas van", title="Evaluating the Adoption of mHealth Technologies by Community Health Workers to Improve the Use of Maternal Health Services in Sub-Saharan Africa: Systematic Review", journal="JMIR Mhealth Uhealth", year="2024", month="Sep", day="24", volume="12", pages="e55819", keywords="maternal health", keywords="antenatal care", keywords="postnatal care", keywords="facility-based births", keywords="sub-Saharan Africa", keywords="mobile health", keywords="mHealth", keywords="review", keywords="narrative synthesis", keywords="mobile phone", abstract="Background: Limited information exists on the impact of mobile health (mHealth) use by community health workers (CHWs) on improving the use of maternal health services in sub-Saharan Africa (SSA). Objective: This systematic review addresses 2 objectives: evaluating the impact of mHealth use by CHWs on antenatal care (ANC) use, facility-based births, and postnatal care (PNC) use in SSA; and identifying facilitators and barriers to mHealth use by CHWs in programs designed to increase ANC use, facility-based births, and PNC use in SSA using a sociotechnical system approach. Methods: We searched for articles in 6 databases (MEDLINE, CINAHL, Web of Science, Embase, Scopus, and Africa Index Medicus) from inception up to September 2022, with additional articles identified from Google Scholar. After article selection, 2 independent reviewers performed title and abstract screening, full-text screening, and data extraction using Covidence software (Veritas Health Innovation Ltd). In addition, we manually screened the references lists of the included articles. Finally, we performed a narrative synthesis of the outcomes. Results: Among the 2594 records retrieved, 10 (0.39\%) studies (n=22, 0.85\% articles) met the inclusion criteria and underwent data extraction. The studies were published between 2012 and 2022 in 6 countries. Of the studies reporting on ANC outcomes, 43\% (3/7) reported that mHealth use by CHWs increased ANC use. Similarly, of the studies reporting on facility-based births, 89\% (8/9) demonstrated an increase due to mHealth use by CHWs. In addition, in the PNC studies, 75\% (3/4) showed increased PNC use associated with mHealth use by CHWs. Many of the studies reported on the importance of addressing factors related to the social environment of mHealth-enabled CHWs, including the perception of CHWs by the community, trust, relationships, digital literacy, training, mentorship and supervision, skills, CHW program ownership, and the provision of incentives. Very few studies reported on how program goals and culture influenced mHealth use by CHWs. Providing free equipment, accessories, and internet connectivity while addressing ongoing challenges with connectivity, power, the ease of using mHealth software, and equipment maintenance support allowed mHealth-enabled CHW programs to thrive. Conclusions: mHealth use by CHWs was associated with an increase in ANC use, facility-based births, and PNC use in SSA. Identifying and addressing social and technical barriers to the use of mHealth is essential to ensure the success of mHealth programs. Trial Registration: PROSPERO CRD42022346364; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=346364 ", doi="10.2196/55819", url="https://mhealth.jmir.org/2024/1/e55819", url="http://www.ncbi.nlm.nih.gov/pubmed/39316427" } @Article{info:doi/10.2196/51273, author="Magnuson, I. Katherine and Li, Kexin and Beuley, Grace and Ryan-Pettes, R. Stacy", title="The Use of Noncommercial Parent-Focused mHealth Interventions for Behavioral Problems in Youth: Systematic Review", journal="JMIR Mhealth Uhealth", year="2024", month="Sep", day="24", volume="12", pages="e51273", keywords="behavioral parent training", keywords="mobile health", keywords="mHealth", keywords="mobile app", keywords="adolescent", keywords="substance use", keywords="child mental health condition", keywords="mobile phone", abstract="Background: The rates of substance use among adolescents are alarmingly high, and current treatment options lack integration of parent-focused interventions, despite evidence that effective parenting practices can mediate treatment outcomes for adolescents involved in substance use. Accessibility and other barriers to parental interventions may be mitigated through mobile health (mHealth); however, few mHealth platforms target substance use behaviors for adolescents through the implementation of behavioral parent training strategies. Objective: This study seeks to review current mHealth platforms within empirical literature that are designed to increase effective parenting through behavioral parent training techniques. Because of the paucity of mHealth modalities that use parenting strategies to target substance use in adolescents, the objective was expanded to include mHealth platforms addressing behavior problems among youth, given that parent-targeted treatments for these clinical presentations overlap with those for adolescent substance use. Overall, the systematic review was conducted to inform the development of mHealth apps for parents of youth involved in substance use, improve accessibility, and better align with parental needs. Methods: This systematic review was conducted using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method to select relevant articles across several databases. Each study was assessed for relevance and inclusion. Each study was reviewed for demographics, delivery medium, intervention status as stand-alone treatment or as an enhancement to treatment, mobile device used, mental health condition targeted, intervention type, underlying intervention theory, behavior change theory applied in design, behavior change techniques, parent training techniques, youth outcomes, parent outcomes, visual design, content, and features. Results: Overall, 11 studies were included. Nearly all studies (9/11, 82\%) predominantly sampled female caregivers. Most of the studies (6/11, 55\%) integrated social learning theory. Only a few of the studies (2/11, 18\%) discussed the embedded behavior change theories, whereas all the studies (11/11, 100\%) used at least one behavior change technique to encourage change in parental behaviors. Many of the studies (7/11, 64\%) tailored design features to the end user. Of the various behavioral parent training techniques, nearly all studies (10/11, 91\%) included the skill of strengthening the parent-child relationship. A preliminary evaluation of treatment outcomes suggests a positive impact of parent-targeted mHealth interventions. When reported, the effect sizes for treatment ranged from Cohen d=0.38 to Cohen d=1.58 for youth and from Cohen d=0.13 to Cohen d=2.59 for parents. Conclusions: Although features and techniques were referenced, only a few of the studies provided specific information related to behavior change theory (2/11, 18\%), visual design (2/11, 18\%), and the translation of parent-targeted interventions to mHealth platforms. Such information would be useful for the development of mHealth apps. Preliminary outcomes for youth and parents are encouraging, but future studies should consider conducting a meta-analysis as the body of studies grows to determine aggregate statistical findings. ", doi="10.2196/51273", url="https://mhealth.jmir.org/2024/1/e51273", url="http://www.ncbi.nlm.nih.gov/pubmed/39316435" } @Article{info:doi/10.2196/56972, author="Singh, Ben and Chastin, Sebastien and Miatke, Aaron and Curtis, Rachel and Dumuid, Dorothea and Brinsley, Jacinta and Ferguson, Ty and Szeto, Kimberley and Simpson, Catherine and Eglitis, Emily and Willems, Iris and Maher, Carol", title="Real-World Accuracy of Wearable Activity Trackers for Detecting Medical Conditions: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2024", month="Aug", day="30", volume="12", pages="e56972", keywords="wearable activity trackers", keywords="disease detection", keywords="atrial fibrillation", keywords="COVID-19 diagnosis", keywords="meta-analysis", keywords="wearables", keywords="wearable tracker", keywords="tracker", keywords="detection", keywords="monitoring", keywords="physiological", keywords="diagnostic tool", keywords="tool", keywords="tools", keywords="Fitbit", keywords="atrial", keywords="COVID-19", keywords="wearable", abstract="Background: Wearable activity trackers, including fitness bands and smartwatches, offer the potential for disease detection by monitoring physiological parameters. However, their accuracy as specific disease diagnostic tools remains uncertain. Objective: This systematic review and meta-analysis aims to evaluate whether wearable activity trackers can be used to detect disease and medical events. Methods: Ten electronic databases were searched for studies published from inception to April 1, 2023. Studies were eligible if they used a wearable activity tracker to diagnose or detect a medical condition or event (eg, falls) in free-living conditions in adults. Meta-analyses were performed to assess the overall area under the curve (\%), accuracy (\%), sensitivity (\%), specificity (\%), and positive predictive value (\%). Subgroup analyses were performed to assess device type (Fitbit, Oura ring, and mixed). The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Diagnostic Test Accuracy Studies. Results: A total of 28 studies were included, involving a total of 1,226,801 participants (age range 28.6-78.3). In total, 16 (57\%) studies used wearables for diagnosis of COVID-19, 5 (18\%) studies for atrial fibrillation, 3 (11\%) studies for arrhythmia or abnormal pulse, 3 (11\%) studies for falls, and 1 (4\%) study for viral symptoms. The devices used were Fitbit (n=6), Apple watch (n=6), Oura ring (n=3), a combination of devices (n=7), Empatica E4 (n=1), Dynaport MoveMonitor (n=2), Samsung Galaxy Watch (n=1), and other or not specified (n=2). For COVID-19 detection, meta-analyses showed a pooled area under the curve of 80.2\% (95\% CI 71.0\%-89.3\%), an accuracy of 87.5\% (95\% CI 81.6\%-93.5\%), a sensitivity of 79.5\% (95\% CI 67.7\%-91.3\%), and specificity of 76.8\% (95\% CI 69.4\%-84.1\%). For atrial fibrillation detection, pooled positive predictive value was 87.4\% (95\% CI 75.7\%-99.1\%), sensitivity was 94.2\% (95\% CI 88.7\%-99.7\%), and specificity was 95.3\% (95\% CI 91.8\%-98.8\%). For fall detection, pooled sensitivity was 81.9\% (95\% CI 75.1\%-88.1\%) and specificity was 62.5\% (95\% CI 14.4\%-100\%). Conclusions: Wearable activity trackers show promise in disease detection, with notable accuracy in identifying atrial fibrillation and COVID-19. While these findings are encouraging, further research and improvements are required to enhance their diagnostic precision and applicability. Trial Registration: Prospero CRD42023407867; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=407867 ", doi="10.2196/56972", url="https://mhealth.jmir.org/2024/1/e56972" } @Article{info:doi/10.2196/53211, author="Mudzengi, Lawrence Don and Chomutare, Herbert and Nagudi, Jeniffer and Ntshiqa, Thobani and Davis, Lucian J. and Charalambous, Salome and Velen, Kavindhran", title="Using mHealth Technologies for Case Finding in Tuberculosis and Other Infectious Diseases in Africa: Systematic Review", journal="JMIR Mhealth Uhealth", year="2024", month="Aug", day="26", volume="12", pages="e53211", keywords="mobile health", keywords="mHealth", keywords="design thinking", keywords="tuberculosis", keywords="Ebola", keywords="HIV", keywords="COVID-19", keywords="infectious diseases", keywords="contact tracing", keywords="mobile phone", abstract="Background: Mobile health (mHealth) technologies are increasingly used in contact tracing and case finding, enhancing and replacing traditional methods for managing infectious diseases such as Ebola, tuberculosis, COVID-19, and HIV. However, the variations in their development approaches, implementation scopes, and effectiveness introduce uncertainty regarding their potential to improve public health outcomes. Objective: We conducted this systematic review to explore how mHealth technologies are developed, implemented, and evaluated. We aimed to deepen our understanding of mHealth's role in contact tracing, enhancing both the implementation and overall health outcomes. Methods: We searched and reviewed studies conducted in Africa focusing on tuberculosis, Ebola, HIV, and COVID-19 and published between 1990 and 2023 using the PubMed, Scopus, Web of Science, and Google Scholar databases. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to review, synthesize, and report the findings from articles that met our criteria. Results: We identified 11,943 articles, but only 19 (0.16\%) met our criteria, revealing a large gap in technologies specifically aimed at case finding and contact tracing of infectious diseases. These technologies addressed a broad spectrum of diseases, with a predominant focus on Ebola and tuberculosis. The type of technologies used ranged from mobile data collection platforms and smartphone apps to advanced geographic information systems (GISs) and bidirectional communication systems. Technologies deployed in programmatic settings, often developed using design thinking frameworks, were backed by significant funding and often deployed at a large scale but frequently lacked rigorous evaluations. In contrast, technologies used in research settings, although providing more detailed evaluation of both technical performance and health outcomes, were constrained by scale and insufficient funding. These challenges not only prevented these technologies from being tested on a wider scale but also hindered their ability to provide actionable and generalizable insights that could inform public health policies effectively. Conclusions: Overall, this review underscored a need for organized development approaches and comprehensive evaluations. A significant gap exists between the expansive deployment of mHealth technologies in programmatic settings, which are typically well funded and rigorously developed, and the more robust evaluations necessary to ascertain their effectiveness. Future research should consider integrating the robust evaluations often found in research settings with the scale and developmental rigor of programmatic implementations. By embedding advanced research methodologies within programmatic frameworks at the design thinking stage, mHealth technologies can potentially become technically viable and effectively meet specific contact tracing health outcomes to inform policy effectively. ", doi="10.2196/53211", url="https://mhealth.jmir.org/2024/1/e53211" } @Article{info:doi/10.2196/54511, author="Niyomyart, Atsadaporn and Ruksakulpiwat, Suebsarn and Benjasirisan, Chitchanok and Phianhasin, Lalipat and Nigussie, Kabtamu and Thorngthip, Sutthinee and Shamita, Gazi and Thampakkul, Jai and Begashaw, Lidya", title="Current Status of Barriers to mHealth Access Among Patients With Stroke and Steps Toward the Digital Health Era: Systematic Review", journal="JMIR Mhealth Uhealth", year="2024", month="Aug", day="22", volume="12", pages="e54511", keywords="digital health", keywords="mHealth", keywords="barrier", keywords="stroke", keywords="systematic review", keywords="mobile phones", abstract="Background: Mobile health (mHealth) offers significant benefits for patients with stroke, facilitating remote monitoring and personalized health care solutions beyond traditional settings. However, there is a dearth of comprehensive data, particularly qualitative insights, on the barriers to mHealth access. Understanding these barriers is crucial for devising strategies to enhance mHealth use among patients with stroke. Objective: This study aims to examine the recent literature focusing on barriers to mHealth access among patients with stroke. Methods: A systematic search of PubMed, MEDLINE, Web of Science, and CINAHL Plus Full Text was conducted for literature published between 2017 and 2023. Abstracts and full texts were independently screened based on predetermined inclusion and exclusion criteria. Data synthesis was performed using the convergent integrated analysis framework recommended by the Joanna Briggs Institute. Results: A total of 12 studies met the inclusion criteria. The majority were qualitative studies (about 42\%), followed by mixed methods (25\%), pilot studies (about 17\%), nonrandomized controlled trials (about 8\%), and observational studies (about 8\%). Participants included patients with stroke, caregivers, and various health care professionals. The most common mHealth practices were home-based telerehabilitation (30\%) and poststroke mHealth and telecare services (20\%). Identified barriers were categorized into two primary themes: (1) at the patient level and (2) at the health provider-patient-device interaction level. The first theme includes 2 subthemes: health-related issues and patient acceptability. The second theme encompassed 3 subthemes: infrastructure challenges (including software, networking, and hardware), support system deficiencies, and time constraints. Conclusions: This systematic review underscores significant barriers to mHealth adoption among patients with stroke. Addressing these barriers in future research is imperative to ensure that mHealth solutions effectively meet patients' needs. ", doi="10.2196/54511", url="https://mhealth.jmir.org/2024/1/e54511" } @Article{info:doi/10.2196/55625, author="Armfield, Nigel and Elphinston, Rachel and Liimatainen, Jenna and Scotti Requena, Simone and Eather, Chloe-Emily and Edirippulige, Sisira and Ritchie, Carrie and Robins, Sarah and Sterling, Michele", title="Development and Use of Mobile Messaging for Individuals With Musculoskeletal Pain Conditions: Scoping Review", journal="JMIR Mhealth Uhealth", year="2024", month="Aug", day="14", volume="12", pages="e55625", keywords="musculoskeletal", keywords="pain", keywords="SMS text messaging", keywords="mobile health", keywords="mHealth", keywords="intervention design", keywords="design", keywords="scoping review", keywords="musculoskeletal pain", keywords="development", keywords="mobile messaging", keywords="behavior change", keywords="efficacy", keywords="effectiveness", keywords="messaging", keywords="implementation", keywords="sustainability", keywords="mobile phone", abstract="Background: Population studies show that musculoskeletal conditions are a leading contributor to the total burden of healthy life lost, second only to cancer and with a similar burden to cardiovascular disease. Prioritizing the delivery of effective treatments is necessary, and with the ubiquity of consumer smart devices, the use of digital health interventions is increasing. Messaging is popular and easy to use and has been studied for a range of health-related uses, including health promotion, encouragement of behavior change, and monitoring of disease progression. It may have a useful role to play in the management and self-management of musculoskeletal conditions. Objective: Previous reviews on the use of messaging for people with musculoskeletal conditions have focused on synthesizing evidence of effectiveness from randomized controlled trials. In this review, our objective was to map the musculoskeletal messaging literature more broadly to identify information that may inform the design of future messaging interventions and summarize the current evidence of efficacy, effectiveness, and economics. Methods: Following a prepublished protocol developed using the Joanna Briggs Institute Manual for Evidence Synthesis, we conducted a comprehensive scoping review of the literature (2010-2022; sources: PubMed, CINAHL, Embase, and PsycINFO) related to SMS text messaging and app-based messaging for people with musculoskeletal conditions. We described our findings using tables, plots, and a narrative summary. Results: We identified a total of 8328 papers for screening, of which 50 (0.6\%) were included in this review (3/50, 6\% previous reviews and 47/50, 94\% papers describing 40 primary studies). Rheumatic diseases accounted for the largest proportion of the included primary studies (19/40, 48\%), followed by studies on multiple musculoskeletal conditions or pain sites (10/40, 25\%), back pain (9/40, 23\%), neck pain (1/40, 3\%), and ``other'' (1/40, 3\%). Most studies (33/40, 83\%) described interventions intended to promote positive behavior change, typically by encouraging increased physical activity and exercise. The studies evaluated a range of outcomes, including pain, function, quality of life, and medication adherence. Overall, the results either favored messaging interventions or had equivocal outcomes. While the theoretical underpinnings of the interventions were generally well described, only 4\% (2/47) of the papers provided comprehensive descriptions of the messaging intervention design and development process. We found no relevant economic evaluations. Conclusions: Messaging has been used for the care and self-management of a range of musculoskeletal conditions with generally favorable outcomes reported. However, with few exceptions, design considerations are poorly described in the literature. Further work is needed to understand and disseminate information about messaging content and message delivery characteristics, such as timing and frequency specifically for people with musculoskeletal conditions. Similarly, further work is needed to understand the economic effects of messaging and practical considerations related to implementation and sustainability. International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2021-048964 ", doi="10.2196/55625", url="https://mhealth.jmir.org/2024/1/e55625" } @Article{info:doi/10.2196/57258, author="Kokorelias, Marie Kristina and Grigorovich, Alisa and Harris, T. Maurita and Rehman, Umair and Ritchie, Louise and Levy, M. AnneMarie and Denecke, Kerstin and McMurray, Josephine", title="Longitudinal Coadaptation of Older Adults With Wearables and Voice-Activated Virtual Assistants: Scoping Review", journal="J Med Internet Res", year="2024", month="Aug", day="7", volume="26", pages="e57258", keywords="older adults", keywords="coadaptation", keywords="voice recognition", keywords="virtual assistant", keywords="wearable", keywords="artificial intelligence", keywords="smart-assistive technology", keywords="scoping review", keywords="review methods", keywords="review methodology", keywords="knowledge synthesis", keywords="synthesis", keywords="scoping", keywords="older adult", keywords="gerontechnology", keywords="technology", keywords="smart technology", keywords="smart technologies", keywords="smart", keywords="geriatrics", keywords="older people", keywords="geriatric", keywords="scoping literature review", keywords="protocol", keywords="Internet of Things", keywords="IoT", keywords="aging", keywords="PRISMA-ScR", keywords="Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews", keywords="user-centered design", keywords="design", keywords="user centered", keywords="mobile phone", abstract="Background: The integration of smart technologies, including wearables and voice-activated devices, is increasingly recognized for enhancing the independence and well-being of older adults. However, the long-term dynamics of their use and the coadaptation process with older adults remain poorly understood. This scoping review explores how interactions between older adults and smart technologies evolve over time to improve both user experience and technology utility. Objective: This review synthesizes existing research on the coadaptation between older adults and smart technologies, focusing on longitudinal changes in use patterns, the effectiveness of technological adaptations, and the implications for future technology development and deployment to improve user experiences. Methods: Following the Joanna Briggs Institute Reviewer's Manual and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, this scoping review examined peer-reviewed papers from databases including Ovid MEDLINE, Ovid Embase, PEDro, Ovid PsycINFO, and EBSCO CINAHL from the year 2000 to August 28, 2023, and included forward and backward searches. The search was updated on March 1, 2024. Empirical studies were included if they involved (1) individuals aged 55 years or older living independently and (2) focused on interactions and adaptations between older adults and wearables and voice-activated virtual assistants in interventions for a minimum period of 8 weeks. Data extraction was informed by the selection and optimization with compensation framework and the sex- and gender-based analysis plus theoretical framework and used a directed content analysis approach. Results: The search yielded 16,143 papers. Following title and abstract screening and a full-text review, 5 papers met the inclusion criteria. Study populations were mostly female participants and aged 73-83 years from the United States and engaged with voice-activated virtual assistants accessed through smart speakers and wearables. Users frequently used simple commands related to music and weather, integrating devices into daily routines. However, communication barriers often led to frustration due to devices' inability to recognize cues or provide personalized responses. The findings suggest that while older adults can integrate smart technologies into their lives, a lack of customization and user-friendly interfaces hinder long-term adoption and satisfaction. The studies highlight the need for technology to be further developed so they can better meet this demographic's evolving needs and call for research addressing small sample sizes and limited diversity. Conclusions: Our findings highlight a critical need for continued research into the dynamic and reciprocal relationship between smart technologies and older adults over time. Future studies should focus on more diverse populations and extend monitoring periods to provide deeper insights into the coadaptation process. Insights gained from this review are vital for informing the development of more intuitive, user-centric smart technology solutions to better support the aging population in maintaining independence and enhancing their quality of life. International Registered Report Identifier (IRRID): RR2-10.2196/51129 ", doi="10.2196/57258", url="https://www.jmir.org/2024/1/e57258" } @Article{info:doi/10.2196/53652, author="Wu, Weizi and Graziano, Teresa and Salner, Andrew and Chen, Ming-Hui and Judge, P. Michelle and Cong, Xiaomei and Xu, Wanli", title="Acceptability, Effectiveness, and Roles of mHealth Applications in Supporting Cancer Pain Self-Management: Integrative Review", journal="JMIR Mhealth Uhealth", year="2024", month="Jul", day="18", volume="12", pages="e53652", keywords="cancer pain", keywords="self-management", keywords="mHealth applications", keywords="integrative review", keywords="cancer survivors", abstract="Background: ?Cancer pain remains highly prevalent and persistent throughout survivorship, and it is crucial to investigate the potential of leveraging the advanced features of mobile health (mHealth) apps to empower individuals to self-manage their pain. Objective: ?This review aims to comprehensively understand the acceptability, users' experiences, and effectiveness of mHealth apps in supporting cancer pain self-management. Methods: ?We conducted an integrative review following Souza and Whittemore and Knafl's 6 review processes. Literature was searched in PubMed, Scopus, CINAHL Plus with Full Text, PsycINFO, and Embase, from 2013 to 2023. Keywords including ``cancer patients,'' ``pain,'' ``self-management,'' ``mHealth applications,'' and relevant synonyms were used in the search. The Johns Hopkins research evidence appraisal tool was used to evaluate the quality of eligible studies. A narrative synthesis was conducted to analyze the extracted data. Results: ?A total of 20 studies were included, with the overall quality rated as high (n=15) to good (n=5). Using mHealth apps to monitor and manage pain was acceptable for most patients with cancer. The internal consistency of the mHealth in measuring pain was 0.96. The reported daily assessment or engagement rate ranged from 61.9\% to 76.8\%. All mHealth apps were designed for multimodal interventions. Participants generally had positive experiences using pain apps, rating them as enjoyable and user-friendly. In addition, 6 studies reported significant improvements in health outcomes, including enhancement in pain remission (severity and intensity), medication adherence, and a reduced frequency of breakthrough pain. The most frequently highlighted roles of mHealth apps included pain monitoring, tracking, reminders, education facilitation, and support coordination. Conclusions: ?mHealth apps are effective and acceptable in supporting pain self-management. They offer a promising multi-model approach for patients to monitor, track, and manage their pain. These findings provide evidence-based insights for leveraging mHealth apps to support cancer pain self-management. More high-quality studies are needed to examine the effectiveness of digital technology--based interventions for cancer pain self-management and to identify the facilitators and barriers to their implementation in real-world practice. ", doi="10.2196/53652", url="https://mhealth.jmir.org/2024/1/e53652" } @Article{info:doi/10.2196/48802, author="Park, Sunghee and Lee, Sohye and Howard, Sheri and Yi, Jeeseon", title="Technology-Based Music Interventions to Reduce Anxiety and Pain Among Patients Undergoing Surgery or Procedures: Systematic Review of the Literature", journal="JMIR Mhealth Uhealth", year="2024", month="Jul", day="8", volume="12", pages="e48802", keywords="technology", keywords="music intervention", keywords="anxiety", keywords="pain", abstract="Background: Hospitalized patients undergoing surgery or procedures may experience negative symptoms. Music is a nonpharmacological complementary approach and is used as an intervention to reduce anxiety, stress, and pain in these patients. Recently, music has been used conveniently in clinical situations with technology devices, and the mode of providing music is an important factor in technology-based music interventions. However, many reviews have focused only on the effectiveness of music interventions. Objective: We aimed to review randomized controlled trials (RCTs) of technology-based music interventions for reducing anxiety and pain among patients undergoing surgery or procedures. We examined the clinical situation, devices used, delivery methods, and effectiveness of technology-based music interventions in primary articles. Methods: The search was performed in the following 5 electronic databases: PubMed, MEDLINE (OvidSP), CINAHL complete, PSYCINFO, and Embase. This systematic review focused on technology-based music interventions. The following articles were included: (1) RCTs, (2) studies using interactive technology (eg, smartphones, mHealth, tablets, applications, and virtual reality), (3) empirical studies reporting pain and anxiety outcomes, and (4) English articles published from 2018 to 2023 (as of January 18, 2023). The risk of bias was assessed using the Cochrane Risk of Bias tool version 2. Results: Among 292 studies identified, 21 met the inclusion criteria and were included. Of these studies, 9 reported that anxiety scores decreased after music interventions and 7 reported that pain could be decreased before, during, and after procedures. The methodology of the music intervention was important to the results on anxiety and pain in the clinical trials. More than 50\% (13/21, 62\%) of the studies included in this review allowed participants to select themes themselves. However, it was difficult to distinguish differences in effects depending on the device or software used for the music interventions. Conclusions: Technology-based music interventions could help reduce anxiety and pain among patients undergoing surgery or procedures. The findings of this review could help medical teams to choose a practical methodology for music interventions. Future studies should examine the effects of advanced technology-based music interventions using smart devices and software that promote interactions between medical staff and patients. ", doi="10.2196/48802", url="https://mhealth.jmir.org/2024/1/e48802" } @Article{info:doi/10.2196/50186, author="Ali, Suad and Alizai, Hira and Hagos, Jemal Delal and Rubio, Ramos Sindy and Calabia, Dale and Serrano Jimenez, Penelope and Senthil, Aarif Vinuu and Appel, Lora", title="mHealth Apps for Dementia, Alzheimer Disease, and Other Neurocognitive Disorders: Systematic Search and Environmental Scan", journal="JMIR Mhealth Uhealth", year="2024", month="Jul", day="3", volume="12", pages="e50186", keywords="dementia", keywords="Alzheimer disease", keywords="mHealth", keywords="mobile health", keywords="apps", keywords="lifestyle behaviors", keywords="mobile phone", abstract="Background: Lifestyle behaviors including exercise, sleep, diet, stress, mental stimulation, and social interaction significantly impact the likelihood of developing dementia. Mobile health (mHealth) apps have been valuable tools in addressing these lifestyle behaviors for general health and well-being, and there is growing recognition of their potential use for brain health and dementia prevention. Effective apps must be evidence-based and safeguard user data, addressing gaps in the current state of dementia-related mHealth apps. Objective: This study aims to describe the scope of available apps for dementia prevention and risk factors, highlighting gaps and suggesting a path forward for future development. Methods: A systematic search of mobile app stores, peer-reviewed literature, dementia and Alzheimer association websites, and browser searches was conducted from October 19, 2022, to November 2, 2022. A total of 1044 mHealth apps were retrieved. After screening, 152 apps met the inclusion criteria and were coded by paired, independent reviewers using an extraction framework. The framework was adapted from the Silberg scale, other scoping reviews of mHealth apps for similar populations, and background research on modifiable dementia risk factors. Coded elements included evidence-based and expert credibility, app features, lifestyle elements of focus, and privacy and security. Results: Of the 152 apps that met the final selection criteria, 88 (57.9\%) addressed modifiable lifestyle behaviors associated with reducing dementia risk. However, many of these apps (59/152, 38.8\%) only addressed one lifestyle behavior, with mental stimulation being the most frequently addressed. More than half (84/152, 55.2\%) scored 2 points out of 9 on the Silberg scale, with a mean score of 2.4 (SD 1.0) points. Most of the 152 apps did not disclose essential information: 120 (78.9\%) did not disclose expert consultation, 125 (82.2\%) did not disclose evidence-based information, 146 (96.1\%) did not disclose author credentials, and 134 (88.2\%) did not disclose their information sources. In addition, 105 (69.2\%) apps did not disclose adherence to data privacy and security practices. Conclusions: There is an opportunity for mHealth apps to support individuals in engaging in behaviors linked to reducing dementia risk. While there is a market for these products, there is a lack of dementia-related apps focused on multiple lifestyle behaviors. Gaps in the rigor of app development regarding evidence base, credibility, and adherence to data privacy and security standards must be addressed. Following established and validated guidelines will be necessary for dementia-related apps to be effective and advance successfully. ", doi="10.2196/50186", url="https://mhealth.jmir.org/2024/1/e50186" } @Article{info:doi/10.2196/52341, author="Hou, Ling Qiao and Liu, Yang Le and Wu, Ying", title="The Effects of mHealth Interventions on Quality of Life, Anxiety, and Depression in Patients With Coronary Heart Disease: Meta-Analysis of Randomized Controlled Trials", journal="J Med Internet Res", year="2024", month="Jun", day="11", volume="26", pages="e52341", keywords="mobile health", keywords="coronary heart disease", keywords="quality of life", keywords="anxiety", keywords="depression", keywords="meta-analysis", keywords="mobile phone", abstract="Background: Coronary heart disease (CHD) is the leading cause of death globally. In addition, 20\% to 40\% of the patients with CHD have comorbid mental health issues such as anxiety or depression, affecting the prognosis and quality of life (QoL). Mobile health (mHealth) interventions have been developed and are widely used; however, the evidence for the effects of mHealth interventions on QoL, anxiety, and depression in patients with CHD is currently ambiguous. Objective: In this study, we aimed to assess the effects of mHealth interventions on QoL, anxiety, and depression in patients with CHD. Methods: We searched the Cochrane Library, PubMed, Embase, CINAHL, Web of Science, China National Knowledge Infrastructure, and Wanfang databases from inception to August 12, 2023. Eligible studies were randomized controlled trials that involved patients with CHD who received mHealth interventions and that reported on QoL, anxiety, or depression outcomes. We used the Cochrane risk-of-bias tool for randomized trials to evaluate the risk of bias in the studies, ensuring a rigorous and methodologically sound analysis. Review Manager (desktop version 5.4; The Cochrane Collaboration) and Stata MP (version 17.0; StataCorp LLC) were used to conduct the meta-analysis. The effect size was calculated using the standardized mean difference (SMD) and its 95\% CI. Results: The meta-analysis included 23 studies (5406 participants in total) and showed that mHealth interventions significantly improved QoL in patients with CHD (SMD 0.49, 95\% CI 0.25-0.72; Z=4.07; P<.001) as well as relieved their anxiety (SMD ?0.46, 95\% CI ?0.83 to ?0.08; Z=2.38; P=.02) and depression (SMD ?0.34, 95\% CI ?0.56 to ?0.12; Z=3.00; P=.003) compared to usual care. The subgroup analyses indicated a significant effect favoring the mHealth intervention on reducing anxiety and depressive symptoms compared to usual care, especially when (1) the intervention duration was ?6 months (P=.04 and P=.001), (2) the mHealth intervention was a simple one (only 1 mHealth intervention was used) (P=.01 and P<.001), (3) it was implemented during the COVID-19 pandemic (P=.04 and P=.01), (4) it was implemented in low- or middle-income countries (P=.01 and P=.02), (5) the intervention focused on mental health (P=.01 and P=.007), and (6) adherence rates were high (?90\%; P=.03 and P=.002). In addition, comparing mHealth interventions to usual care, there was an improvement in QoL when (1) the mHealth intervention was a simple one (P<.001), (2) it was implemented in low- or middle-income countries (P<.001), and (3) the intervention focused on mental health (P<.001). Conclusions: On the basis of the existing evidence, mHealth interventions might be effective in improving QoL and reducing anxiety and depression in patients with CHD. However, large sample, high-quality, and rigorously designed randomized controlled trials are needed to provide further evidence. Trial Registration: PROSPERO CRD42022383858; https://tinyurl.com/3ea2npxf ", doi="10.2196/52341", url="https://www.jmir.org/2024/1/e52341", url="http://www.ncbi.nlm.nih.gov/pubmed/38861710" } @Article{info:doi/10.2196/40689, author="Choi, Adrien and Ooi, Aysel and Lottridge, Danielle", title="Digital Phenotyping for Stress, Anxiety, and Mild Depression: Systematic Literature Review", journal="JMIR Mhealth Uhealth", year="2024", month="May", day="23", volume="12", pages="e40689", keywords="digital phenotyping", keywords="passive sensing", keywords="stress", keywords="anxiety", keywords="depression", keywords="PRISMA", keywords="Preferred Reporting Items for Systematic Reviews and Meta-Analyses", keywords="mobile phone", abstract="Background: Unaddressed early-stage mental health issues, including stress, anxiety, and mild depression, can become a burden for individuals in the long term. Digital phenotyping involves capturing continuous behavioral data via digital smartphone devices to monitor human behavior and can potentially identify milder symptoms before they become serious. Objective: This systematic literature review aimed to answer the following questions: (1) what is the evidence of the effectiveness of digital phenotyping using smartphones in identifying behavioral patterns related to stress, anxiety, and mild depression? and (2) in particular, which smartphone sensors are found to be effective, and what are the associated challenges? Methods: We used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) process to identify 36 papers (reporting on 40 studies) to assess the key smartphone sensors related to stress, anxiety, and mild depression. We excluded studies conducted with nonadult participants (eg, teenagers and children) and clinical populations, as well as personality measurement and phobia studies. As we focused on the effectiveness of digital phenotyping using smartphones, results related to wearable devices were excluded. Results: We categorized the studies into 3 major groups based on the recruited participants: studies with students enrolled in universities, studies with adults who were unaffiliated to any particular organization, and studies with employees employed in an organization. The study length varied from 10 days to 3 years. A range of passive sensors were used in the studies, including GPS, Bluetooth, accelerometer, microphone, illuminance, gyroscope, and Wi-Fi. These were used to assess locations visited; mobility; speech patterns; phone use, such as screen checking; time spent in bed; physical activity; sleep; and aspects of social interactions, such as the number of interactions and response time. Of the 40 included studies, 31 (78\%) used machine learning models for prediction; most others (n=8, 20\%) used descriptive statistics. Students and adults who experienced stress, anxiety, or depression visited fewer locations, were more sedentary, had irregular sleep, and accrued increased phone use. In contrast to students and adults, less mobility was seen as positive for employees because less mobility in workplaces was associated with higher performance. Overall, travel, physical activity, sleep, social interaction, and phone use were related to stress, anxiety, and mild depression. Conclusions: This study focused on understanding whether smartphone sensors can be effectively used to detect behavioral patterns associated with stress, anxiety, and mild depression in nonclinical participants. The reviewed studies provided evidence that smartphone sensors are effective in identifying behavioral patterns associated with stress, anxiety, and mild depression. ", doi="10.2196/40689", url="https://mhealth.jmir.org/2024/1/e40689", url="http://www.ncbi.nlm.nih.gov/pubmed/38780995" } @Article{info:doi/10.2196/46282, author="Wei, Lai and Wang, Jia Stephen", title="Motion Tracking of Daily Living and Physical Activities in Health Care: Systematic Review From Designers' Perspective", journal="JMIR Mhealth Uhealth", year="2024", month="May", day="6", volume="12", pages="e46282", keywords="motion tracking", keywords="daily living", keywords="physical activity", keywords="health care application", keywords="design", keywords="public health", keywords="systematic review", keywords="mobile phone", abstract="Background: Motion tracking technologies serve as crucial links between physical activities and health care insights, facilitating data acquisition essential for analyzing and intervening in physical activity. Yet, systematic methodologies for evaluating motion tracking data, especially concerning user activity recognition in health care applications, remain underreported. Objective: This study aims to systematically review motion tracking in daily living and physical activities, emphasizing the critical interaction among devices, users, and environments from a design perspective, and to analyze the process involved in health care application research. It intends to delineate the design and application intricacies in health care contexts, focusing on enhancing motion tracking data's accuracy and applicability for health monitoring and intervention strategies. Methods: Using a systematic review, this research scrutinized motion tracking data and their application in health care and wellness, examining studies from Scopus, Web of Science, EBSCO, and PubMed databases. The review used actor network theory and data-enabled design to understand the complex interplay between humans, devices, and environments within these applications. Results: Out of 1501 initially identified studies, 54 (3.66\%) were included for in-depth analysis. These articles predominantly used accelerometer and gyroscope sensors (n=43, 80\%) to monitor and analyze motion, demonstrating a strong preference for these technologies in capturing both dynamic and static activities. While incorporating portable devices (n=11, 20\%) and multisensor configurations (n=16, 30\%), the application of sensors across the body (n=15, 28\%) and within physical spaces (n=17, 31\%) highlights the diverse applications of motion tracking technologies in health care research. This diversity reflects the application's alignment with activity types ranging from daily movements to specialized scenarios. The results also reveal a diverse participant pool, including the general public, athletes, and specialized groups, with a focus on healthy individuals (n=31, 57\%) and athletes (n=14, 26\%). Despite this extensive application range, the focus primarily on laboratory-based studies (n=39, 72\%) aimed at professional uses, such as precise activity identification and joint functionality assessment, emphasizes a significant challenge in translating findings from controlled environments to the dynamic conditions of everyday physical activities. Conclusions: This study's comprehensive investigation of motion tracking technology in health care research reveals a significant gap between the methods used for data collection and their practical application in real-world scenarios. It proposes an innovative approach that includes designers in the research process, emphasizing the importance of incorporating data-enabled design framework. This ensures that motion data collection is aligned with the dynamic and varied nature of daily living and physical activities. Such integration is crucial for developing health applications that are accessible, intuitive, and tailored to meet diverse user needs. By leveraging a multidisciplinary approach that combines design, engineering, and health sciences, the research opens new pathways for enhancing the usability and effectiveness of health technologies. ", doi="10.2196/46282", url="https://mhealth.jmir.org/2024/1/e46282", url="http://www.ncbi.nlm.nih.gov/pubmed/38709547" } @Article{info:doi/10.2196/49024, author="Eaton, K. Cyd and McWilliams, Emma and Yablon, Dana and Kesim, Irem and Ge, Renee and Mirus, Karissa and Sconiers, Takeera and Donkoh, Alfred and Lawrence, Melanie and George, Cynthia and Morrison, Leigh Mary and Muther, Emily and Oates, R. Gabriela and Sathe, Meghana and Sawicki, S. Gregory and Snell, Carolyn and Riekert, Kristin", title="Cross-Cutting mHealth Behavior Change Techniques to Support Treatment Adherence and Self-Management of Complex Medical Conditions: Systematic Review", journal="JMIR Mhealth Uhealth", year="2024", month="May", day="1", volume="12", pages="e49024", keywords="cystic fibrosis", keywords="mobile health", keywords="technology", keywords="self-management", keywords="patient adherence", keywords="behavior intervention", keywords="mHealth intervention", keywords="systematic review", keywords="evaluation of mHealth", keywords="treatment adherence", keywords="mHealth", abstract="Background: Mobile health (mHealth) interventions have immense potential to support disease self-management for people with complex medical conditions following treatment regimens that involve taking medicine and other self-management activities. However, there is no consensus on what discrete behavior change techniques (BCTs) should be used in an effective adherence and self-management--promoting mHealth solution for any chronic illness. Reviewing the extant literature to identify effective, cross-cutting BCTs in mHealth interventions for adherence and self-management promotion could help accelerate the development, evaluation, and dissemination of behavior change interventions with potential generalizability across complex medical conditions. Objective: This study aimed to identify cross-cutting, mHealth-based BCTs to incorporate into effective mHealth adherence and self-management interventions for people with complex medical conditions, by systematically reviewing the literature across chronic medical conditions with similar adherence and self-management demands. Methods: A registered systematic review was conducted to identify published evaluations of mHealth adherence and self-management interventions for chronic medical conditions with complex adherence and self-management demands. The methodological characteristics and BCTs in each study were extracted using a standard data collection form. Results: A total of 122 studies were reviewed; the majority involved people with type 2 diabetes (28/122, 23\%), asthma (27/122, 22\%), and type 1 diabetes (19/122, 16\%). mHealth interventions rated as having a positive outcome on adherence and self-management used more BCTs (mean 4.95, SD 2.56) than interventions with no impact on outcomes (mean 3.57, SD 1.95) or those that used >1 outcome measure or analytic approach (mean 3.90, SD 1.93; P=.02). The following BCTs were associated with positive outcomes: self-monitoring outcomes of behavior (39/59, 66\%), feedback on outcomes of behavior (34/59, 58\%), self-monitoring of behavior (34/59, 58\%), feedback on behavior (29/59, 49\%), credible source (24/59, 41\%), and goal setting (behavior; 14/59, 24\%). In adult-only samples, prompts and cues were associated with positive outcomes (34/45, 76\%). In adolescent and young adult samples, information about health consequences (1/4, 25\%), problem-solving (1/4, 25\%), and material reward (behavior; 2/4, 50\%) were associated with positive outcomes. In interventions explicitly targeting medicine taking, prompts and cues (25/33, 76\%) and credible source (13/33, 39\%) were associated with positive outcomes. In interventions focused on self-management and other adherence targets, instruction on how to perform the behavior (8/26, 31\%), goal setting (behavior; 8/26, 31\%), and action planning (5/26, 19\%) were associated with positive outcomes. Conclusions: To support adherence and self-management in people with complex medical conditions, mHealth tools should purposefully incorporate effective and developmentally appropriate BCTs. A cross-cutting approach to BCT selection could accelerate the development of much-needed mHealth interventions for target populations, although mHealth intervention developers should continue to consider the unique needs of the target population when designing these tools. Trial Registration: PROSPERO CRD42021224407; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=224407 ", doi="10.2196/49024", url="https://mhealth.jmir.org/2024/1/e49024" } @Article{info:doi/10.2196/51478, author="Wang, Jun-Wei and Zhu, Zhicheng and Shuling, Zhang and Fan, Jia and Jin, Yu and Gao, Zhan-Le and Chen, Wan-Di and Li, Xue", title="Effectiveness of mHealth App--Based Interventions for Increasing Physical Activity and Improving Physical Fitness in Children and Adolescents: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2024", month="Apr", day="30", volume="12", pages="e51478", keywords="mobile health", keywords="mHealth apps", keywords="children and adolescents", keywords="physical activity", keywords="physical fitness", keywords="systematic review", keywords="meta-analysis", keywords="mobile phone", abstract="Background: The COVID-19 pandemic has significantly reduced physical activity (PA) levels and increased sedentary behavior (SB), which can lead to worsening physical fitness (PF). Children and adolescents may benefit from mobile health (mHealth) apps to increase PA and improve PF. However, the effectiveness of mHealth app--based interventions and potential moderators in this population are not yet fully understood. Objective: This study aims to review and analyze the effectiveness of mHealth app--based interventions in promoting PA and improving PF and identify potential moderators of the efficacy of mHealth app--based interventions in children and adolescents. Methods: We searched for randomized controlled trials (RCTs) published in the PubMed, Web of Science, EBSCO, and Cochrane Library databases until December 25, 2023, to conduct this meta-analysis. We included articles with intervention groups that investigated the effects of mHealth-based apps on PA and PF among children and adolescents. Due to high heterogeneity, a meta-analysis was conducted using a random effects model. The Cochrane Risk of Bias Assessment Tool was used to evaluate the risk of bias. Subgroup analysis and meta-regression analyses were performed to identify potential influences impacting effect sizes. Results: We included 28 RCTs with a total of 5643 participants. In general, the risk of bias of included studies was low. Our findings showed that mHealth app--based interventions significantly increased total PA (TPA; standardized mean difference [SMD] 0.29, 95\% CI 0.13-0.45; P<.001), reduced SB (SMD --0.97, 95\% CI --1.67 to --0.28; P=.006) and BMI (weighted mean difference --0.31 kg/m2, 95\% CI --0.60 to --0.01 kg/m2; P=.12), and improved muscle strength (SMD 1.97, 95\% CI 0.09-3.86; P=.04) and agility (SMD --0.35, 95\% CI --0.61 to --0.10; P=.006). However, mHealth app--based interventions insignificantly affected moderate to vigorous PA (MVPA; SMD 0.11, 95\% CI --0.04 to 0.25; P<.001), waist circumference (weighted mean difference 0.38 cm, 95\% CI --1.28 to 2.04 cm; P=.65), muscular power (SMD 0.01, 95\% CI --0.08 to 0.10; P=.81), cardiorespiratory fitness (SMD --0.20, 95\% CI --0.45 to 0.05; P=.11), muscular endurance (SMD 0.47, 95\% CI --0.08 to 1.02; P=.10), and flexibility (SMD 0.09, 95\% CI --0.23 to 0.41; P=.58). Subgroup analyses and meta-regression showed that intervention duration was associated with TPA and MVPA, and age and types of intervention was associated with BMI. Conclusions: Our meta-analysis suggests that mHealth app--based interventions may yield small-to-large beneficial effects on TPA, SB, BMI, agility, and muscle strength in children and adolescents. Furthermore, age and intervention duration may correlate with the higher effectiveness of mHealth app--based interventions. However, due to the limited number and quality of included studies, the aforementioned conclusions require validation through additional high-quality research. Trial Registration: PROSPERO CRD42023426532; https://tinyurl.com/25jm4kmf ", doi="10.2196/51478", url="https://mhealth.jmir.org/2024/1/e51478", url="http://www.ncbi.nlm.nih.gov/pubmed/38687568" } @Article{info:doi/10.2196/49509, author="Luo, Qianqian and Zhang, Yue and Wang, Wei and Cui, Tianyu and Li, Tianying", title="mHealth-Based Gamification Interventions Among Men Who Have Sex With Men in the HIV Prevention and Care Continuum: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2024", month="Apr", day="15", volume="12", pages="e49509", keywords="mHealth", keywords="gamification", keywords="HIV", keywords="men who have sex with men", keywords="meta-analysis", keywords="PRISMA", keywords="mobile health", keywords="Preferred Reporting Items for Systematic Reviews and Meta-Analyses", abstract="Background: In the past few years, a burgeoning interest has emerged in applying gamification to promote desired health behaviors. However, little is known about the effectiveness of such applications in the HIV prevention and care continuum among men who have sex with men (MSM). Objective: This study aims to summarize and evaluate research on the effectiveness of gamification on the HIV prevention and care continuum, including HIV-testing promotion; condomless anal sex (CAS) reduction; and uptake of and adherence to pre-exposure prophylaxis (PrEP), postexposure prophylaxis (PEP), and antiretroviral therapy (ART). Methods: We comprehensively searched PubMed, Embase, the Cochrane Library, Web of Science, Scopus, and the Journal of Medical Internet Research and its sister journals for studies published in English and Chinese from inception to January 2024. Eligible studies were included when they used gamified interventions with an active or inactive control group and assessed at least one of the following outcomes: HIV testing; CAS; and uptake of and adherence to PrEP, PEP, and ART. During the meta-analysis, a random-effects model was applied. Two reviewers independently assessed the quality and risk of bias of each included study. Results: The systematic review identified 26 studies, including 10 randomized controlled trials (RCTs). The results indicated that gamified digital interventions had been applied to various HIV outcomes, such as HIV testing, CAS, PrEP uptake and adherence, PEP uptake, and ART adherence. Most of the studies were conducted in the United States (n=19, 73\%). The most frequently used game component was gaining points, followed by challenges. The meta-analysis showed gamification interventions could reduce the number of CAS acts at the 3-month follow-up (n=2 RCTs; incidence rate ratio 0.62, 95\% CI 0.44-0.88). The meta-analysis also suggested an effective but nonstatistically significant effect of PrEP adherence at the 3-month follow-up (n=3 RCTs; risk ratio 1.16, 95\% CI 0.96-1.38) and 6-month follow-up (n=4 RCTs; risk ratio 1.28, 95\% CI 0.89-1.84). Only 1 pilot RCT was designed to evaluate the effectiveness of a gamified app in promoting HIV testing and PrEP uptake. No RCT was conducted to evaluate the effect of the gamified digital intervention on PEP uptake and adherence, and ART initiation among MSM. Conclusions: Our findings suggest the short-term effect of gamified digital interventions on lowering the number of CAS acts in MSM. Further well-powered studies are still needed to evaluate the effect of the gamified digital intervention on HIV testing, PrEP uptake, PEP initiation and adherence, and ART initiation in MSM. Trial Registration: PROSPERO CRD42023392193; https://www.crd.york.ac.uk/PROSPERO/display\_record.php?RecordID=392193 ", doi="10.2196/49509", url="https://mhealth.jmir.org/2024/1/e49509" } @Article{info:doi/10.2196/49751, author="Lyzwinski, Nathalie Lynnette and Elgendi, Mohamed and Menon, Carlo", title="Users' Acceptability and Perceived Efficacy of mHealth for Opioid Use Disorder: Scoping Review", journal="JMIR Mhealth Uhealth", year="2024", month="Apr", day="11", volume="12", pages="e49751", keywords="acceptability", keywords="addict", keywords="addiction", keywords="addictions", keywords="app", keywords="app-based", keywords="application", keywords="applications", keywords="apps", keywords="barrier", keywords="barriers", keywords="challenge", keywords="challenges", keywords="messaging", keywords="mHealth", keywords="mobile health", keywords="monitoring", keywords="opioid", keywords="opioids", keywords="overdose", keywords="overdosing", keywords="pharmacology", keywords="review methodology", keywords="review methods", keywords="scoping", keywords="sensor", keywords="sensors", keywords="SMS", keywords="substance abuse", keywords="substance use", keywords="text message", keywords="wearable technology", keywords="wearable", keywords="wearables", abstract="Background: The opioid crisis continues to pose significant challenges to global public health, necessitating the development of novel interventions to support individuals in managing their substance use and preventing overdose-related deaths. Mobile health (mHealth), as a promising platform for addressing opioid use disorder, requires a comprehensive understanding of user perspectives to minimize barriers to care and optimize the benefits of mHealth interventions. Objective: This study aims to synthesize qualitative insights into opioid users' acceptability and perceived efficacy of mHealth and wearable technologies for opioid use disorder. Methods: A scoping review of PubMed (MEDLINE) and Google Scholar databases was conducted to identify research on opioid user perspectives concerning mHealth-assisted interventions, including wearable sensors, SMS text messaging, and app-based technology. Results: Overall, users demonstrate a high willingness to engage with mHealth interventions to prevent overdose-related deaths and manage opioid use. Users perceive mHealth as an opportunity to access care and desire the involvement of trusted health care professionals in these technologies. User comfort with wearing opioid sensors emerged as a significant factor. Personally tailored content, social support, and encouragement are preferred by users. Privacy concerns and limited access to technology pose barriers to care. Conclusions: To maximize benefits and minimize risks for users, it is crucial to implement robust privacy measures, provide comprehensive user training, integrate behavior change techniques, offer professional and peer support, deliver tailored messages, incorporate behavior change theories, assess readiness for change, design stigma-reducing apps, use visual elements, and conduct user-focused research for effective opioid management in mHealth interventions. mHealth demonstrates considerable potential as a tool for addressing opioid use disorder and preventing overdose-related deaths, given the high acceptability and perceived benefits reported by users. ", doi="10.2196/49751", url="https://mhealth.jmir.org/2024/1/e49751", url="http://www.ncbi.nlm.nih.gov/pubmed/38602751" } @Article{info:doi/10.2196/54244, author="Yang, Xiaoyu and Li, Xueting and Jiang, Shanshan and Yu, Xinying", title="Effects of Telemedicine on Informal Caregivers of Patients in Palliative Care: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2024", month="Apr", day="8", volume="12", pages="e54244", keywords="telemedicine", keywords="palliative care", keywords="informal caregivers", keywords="caregiver burden", keywords="anxiety", keywords="depression", keywords="quality of life", keywords="systematic review", keywords="meta-analysis", keywords="PRISMA", keywords="Preferred Reporting Items for Systematic Reviews and Meta-Analyses", abstract="Background: Telemedicine technology is a rapidly developing field that shows immense potential for improving medical services. In palliative care, informal caregivers assume the primary responsibility in patient care and often face challenges such as increased physical and mental stress and declining health. In such cases, telemedicine interventions can provide support and improve their health outcomes. However, research findings regarding the use of telemedicine among informal caregivers are controversial, and the efficacy of telemedicine remains unclear. Objective: This study aimed to evaluate the impacts of telemedicine on the burden, anxiety, depression, and quality of life of informal caregivers of patients in palliative care. Methods: A systematic literature search was conducted using the PubMed, Embase, Web of Science, CENTRAL, PsycINFO, CINAHL Plus with Full Text, CBM, CNKI, WanFang, and VIP databases to identify relevant randomized controlled trials published from inception to March 2023. Two authors independently screened the studies and extracted the relevant information. The methodological quality of the included studies was assessed using the Cochrane risk-of-bias tool. Intervention effects were estimated and sensitivity analysis was conducted using Review Manager 5.4, whereas 95\% prediction intervals (PIs) were calculated using R (version 4.3.2) and RStudio. Results: A total of 9 randomized controlled trials were included in this study. The meta-analysis indicated that telemedicine has reduced the caregiving burden (standardized mean differences [SMD] ?0.49, 95\% CI ?0.72 to ?0.27; P<.001; 95\% PI ?0.86 to ?0.13) and anxiety (SMD ?0.23, 95\% CI ?0.40 to ?0.06; P=.009; 95\% PI ?0.98 to 0.39) of informal caregivers; however, it did not affect depression (SMD ?0.21, 95\% CI ?0.47 to 0.05; P=.11; 95\% PI ?0.94 to 0.51) or quality of life (SMD 0.35, 95\% CI ?0.20 to 0.89; P=.21; 95\% PI ?2.15 to 2.85). Conclusions: Although telemedicine can alleviate the caregiving burden and anxiety of informal caregivers, it does not significantly reduce depression or improve their quality of life. Further high-quality, large-sample studies are needed to validate the effects of telemedicine. Furthermore, personalized intervention programs based on theoretical foundations are required to support caregivers. Trial Registration: PROSPERO CRD42023415688; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=415688 ", doi="10.2196/54244", url="https://mhealth.jmir.org/2024/1/e54244" } @Article{info:doi/10.2196/52179, author="Moorthy, Preetha and Weinert, Lina and Sch{\"u}ttler, Christina and Svensson, Laura and Sedlmayr, Brita and M{\"u}ller, Julia and Nagel, Till", title="Attributes, Methods, and Frameworks Used to Evaluate Wearables and Their Companion mHealth Apps: Scoping Review", journal="JMIR Mhealth Uhealth", year="2024", month="Apr", day="5", volume="12", pages="e52179", keywords="wearables", keywords="mobile health", keywords="mHealth", keywords="mobile phone", keywords="usability methods", keywords="usability attributes", keywords="evaluation frameworks", keywords="health care", abstract="Background: Wearable devices, mobile technologies, and their combination have been accepted into clinical use to better assess the physical fitness and quality of life of patients and as preventive measures. Usability is pivotal for overcoming constraints and gaining users' acceptance of technology such as wearables and their companion mobile health (mHealth) apps. However, owing to limitations in design and evaluation, interactive wearables and mHealth apps have often been restricted from their full potential. Objective: This study aims to identify studies that have incorporated wearable devices and determine their frequency of use in conjunction with mHealth apps or their combination. Specifically, this study aims to understand the attributes and evaluation techniques used to evaluate usability in the health care domain for these technologies and their combinations. Methods: We conducted an extensive search across 4 electronic databases, spanning the last 30 years up to December 2021. Studies including the keywords ``wearable devices,'' ``mobile apps,'' ``mHealth apps,'' ``physiological data,'' ``usability,'' ``user experience,'' and ``user evaluation'' were considered for inclusion. A team of 5 reviewers screened the collected publications and charted the features based on the research questions. Subsequently, we categorized these characteristics following existing usability and wearable taxonomies. We applied a methodological framework for scoping reviews and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. Results: A total of 382 reports were identified from the search strategy, and 68 articles were included. Most of the studies (57/68, 84\%) involved the simultaneous use of wearables and connected mobile apps. Wrist-worn commercial consumer devices such as wristbands were the most prevalent, accounting for 66\% (45/68) of the wearables identified in our review. Approximately half of the data from the medical domain (32/68, 47\%) focused on studies involving participants with chronic illnesses or disorders. Overall, 29 usability attributes were identified, and 5 attributes were frequently used for evaluation: satisfaction (34/68, 50\%), ease of use (27/68, 40\%), user experience (16/68, 24\%), perceived usefulness (18/68, 26\%), and effectiveness (15/68, 22\%). Only 10\% (7/68) of the studies used a user- or human-centered design paradigm for usability evaluation. Conclusions: Our scoping review identified the types and categories of wearable devices and mHealth apps, their frequency of use in studies, and their implementation in the medical context. In addition, we examined the usability evaluation of these technologies: methods, attributes, and frameworks. Within the array of available wearables and mHealth apps, health care providers encounter the challenge of selecting devices and companion apps that are effective, user-friendly, and compatible with user interactions. The current gap in usability and user experience in health care research limits our understanding of the strengths and limitations of wearable technologies and their companion apps. Additional research is necessary to overcome these limitations. ", doi="10.2196/52179", url="https://mhealth.jmir.org/2024/1/e52179", url="http://www.ncbi.nlm.nih.gov/pubmed/38578671" } @Article{info:doi/10.2196/52192, author="Schyvens, An-Marie and Van Oost, Catharina Nina and Aerts, Jean-Marie and Masci, Federica and Peters, Brent and Neven, An and Dirix, H{\'e}l{\`e}ne and Wets, Geert and Ross, Veerle and Verbraecken, Johan", title="Accuracy of Fitbit Charge 4, Garmin Vivosmart 4, and WHOOP Versus Polysomnography: Systematic Review", journal="JMIR Mhealth Uhealth", year="2024", month="Mar", day="27", volume="12", pages="e52192", keywords="sleep", keywords="wearable device", keywords="validation", keywords="polysomnography", keywords="assessing sleep", keywords="PRISMA", keywords="Preferred Reporting Items for Systematic Reviews and Meta-Analyses", abstract="Background: Despite being the gold-standard method for objectively assessing sleep, polysomnography (PSG) faces several limitations as it is expensive, time-consuming, and labor-intensive; requires various equipment and technical expertise; and is impractical for long-term or in-home use. Consumer wrist-worn wearables are able to monitor sleep parameters and thus could be used as an alternative for PSG. Consequently, wearables gained immense popularity over the past few years, but their accuracy has been a major concern. Objective: A systematic review of the literature was conducted to appraise the performance of 3 recent-generation wearable devices (Fitbit Charge 4, Garmin Vivosmart 4, and WHOOP) in determining sleep parameters and sleep stages. Methods: Per the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement, a comprehensive search was conducted using the PubMed, Web of Science, Google Scholar, Scopus, and Embase databases. Eligible publications were those that (1) involved the validity of sleep data of any marketed model of the candidate wearables and (2) used PSG or an ambulatory electroencephalogram monitor as a reference sleep monitoring device. Exclusion criteria were as follows: (1) incorporated a sleep diary or survey method as a reference, (2) review paper, (3) children as participants, and (4) duplicate publication of the same data and findings. Results: The search yielded 504 candidate articles. After eliminating duplicates and applying the eligibility criteria, 8 articles were included. WHOOP showed the least disagreement relative to PSG and Sleep Profiler for total sleep time (?1.4 min), light sleep (?9.6 min), and deep sleep (?9.3 min) but showed the largest disagreement for rapid eye movement (REM) sleep (21.0 min). Fitbit Charge 4 and Garmin Vivosmart 4 both showed moderate accuracy in assessing sleep stages and total sleep time compared to PSG. Fitbit Charge 4 showed the least disagreement for REM sleep (4.0 min) relative to PSG. Additionally, Fitbit Charge 4 showed higher sensitivities to deep sleep (75\%) and REM sleep (86.5\%) compared to Garmin Vivosmart 4 and WHOOP. Conclusions: The findings of this systematic literature review indicate that the devices with higher relative agreement and sensitivities to multistate sleep (ie, Fitbit Charge 4 and WHOOP) seem appropriate for deriving suitable estimates of sleep parameters. However, analyses regarding the multistate categorization of sleep indicate that all devices can benefit from further improvement in the assessment of specific sleep stages. Although providers are continuously developing new versions and variants of wearables, the scientific research on these wearables remains considerably limited. This scarcity in literature not only reduces our ability to draw definitive conclusions but also highlights the need for more targeted research in this domain. Additionally, future research endeavors should strive for standardized protocols including larger sample sizes to enhance the comparability and power of the results across studies. ", doi="10.2196/52192", url="https://mhealth.jmir.org/2024/1/e52192" } @Article{info:doi/10.2196/45860, author="Bernstein, E. Emily and Wolfe, C. Emma and Huguenel, M. Brynn and Wilhelm, Sabine", title="Lessons and Untapped Potential of Smartphone-Based Physical Activity Interventions for Mental Health: Narrative Review", journal="JMIR Mhealth Uhealth", year="2024", month="Mar", day="15", volume="12", pages="e45860", keywords="smartphone", keywords="digital health", keywords="exercise", keywords="physical activity", keywords="mental health", keywords="depression", keywords="anxiety", keywords="mobile phone", abstract="Background: Physical activity has well-known and broad health benefits, including antidepressive and anxiolytic effects. However, only approximately half of Americans meet even the minimum exercise recommendations. Individuals with anxiety, depression, or related conditions are even less likely to do so. With the advent of mobile sensors and phones, experts have quickly noted the utility of technology for the enhanced measurement of and intervention for physical activity. In addition to being more accessible than in-person approaches, technology-driven interventions may uniquely engage key mechanisms of behavior change such as self-awareness. Objective: This study aims to provide a narrative overview and specific recommendations for future research on smartphone-based physical activity interventions for psychological disorders or concerns. Methods: In this paper, we summarized early efforts to adapt and test smartphone-based or smartphone-supported physical activity interventions for mental health. The included articles described or reported smartphone-delivered or smartphone-supported interventions intended to increase physical activity or reduce sedentary behavior and included an emotional disorder, concern, or symptom as an outcome measure. We attempted to extract details regarding the intervention designs, trial designs, study populations, outcome measures, and inclusion of adaptations specifically for mental health. In taking a narrative lens, we drew attention to the type of work that has been done and used these exemplars to discuss key directions to build on. Results: To date, most studies have examined mental health outcomes as secondary or exploratory variables largely in the context of managing medical concerns (eg, cancer and diabetes). Few trials have recruited psychiatric populations or explicitly aimed to target psychiatric concerns. Consequently, although there are encouraging signals that smartphone-based physical activity interventions could be feasible, acceptable, and efficacious for individuals with mental illnesses, this remains an underexplored area. Conclusions: Promising avenues for tailoring validated smartphone-based interventions include adding psychoeducation (eg, the relationship between depression, physical activity, and inactivity), offering psychosocial treatment in parallel (eg, cognitive restructuring), and adding personalized coaching. To conclude, we offer specific recommendations for future research, treatment development, and implementation in this area, which remains open and promising for flexible, highly scalable support. ", doi="10.2196/45860", url="https://mhealth.jmir.org/2024/1/e45860", url="http://www.ncbi.nlm.nih.gov/pubmed/38488834" } @Article{info:doi/10.2196/44406, author="Gheisari, Mehdi and Ghaderzadeh, Mustafa and Li, Huxiong and Taami, Tania and Fern{\'a}ndez-Campusano, Christian and Sadeghsalehi, Hamidreza and Afzaal Abbasi, Aaqif", title="Mobile Apps for COVID-19 Detection and Diagnosis for Future Pandemic Control: Multidimensional Systematic Review", journal="JMIR Mhealth Uhealth", year="2024", month="Feb", day="22", volume="12", pages="e44406", keywords="COVID-19", keywords="detection", keywords="diagnosis", keywords="internet of things", keywords="cloud computing", keywords="mobile applications", keywords="mobile app", keywords="mobile apps", keywords="artificial intelligence: AI", keywords="mobile phone", keywords="smartphone", abstract="Background: In the modern world, mobile apps are essential for human advancement, and pandemic control is no exception. The use of mobile apps and technology for the detection and diagnosis of COVID-19 has been the subject of numerous investigations, although no thorough analysis of COVID-19 pandemic prevention has been conducted using mobile apps, creating a gap. Objective: With the intention of helping software companies and clinical researchers, this study provides comprehensive information regarding the different fields in which mobile apps were used to diagnose COVID-19 during the pandemic. Methods: In this systematic review, 535 studies were found after searching 5 major research databases (ScienceDirect, Scopus, PubMed, Web of Science, and IEEE). Of these, only 42 (7.9\%) studies concerned with diagnosing and detecting COVID-19 were chosen after applying inclusion and exclusion criteria using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol. Results: Mobile apps were categorized into 6 areas based on the content of these 42 studies: contact tracing, data gathering, data visualization, artificial intelligence (AI)--based diagnosis, rule- and guideline-based diagnosis, and data transformation. Patients with COVID-19 were identified via mobile apps using a variety of clinical, geographic, demographic, radiological, serological, and laboratory data. Most studies concentrated on using AI methods to identify people who might have COVID-19. Additionally, symptoms, cough sounds, and radiological images were used more frequently compared to other data types. Deep learning techniques, such as convolutional neural networks, performed comparatively better in the processing of health care data than other types of AI techniques, which improved the diagnosis of COVID-19. Conclusions: Mobile apps could soon play a significant role as a powerful tool for data collection, epidemic health data analysis, and the early identification of suspected cases. These technologies can work with the internet of things, cloud storage, 5th-generation technology, and cloud computing. Processing pipelines can be moved to mobile device processing cores using new deep learning methods, such as lightweight neural networks. In the event of future pandemics, mobile apps will play a critical role in rapid diagnosis using various image data and clinical symptoms. Consequently, the rapid diagnosis of these diseases can improve the management of their effects and obtain excellent results in treating patients. ", doi="10.2196/44406", url="https://mhealth.jmir.org/2024/1/e44406", url="http://www.ncbi.nlm.nih.gov/pubmed/38231538" } @Article{info:doi/10.2196/45139, author="Lyzwinski, Lynnette and Elgendi, Mohamed and Menon, Carlo", title="Innovative Approaches to Menstruation and Fertility Tracking Using Wearable Reproductive Health Technology: Systematic Review", journal="J Med Internet Res", year="2024", month="Feb", day="15", volume="26", pages="e45139", keywords="fertility cycle", keywords="fertility monitoring", keywords="ovulation", keywords="menstruation", keywords="wearable devices", keywords="mHealth", keywords="reproductive health", keywords="wearable", keywords="fertility", keywords="menstrual", keywords="women's health", keywords="ovulate", keywords="sexual health", keywords="scoping", keywords="review method", abstract="Background: Emerging digital health technology has moved into the reproductive health market for female individuals. In the past, mobile health apps have been used to monitor the menstrual cycle using manual entry. New technological trends involve the use of wearable devices to track fertility by assessing physiological changes such as temperature, heart rate, and respiratory rate. Objective: The primary aims of this study are to review the types of wearables that have been developed and evaluated for menstrual cycle tracking and to examine whether they may detect changes in the menstrual cycle in female individuals. Another aim is to review whether these devices are effective for tracking various stages in the menstrual cycle including ovulation and menstruation. Finally, the secondary aim is to assess whether the studies have validated their findings by reporting accuracy and sensitivity. Methods: A review of PubMed or MEDLINE was undertaken to evaluate wearable devices for their effectiveness in predicting fertility and differentiating between the different stages of the menstrual cycle. Results: Fertility cycle--tracking wearables include devices that can be worn on the wrists, on the fingers, intravaginally, and inside the ear. Wearable devices hold promise for predicting different stages of the menstrual cycle including the fertile window and may be used by female individuals as part of their reproductive health. Most devices had high accuracy for detecting fertility and were able to differentiate between the luteal phase (early and late), fertile window, and menstruation by assessing changes in heart rate, heart rate variability, temperature, and respiratory rate. Conclusions: More research is needed to evaluate consumer perspectives on reproductive technology for monitoring fertility, and ethical issues around the privacy of digital data need to be addressed. Additionally, there is also a need for more studies to validate and confirm this research, given its scarcity, especially in relation to changes in respiratory rate as a proxy for reproductive cycle staging. ", doi="10.2196/45139", url="https://www.jmir.org/2024/1/e45139", url="http://www.ncbi.nlm.nih.gov/pubmed/38358798" } @Article{info:doi/10.2196/48526, author="Percy Campbell, Jessica and Buchan, Jacob and Chu, H. Charlene and Bianchi, Andria and Hoey, Jesse and Khan, S. Shehroz", title="User Perception of Smart Home Surveillance Among Adults Aged 50 Years and Older: Scoping Review", journal="JMIR Mhealth Uhealth", year="2024", month="Feb", day="9", volume="12", pages="e48526", keywords="smart homes", keywords="privacy", keywords="surveillance", keywords="ambient assisted living", keywords="smart speakers", keywords="Internet of Things", keywords="sensors", keywords="sensor", keywords="smart home", keywords="perception", keywords="perceptions", keywords="elderly", keywords="older adult", keywords="older adults", keywords="review methods", keywords="review methodology", keywords="home monitoring", keywords="security", keywords="safety", keywords="ageing", keywords="ageing-in-place", keywords="integrative review", keywords="integrative reviews", abstract="Background: Smart home technology (SHT) can be useful for aging in place or health-related purposes. However, surveillance studies have highlighted ethical issues with SHTs, including user privacy, security, and autonomy. Objective: As digital technology is most often designed for younger adults, this review summarizes perceptions of SHTs among users aged 50 years and older to explore their understanding of privacy, the purpose of data collection, risks and benefits, and safety. Methods: Through an integrative review, we explored community-dwelling adults' (aged 50 years and older) perceptions of SHTs based on research questions under 4 nonmutually exclusive themes: privacy, the purpose of data collection, risk and benefits, and safety. We searched 1860 titles and abstracts from Ovid MEDLINE, Ovid Embase, Cochrane Database of Systematic Reviews, and Cochrane Central Register of Controlled Trials, Scopus, Web of Science Core Collection, and IEEE Xplore or IET Electronic Library, resulting in 15 included studies. Results: The 15 studies explored user perception of smart speakers, motion sensors, or home monitoring systems. A total of 13 (87\%) studies discussed user privacy concerns regarding data collection and access. A total of 4 (27\%) studies explored user knowledge of data collection purposes, 7 (47\%) studies featured risk-related concerns such as data breaches and third-party misuse alongside benefits such as convenience, and 9 (60\%) studies reported user enthusiasm about the potential for home safety. Conclusions: Due to the growing size of aging populations and advances in technological capabilities, regulators and designers should focus on user concerns by supporting higher levels of agency regarding data collection, use, and disclosure and by bolstering organizational accountability. This way, relevant privacy regulation and SHT design can better support user safety while diminishing potential risks to privacy, security, autonomy, or discriminatory outcomes. ", doi="10.2196/48526", url="https://mhealth.jmir.org/2024/1/e48526", url="http://www.ncbi.nlm.nih.gov/pubmed/38335026" } @Article{info:doi/10.2196/47843, author="Pritwani, Sabhya and Shrivastava, Purnima and Pandey, Shruti and Kumar, Ajit and Malhotra, Rajesh and Maddison, Ralph and Devasenapathy, Niveditha", title="Mobile and Computer-Based Applications for Rehabilitation Monitoring and Self-Management After Knee Arthroplasty: Scoping Review", journal="JMIR Mhealth Uhealth", year="2024", month="Jan", day="26", volume="12", pages="e47843", keywords="knee arthroplasty", keywords="telerehabilitation", keywords="mHealth", keywords="rehabilitation", keywords="monitoring", keywords="self-management", keywords="knee", keywords="arthroplasty", keywords="social support", keywords="mHealth intervention", keywords="development", keywords="scoping review", keywords="knee replacement", abstract="Background: Successful post-knee replacement rehabilitation requires adequate access to health information, social support, and periodic monitoring by a health professional. Mobile health (mHealth) and computer-based technologies are used for rehabilitation and remote monitoring. The extent of technology use and its function in post-knee replacement rehabilitation care in low and middle-income settings are unknown. Objective: To inform future mHealth intervention development, we conducted a scoping review to map the features and functionality of existing technologies and determine users' perspectives on telerehabilitation and technology for self-management. Methods: We followed the Joanna Briggs Institute methodology for scoping reviews. We searched the Embase, Medline, PsycINFO via OVID, and Cochrane Central Register of Controlled Trials databases for manuscripts published from 2001 onward. We included original research articles reporting the use of mobile or computer-based technologies by patients, health care providers, researchers, or family members. Studies were divided into the following 3 categories based on the purpose: validation studies, clinical evaluation, and end user feedback. We extracted general information on study design, technology features, proposed function, and perspectives of health care providers and patients. The protocol for this review is accessible in the Open Science Framework. Results: Of the 5960 articles, 158 that reported from high-income settings contributed to the qualitative summary (64 studies on mHealth or telerehabilitation programs, 28 validation studies, 38 studies describing users' perceptions). The highest numbers of studies were from Europe or the United Kingdom and North America regarding the use of a mobile app with or without wearables and reported mainly in the last decade. No studies were from low and middle-income settings. The primary functions of technology for remote rehabilitation were education to aid recovery and enable regular, appropriate exercises; monitoring progress of pain (n=19), activity (n=20), and exercise adherence (n=30); 1 or 2-way communication with health care professionals to facilitate the continuum of care (n=51); and goal setting (n=23). Assessment of range of motion (n=16) and gait analysis (n=10) were the commonly validated technologies developed to incorporate into a future rehabilitation program. Few studies (n=14) reported end user involvement during the development stage. We summarized the reasons for satisfaction and dissatisfaction among users across various technologies. Conclusions: Several existing mobile and computer-based technologies facilitate post-knee replacement rehabilitation care for patients and health care providers. However, they are limited to high-income settings and may not be extrapolated to low-income settings. A systematic needs assessment of patients undergoing knee replacement and health care providers involved in rehabilitation, involving end users at all stages of development and evaluation, with clear reporting of the development and clinical evaluation can make post-knee replacement rehabilitation care in resource-poor settings accessible and cost-effective. ", doi="10.2196/47843", url="https://mhealth.jmir.org/2024/1/e47843", url="http://www.ncbi.nlm.nih.gov/pubmed/38277195" } @Article{info:doi/10.2196/50616, author="Nagel, Johanna and Wegener, Florian and Grim, Casper and Hoppe, Wilhelm Matthias", title="Effects of Digital Physical Health Exercises on Musculoskeletal Diseases: Systematic Review With Best-Evidence Synthesis", journal="JMIR Mhealth Uhealth", year="2024", month="Jan", day="23", volume="12", pages="e50616", keywords="mobile health", keywords="mHealth", keywords="electronic health", keywords="eHealth", keywords="digital health applications", keywords="DiGA", keywords="musculoskeletal", keywords="MSK", keywords="home-based", keywords="PROM", keywords="disorder", keywords="mobile phone", abstract="Background: Musculoskeletal diseases affect 1.71 billion people worldwide, impose a high biopsychosocial burden on patients, and are associated with high economic costs. The use of digital health interventions is a promising cost-saving approach for the treatment of musculoskeletal diseases. As physical exercise is the best clinical practice in the treatment of musculoskeletal diseases, digital health interventions that provide physical exercises could have a highly positive impact on musculoskeletal diseases, but evidence is lacking. Objective: This systematic review aims to evaluate the impact of digital physical health exercises on patients with musculoskeletal diseases concerning the localization of the musculoskeletal disease, patient-reported outcomes, and medical treatment types. Methods: We performed systematic literature research using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The search was conducted using the PubMed, BISp, Cochrane Library, and Web of Science databases. The Scottish Intercollegiate Guidelines Network checklist was used to assess the quality of the included original studies. To determine the evidence and direction of the impact of digital physical health exercises, a best-evidence synthesis was conducted, whereby only studies with at least acceptable methodological quality were included for validity purposes. Results: A total of 8988 studies were screened, of which 30 (0.33\%) randomized controlled trials met the inclusion criteria. Of these, 16 studies (53\%) were of acceptable or high quality; they included 1840 patients (1008/1643, 61.35\% female; 3 studies including 197 patients did not report gender distribution) with various musculoskeletal diseases. A total of 3 different intervention types (app-based interventions, internet-based exercises, and telerehabilitation) were used to deliver digital physical health exercises. Strong evidence was found for the positive impact of digital physical health exercises on musculoskeletal diseases located in the back. Moderate evidence was found for diseases located in the shoulder and hip, whereas evidence for the entire body was limited. Conflicting evidence was found for diseases located in the knee and hand. For patient-reported outcomes, strong evidence was found for impairment and quality of life. Conflicting evidence was found for pain and function. Regarding the medical treatment type, conflicting evidence was found for operative and conservative therapies. Conclusions: Strong to moderate evidence was found for a positive impact on musculoskeletal diseases located in the back, shoulder, and hip and on the patient-reported outcomes of impairment and quality of life. Thus, digital physical health exercises could have a positive effect on a variety of symptoms of musculoskeletal diseases. ", doi="10.2196/50616", url="https://mhealth.jmir.org/2024/1/e50616", url="http://www.ncbi.nlm.nih.gov/pubmed/38261356" } @Article{info:doi/10.2196/50787, author="Wu, Man and Li, Chaoyang and Hu, Ting and Zhao, Xueyang and Qiao, Guiyuan and Gao, Xiaolian and Zhu, Xinhong and Yang, Fen", title="Effectiveness of Telecare Interventions on Depression Symptoms Among Older Adults: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2024", month="Jan", day="17", volume="12", pages="e50787", keywords="telecare", keywords="depression", keywords="anxiety", keywords="quality of life", keywords="older adults", keywords="meta-analysis", abstract="Background: Depression is the most common psychiatric disorder among older adults. Despite the effectiveness of pharmacological and psychological therapies, many patients with late-life depression (LLD) are unable to access timely treatment. Telecare has been shown to be effective in addressing patients' psychosocial issues, while its effectiveness in serving patients with LLD remains unclear. Objective: This study aimed to evaluate the effectiveness of telecare in reducing depression and anxiety symptoms and improving quality of life (QoL) in patients with LLD. Methods: Databases including the Cochrane Library, Web of Science, PubMed, Embase, and EBSCO were searched for randomized controlled trials (RCTs) evaluating the effectiveness of telecare for LLD from database establishment to December 28, 2022. Results: A total of 12 RCTs involving 1663 participants were identified in this study. The meta-analysis showed that (1) telecare significantly reduced depressive symptoms in patients with LLD compared to those in usual care (UC; standardized mean difference [SMD]=--0.46, 95\% CI --0.53 to --0.38; P<.001), with the best improvement observed within 3 months of intervention (SMD=--0.72, 95\% CI --1.16 to --0.28; P<.001); (2) other scales appeared more effective than the Patient Health Questionnaire-9 for LLD in telecare interventions (SMD=--0.65, 95\% CI --0.96 to --0.35; P<.001); (3) telecare was more effective than telephone-based interventions for remote monitoring of LLD (SMD=--1.13, 95\% CI --1.51 to --0.76; P<.001); (4) the reduction of depressive symptoms was more pronounced in patients with LLD with chronic conditions (SMD=--0.67, 95\% CI --0.89 to --0.44; P<.001); (5) telecare was more effective for LLD in Europe and the Americas than in other regions (SMD=--0.73, 95\% CI --0.99 to --0.47; P<.001); (6) telecare significantly reduced anxiety symptoms in patients with LLD (SMD=--0.53, 95\% CI --0.73 to --0.33; P=.02); and (7) there was no significant improvement in the psychological components of QoL in patients with LLD compared to those receiving UC (SMD=0.30, 95\% CI 0.18-0.43; P=.80). Conclusions: Telecare is a promising modality of care for treatment, which can alleviate depression and anxiety symptoms in patients with LLD. Continued in-depth research into the effectiveness of telecare in treating depression could better identify where older patients would benefit from this intervention. ", doi="10.2196/50787", url="https://mhealth.jmir.org/2024/1/e50787", url="http://www.ncbi.nlm.nih.gov/pubmed/38231546" } @Article{info:doi/10.2196/49373, author="He, Yirong and Huang, Chuanya and He, Qiuyang and Liao, Shujuan and Luo, Biru", title="Effects of mHealth-Based Lifestyle Interventions on Gestational Diabetes Mellitus in Pregnant Women With Overweight and Obesity: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2024", month="Jan", day="17", volume="12", pages="e49373", keywords="mobile health", keywords="mHealth", keywords="lifestyle intervention", keywords="gestational diabetes mellitus", keywords="meta-analysis", keywords="mobile phone", abstract="Background: The increasing incidence of gestational diabetes mellitus (GDM) is a global health problem that is more likely to occur in pregnant women with overweight or obesity. Adhering to a healthy lifestyle is associated with a reduced risk of GDM. With the development of IT, mobile health (mHealth) interventions have become widely available in health care. However, there are no definitive conclusions on the effectiveness of mHealth-based lifestyle interventions in preventing GDM. Objective: This study aims to evaluate the impact of mHealth-based lifestyle interventions on GDM and other pregnancy outcomes in pregnant women with overweight or obesity. Methods: A systematic literature search was conducted in 5 English databases (MEDLINE, Embase, Web of Science, CENTRAL, and CINAHL) and 4 Chinese databases (CBM, CNKI, Vip, and Wanfang) to identify randomized controlled trials (RCTs) on the effectiveness of mHealth-based interventions for GDM from inception to January 10, 2023. In total, 2 authors independently screened the studies and extracted the data. The quality of the included studies was examined using the Cochrane risk-of-bias tool. Data synthesis was conducted using Review Manager (version 5.4; The Cochrane Collaboration). Results: A total of 16 RCTs with 7351 participants were included in this study. The included studies were published between 2014 and 2021 and were conducted in China, the United States, Australia, New Zealand, the United Kingdom, Ireland, and Norway. The sample sizes of the studies ranged from 75 to 2202, and the duration of the mHealth-based lifestyle interventions ranged from 4 to 28 weeks. Compared with usual care, mHealth-based lifestyle interventions significantly reduced the incidence of GDM (odds ratio [OR] 0.74, 95\% CI 0.56-0.96; P=.03; I2=65\%), preterm birth (OR 0.65, 95\% CI 0.48-0.87; P=.004; I2=25\%), macrosomia (OR 0.59, 95\% CI 0.40-0.87; P=.008; I2=59\%), and gestational weight gain (mean difference=?1.12 kg, 95\% CI ?1.44 to ?0.80; P<.001; I2=43\%). The subgroup analysis showed that interventions delivered via apps (OR 0.55, 95\% CI 0.37-0.83; P=.004; I2=44\%), provided by obstetricians (OR 0.69, 95\% CI 0.51-0.93; P=.02; I2=60\%), and targeted at Asian populations (OR 0.44, 95\% CI 0.34-0.58; P<.001; I2=0\%) and that used the International Association of Diabetes and Pregnancy Study Groups diagnostic criteria (OR 0.58, 95\% CI 0.39-0.86; P=.007; I2=69\%) showed a statistically significant reduction in the risk of GDM. Conclusions: mHealth-based lifestyle interventions had a favorable impact on the prevention of GDM in pregnant women with overweight and obesity. Future studies need to further explore the potential of mHealth-based interventions for GDM through better design and more rigorous large-scale RCTs. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42021286995; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=286995 ", doi="10.2196/49373", url="https://mhealth.jmir.org/2024/1/e49373", url="http://www.ncbi.nlm.nih.gov/pubmed/38231555" } @Article{info:doi/10.2196/50293, author="Moungui, Claude Henri and Nana-Djeunga, Clotaire Hugues and Anyiang, Frankline Che and Cano, Mireia and Ruiz Postigo, Antonio Jose and Carrion, Carme", title="Dissemination Strategies for mHealth Apps: Systematic Review", journal="JMIR Mhealth Uhealth", year="2024", month="Jan", day="5", volume="12", pages="e50293", keywords="mobile health", keywords="mHealth", keywords="mobile health apps", keywords="mHealth apps", keywords="dissemination", keywords="marketing strategies", keywords="digital marketing", keywords="engagement", keywords="onboarding", keywords="systematic review", keywords="systematic", keywords="market", keywords="marketing", keywords="app", keywords="apps", keywords="adoption", keywords="consumer", keywords="mobile phone", abstract="Background: Among the millions of mobile apps in existence, thousands fall under the category of mobile health (mHealth). Although the utility of mHealth apps has been demonstrated for disease diagnosis, treatment data management, and health promotion strategies, to be effective they must reach and be used by their target audience. An appropriate marketing strategy can ensure that apps reach potential users and potentially convert them to actual users. Such a strategy requires definitions of target end users, communication channels, and advertising content, as well as a timeline for effectively reaching and motivating end users to adopt and maintain engagement with the mHealth app. Objective: The aim of this study was to identify strategies and elements that ensure that end users adopt and remain engaged with mHealth apps. Methods: A systematic search of the PubMed, PsycINFO, Scopus, and CINAHL databases was conducted for suitable studies published between January 1, 2018, and September 30, 2022. Two researchers independently screened studies for inclusion, extracted data, and assessed the risk of bias. The main outcome was dissemination strategies for mHealth apps. Results: Of the 648 papers retrieved from the selected databases, only 10 (1.5\%) met the inclusion criteria. The marketing strategies used in these studies to inform potential users of the existence of mHealth apps and motivate download included both paid and unpaid strategies and used various channels, including social media, emails, printed posters, and face-to-face communication. Most of the studies reported a combination of marketing concepts used to advertise their mHealth apps. Advertising messages included instructions on where and how to download and install the apps. In most of the studies (6/10, 60\%), instructions were oriented toward how to use the apps and maintain engagement with a health intervention. The most frequently used paid marketing platform was Facebook Ads Manager (2/10, 20\%). Advertising performance was influenced by many factors, including but not limited to advertising content. In 1 (10\%) of the 10 studies, animated graphics generated the greatest number of clicks compared with other image types. The metrics used to assess marketing strategy effectiveness were number of downloads; nonuse rate; dropout rate; adherence rate; duration of app use; and app usability over days, weeks, or months. Additional indicators such as cost per click, cost per install, and clickthrough rate were mainly used to assess the cost-effectiveness of paid marketing campaigns. Conclusions: mHealth apps can be disseminated via paid and unpaid marketing strategies using various communication channels. The effects of these strategies are reflected in download numbers and user engagement with mHealth apps. Further research could provide guidance on a framework for disseminating mHealth apps and encouraging their routine use. ", doi="10.2196/50293", url="https://mhealth.jmir.org/2024/1/e50293", url="http://www.ncbi.nlm.nih.gov/pubmed/38180796" } @Article{info:doi/10.2196/48716, author="Wu, Ying and Wang, Xiaohui and Zhou, Mengyao and Huang, Zhuoer and Liu, Lijuan and Cong, Li", title="Application of eHealth Tools in Anticoagulation Management After Cardiac Valve Replacement: Scoping Review Coupled With Bibliometric Analysis", journal="JMIR Mhealth Uhealth", year="2024", month="Jan", day="5", volume="12", pages="e48716", keywords="eHealth tool", keywords="cardiac valve replacement", keywords="anticoagulation management", keywords="scoping review", keywords="bibliometrics analysis", keywords="rehabilitation", abstract="Background: Anticoagulation management can effectively prevent complications in patients undergoing cardiac valve replacement (CVR). The emergence of eHealth tools provides new prospects for the management of long-term anticoagulants. However, there is no comprehensive summary of the application of eHealth tools in anticoagulation management after CVR. Objective: Our objective is to clarify the current state, trends, benefits, and challenges of using eHealth tools in the anticoagulation management of patients after CVR and provide future directions and recommendations for development in this field. Methods: This scoping review follows the 5-step framework developed by Arksey and O'Malley. We searched 5 databases such as PubMed, MEDLINE, Web of Science, CINAHL, and Embase using keywords such as ``eHealth,'' ``anticoagulation,'' and ``valve replacement.'' We included papers on the practical application of eHealth tools and excluded papers describing the underlying mechanisms for developing eHealth tools. The search time ranged from the database inception to March 1, 2023. The study findings were reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). Additionally, VOSviewer (version 1.6.18) was used to construct visualization maps of countries, institutions, authors, and keywords to investigate the internal relations of included literature and to explore research hotspots and frontiers. Results: This study included 25 studies that fulfilled the criteria. There were 27,050 participants in total, with the sample size of the included studies ranging from 49 to 13,219. The eHealth tools mainly include computer-based support systems, electronic health records, telemedicine platforms, and mobile apps. Compared to traditional anticoagulation management, eHealth tools can improve time in therapeutic range and life satisfaction. However, there is no significant impact observed in terms of economic benefits and anticoagulation-related complications. Bibliometric analysis suggests the potential for increased collaboration and opportunities among countries and academic institutions. Italy had the widest cooperative relationships. Machine learning and artificial intelligence are the popular research directions in anticoagulation management. Conclusions: eHealth tools exhibit promise for clinical applications in anticoagulation management after CVR, with the potential to enhance postoperative rehabilitation. Further high-quality research is needed to explore the economic benefits of eHealth tools in long-term anticoagulant therapy and the potential to reduce the occurrence of adverse events. ", doi="10.2196/48716", url="https://mhealth.jmir.org/2024/1/e48716", url="http://www.ncbi.nlm.nih.gov/pubmed/38180783" } @Article{info:doi/10.2196/39286, author="Rojo, Ana and Castrillo Calvillo, Arantxa and L{\'o}pez, Cristina and Raya, Rafael and Moreno, C. Juan", title="Effects of a Virtual Reality Cycling Platform on Lower Limb Rehabilitation in Patients With Ataxia and Hemiparesis: Pilot Randomized Controlled Trial", journal="JMIR Serious Games", year="2024", month="Jan", day="4", volume="12", pages="e39286", keywords="ataxia", keywords="cycling", keywords="hemiparesis", keywords="lower limb", keywords="neuropathology", keywords="rehabilitation", keywords="virtual reality", keywords="limb", keywords="intervention", keywords="neural", keywords="neural plasticity", keywords="therapy", keywords="muscle", keywords="strength", keywords="balance", keywords="tool", keywords="exercise", keywords="physical activity", keywords="neuroplasticity", abstract="Background: New interventions based on motor learning principles and neural plasticity have been tested among patients with ataxia and hemiparesis. Therapies of pedaling exercises have also shown their potential to induce improvements in muscle activity, strength, and balance. Virtual reality (VR) has been demonstrated as an effective tool for improving the adherence to physical therapy, but it is still undetermined if it promotes greater improvements than conventional therapy. Objective: Our objective was to compare the effect on lower limb range of motion (ROM) when using VR technology for cycling exercise versus not using VR technology. Methods: A randomized controlled trial with 20 patients with ataxia and hemiparesis was carried out. The participants were divided into 2 groups: the experimental group (n=10, 50\%) performed pedaling exercises using the VR system and the control group (n=10, 50\%) performed pedaling exercises without using VR. Measurements of the active and passive ROM of the hip and knee joint were taken before and after a cycling intervention, which consisted of 3 sessions of the same duration but with progressively increasing speeds (4, 5, and 6 km/h). Repeated measures ANOVAs were conducted to compare the preintervention (Ti) and postintervention (Te) assessments within each group. Additionally, the improvement effect of using the VR system was analyzed by comparing the variation coefficient ($\Delta$ = 1 -- [Te / Ti]) between the preintervention and postintervention assessments for each group. Group comparisons were made using independent 1-tailed t tests. Results: Significant improvements were shown in active left hip flexion (P=.03) over time, but there was no group-time interaction effect (P=.67). Passive left hip flexion (P=.93) did not show significant improvements, and similar results were observed for active and passive right hip flexion (P=.39 and P=.83, respectively). Neither assessments of knee flexion (active left: P=.06; passive left: P=.76; active right: P=.34; passive right: P=.06) nor knee extension showed significant changes (active left: P=.66; passive left: P=.92; active right: P=.12; passive right: P=.38). However, passive right knee extension (P=.04) showed a significant improvement over time. Overall, although active and passive ROM of the knee and hip joints showed a general improvement, no statistically significant differences were found between the groups. Conclusions: In this study, participants who underwent the cycling intervention using the VR system showed similar improvement in lower limb ROM to the participants who underwent conventional training. Ultimately, the VR system can be used to engage participants in physical activity. Trial Registration: ClinicalTrials.gov NCT05162040; https://www.clinicaltrials.gov/study/NCT05162040 ", doi="10.2196/39286", url="https://games.jmir.org/2023/1/e39286" } @Article{info:doi/10.2196/46558, author="Thompson, N. Alexandra and Dawson, R. Deirdre and Legasto-Mulvale, Michelle Jean and Chandran, Nivetha and Tanchip, Chelsea and Niemczyk, Veronika and Rashkovan, Jillian and Jeyakumar, Saisa and Wang, H. Rosalie and Cameron, I. Jill and Nalder, Emily", title="Mobile Technology--Based Interventions for Stroke Self-Management Support: Scoping Review", journal="JMIR Mhealth Uhealth", year="2023", month="Dec", day="6", volume="11", pages="e46558", keywords="stroke", keywords="chronic disease", keywords="self-management", keywords="rehabilitation", keywords="mobile health", keywords="mHealth", keywords="eHealth", keywords="telehealth", keywords="telemedicine", keywords="digital health", keywords="mobile phone", abstract="Background: There is growing interest in enhancing stroke self-management support using mobile health (mHealth) technology (eg, smartphones and apps). Despite this growing interest, ``self-management support'' is inconsistently defined and applied in the poststroke mHealth intervention literature, which limits efforts to synthesize and compare evidence. To address this gap in conceptual clarity, a scoping review was conducted. Objective: The objectives were to (1) identify and describe the types of poststroke mHealth interventions evaluated using a randomized controlled trial design, (2) determine whether (and how) such interventions align with well-accepted conceptualizations of self-management support (the theory by Lorig and Holman and the Practical Reviews in Self-Management Support [PRISMS] taxonomy by Pearce and colleagues), and (3) identify the mHealth functions that facilitate self-management. Methods: A scoping review was conducted according to the methodology by Arksey and O'Malley and Levac et al. In total, 7 databases were searched. Article screening and data extraction were performed by 2 reviewers. The data were analyzed using descriptive statistics and content analysis. Results: A total of 29 studies (26 interventions) were included. The interventions addressed 7 focal areas (physical exercise, risk factor management, linguistic exercise, activities of daily living training, medication adherence, stroke education, and weight management), 5 types of mobile devices (mobile phones or smartphones, tablets, wearable sensors, wireless monitoring devices, and laptops), and 7 mHealth functions (educating, communicating, goal setting, monitoring, providing feedback, reminding, and motivating). Collectively, the interventions aligned well with the concept of self-management support. However, on an individual basis (per intervention), the alignment was less strong. Conclusions: On the basis of the results, it is recommended that future research on poststroke mHealth interventions be more theoretically driven, more multidisciplinary, and larger in scale. ", doi="10.2196/46558", url="https://mhealth.jmir.org/2023/1/e46558", url="http://www.ncbi.nlm.nih.gov/pubmed/38055318" } @Article{info:doi/10.2196/49741, author="Lee, Sol and Rajaguru, Vasuki and Baek, Sang Joon and Shin, Jaeyong and Park, Youngmok", title="Digital Health Interventions to Enhance Tuberculosis Treatment Adherence: Scoping Review", journal="JMIR mHealth and uHealth", year="2023", month="Dec", day="4", volume="11", pages="e49741", keywords="tuberculosis", keywords="patient compliance", keywords="digital health", keywords="medication adherence", keywords="text messaging", keywords="mobile apps", keywords="application", keywords="medication", keywords="text", keywords="scoping review", keywords="disease management", keywords="chronic disease", keywords="communication", keywords="feedback", keywords="self-management", keywords="PRISMA", abstract="Background: Digital health technologies are widely used for disease management, with their computing platforms, software, and sensors being used for health care. These technologies are developed to manage chronic diseases and infectious bacterial diseases, including tuberculosis (TB). Objective: This study aims to comprehensively review the literature on the use of digital health interventions (DHIs) for enhancing TB treatment adherence and identify major strategies for their adoption. Methods: We conducted a literature search in the PubMed, Cochrane Library, Ovid Embase, and Scopus databases for relevant studies published between January 2012 and March 2022. Studies that focused on web-based or mobile phone--based interventions, medication adherence, digital health, randomized controlled trials, digital interventions, or mobile health and ubiquitous health technology for TB treatment and related health outcomes were included. Results: We identified 27 relevant studies and classified them according to the intervention method, a significant difference in treatment success, and health outcomes. The following interventions were emphasized: SMS text messaging interventions (8/27, 30\%), medicine reminders (6/27, 22\%), and web-based direct observation therapy (9/27, 33\%). Digital health technology significantly promoted disease management among individuals and health care professionals. However, only a few studies addressed 2-way communication therapies, such as interactive SMS text messaging and feedback systems. Conclusions: This scoping review classified studies on DHIs for patients with TB and demonstrated their potential for the self-management of TB. DHIs are still being developed, and evidence on the impact of digital technologies on enhancing TB treatment adherence remains limited. However, it is necessary to encourage patients' participation in TB treatment and self-management through bidirectional communication. We emphasize the importance of developing a communication system. ", doi="10.2196/49741", url="https://mhealth.jmir.org/2023/1/e49741" } @Article{info:doi/10.2196/45947, author="Harper, C. Rosie and Sheppard, Sally and Stewart, Carly and Clark, J. Carol", title="Exploring Adherence to Pelvic Floor Muscle Training in Women Using Mobile Apps: Scoping Review", journal="JMIR Mhealth Uhealth", year="2023", month="Nov", day="30", volume="11", pages="e45947", keywords="adherence", keywords="behavior change", keywords="mHealth", keywords="mobile apps", keywords="pelvic floor muscle training", keywords="women", abstract="Background: Pelvic floor dysfunction is a public health issue, with 1 in 3 women experiencing symptoms at some point in their lifetime. The gold standard of treatment for pelvic floor dysfunction is supervised pelvic floor muscle training (PFMT); however, adherence to PFMT in women is poor. Mobile apps are increasingly being used in the National Health Service to enable equity in the distribution of health care and increase accessibility to services. However, it is unclear how PFMT mobile apps influence PFMT adherence in women. Objective: We aimed to identify which behavior change techniques (BCTs) have been used in PFMT mobile apps, to distinguish the core ``capability, opportunity, and motivation'' (COM) behaviors targeted by the BCTs used in PFMT mobile apps, and to compare the levels of PFMT adherence in women between those using PFMT mobile apps and those receiving usual care. Methods: We conducted a scoping review of the literature. Published quantitative literature that compared the use of a PFMT mobile app to a control group was included to address the objectives of the study. The electronic bibliographic databases searched included MEDLINE, CINAHL, Scopus, Web of Science, and PEDro, along with CENTRAL. Studies were also identified from reference searching of systematic reviews. Original articles written in English from 2006 onward were included. Nonexperimental quantitative studies, qualitative studies, studies that use male participants, case studies, web-based interventions, and interventions that use vaginal probes were excluded. Narrative synthesis was conducted on eligible articles based on the aims of the study. Results: Of the 114 records retrieved from the search, a total of 6 articles met the eligibility and inclusion criteria. The total number of participants in the studies was 471. All PFMT mobile apps used the BCT ``prompts and cues.'' Opportunity was the core COM behavior targeted by the PFMT mobile apps. Higher levels of adherence to PFMT were observed among women using PFMT mobile apps. Conclusions: Digital ``prompts and cues'' are a BCT commonly used in PFMT mobile apps, and further research is required to practically assess whether a future randomized controlled trial that investigates the effectiveness of digital ``prompts and cues'' on PFMT adherence in women can be conducted. ", doi="10.2196/45947", url="https://mhealth.jmir.org/2023/1/e45947", url="http://www.ncbi.nlm.nih.gov/pubmed/38032694" } @Article{info:doi/10.2196/52377, author="Ponzo, Sonia and May, Merle and Tamayo-Elizalde, Miren and Bailey, Kerri and Shand, J. Alanna and Bamford, Ryan and Multmeier, Jan and Griessel, Ivan and Szulyovszky, Benedek and Blakey, William and Valentine, Sophie and Plans, David", title="App Characteristics and Accuracy Metrics of Available Digital Biomarkers for Autism: Scoping Review", journal="JMIR Mhealth Uhealth", year="2023", month="Nov", day="17", volume="11", pages="e52377", keywords="autism", keywords="diagnostics", keywords="digital biomarkers", keywords="digital health", keywords="mobile apps", keywords="neurodevelopmental conditions", abstract="Background: Diagnostic delays in autism are common, with the time to diagnosis being up to 3 years from the onset of symptoms. Such delays have a proven detrimental effect on individuals and families going through the process. Digital health products, such as mobile apps, can help close this gap due to their scalability and ease of access. Further, mobile apps offer the opportunity to make the diagnostic process faster and more accurate by providing additional and timely information to clinicians undergoing autism assessments. Objective: The aim of this scoping review was to synthesize the available evidence about digital biomarker tools to aid clinicians, researchers in the autism field, and end users in making decisions as to their adoption within clinical and research settings. Methods: We conducted a structured literature search on databases and search engines to identify peer-reviewed studies and regulatory submissions that describe app characteristics, validation study details, and accuracy and validity metrics of commercial and research digital biomarker apps aimed at aiding the diagnosis of autism. Results: We identified 4 studies evaluating 4 products: 1 commercial and 3 research apps. The accuracy of the identified apps varied between 28\% and 80.6\%. Sensitivity and specificity also varied, ranging from 51.6\% to 81.6\% and 18.5\% to 80.5\%, respectively. Positive predictive value ranged from 20.3\% to 76.6\%, and negative predictive value fluctuated between 48.7\% and 97.4\%. Further, we found a lack of details around participants' demographics and, where these were reported, important imbalances in sex and ethnicity in the studies evaluating such products. Finally, evaluation methods as well as accuracy and validity metrics of available tools were not clearly reported in some cases and varied greatly across studies. Different comparators were also used, with some studies validating their tools against the Diagnostic and Statistical Manual of Mental Disorders criteria and others through self-reported measures. Further, while in most cases, 2 classes were used for algorithm validation purposes, 1 of the studies reported a third category (indeterminate). These discrepancies substantially impact the comparability and generalizability of the results, thus highlighting the need for standardized validation processes and the reporting of findings. Conclusions: Despite their popularity, systematic evaluations and syntheses of the current state of the art of digital health products are lacking. Standardized and transparent evaluations of digital health tools in diverse populations are needed to assess their real-world usability and validity, as well as help researchers, clinicians, and end users safely adopt novel tools within clinical and research practices. ", doi="10.2196/52377", url="https://mhealth.jmir.org/2023/1/e52377", url="http://www.ncbi.nlm.nih.gov/pubmed/37976084" } @Article{info:doi/10.2196/46237, author="Grayek, Emily and Krishnamurti, Tamar and Hu, Lydia and Babich, Olivia and Warren, Katherine and Fischhoff, Baruch", title="Collection and Analysis of Adherence Information for Software as a Medical Device Clinical Trials: Systematic Review", journal="JMIR Mhealth Uhealth", year="2023", month="Nov", day="15", volume="11", pages="e46237", keywords="mobile health", keywords="mHealth", keywords="adherence", keywords="evaluation", keywords="usability", keywords="efficacy", keywords="systematic review", keywords="application", keywords="compliance", keywords="safety", keywords="effectiveness", keywords="engagement", keywords="risk", keywords="medical device", keywords="clinical trials", abstract="Background: The rapid growth of digital health apps has necessitated new regulatory approaches to ensure compliance with safety and effectiveness standards. Nonadherence and heterogeneous user engagement with digital health apps can lead to trial estimates that overestimate or underestimate an app's effectiveness. However, there are no current standards for how researchers should measure adherence or address the risk of bias imposed by nonadherence through efficacy analyses. Objective: This systematic review aims to address 2 critical questions regarding clinical trials of software as a medical device (SaMD) apps: How well do researchers report adherence and engagement metrics for studies of effectiveness and efficacy? and What efficacy analyses do researchers use to account for nonadherence and how appropriate are their methods? Methods: We searched the Food and Drug Administration's registration database for registrations of repeated-use, patient-facing SaMD therapeutics. For each such registration, we searched ClinicalTrials.gov, company websites, and MEDLINE for the corresponding clinical trial and study articles through March 2022. Adherence and engagement data were summarized for each of the 24 identified articles, corresponding to 10 SaMD therapeutics. Each article was analyzed with a framework developed using the Cochrane risk-of-bias questions to estimate the potential effects of imperfect adherence on SaMD effectiveness. This review, funded by the Richard King Mellon Foundation, is registered on the Open Science Framework. Results: We found that although most articles (23/24, 96\%) reported collecting information about SaMD therapeutic engagement, of the 20 articles for apps with prescribed use, only 9 (45\%) reported adherence information across all aspects of prescribed use: 15 (75\%) reported metrics for the initiation of therapeutic use, 16 (80\%) reported metrics reporting adherence between the initiation and discontinuation of the therapeutic (implementation), and 4 (20\%) reported the discontinuation of the therapeutic (persistence). The articles varied in the reported metrics. For trials that reported adherence or engagement, there were 4 definitions of initiation, 8 definitions of implementation, and 4 definitions of persistence. All articles studying a therapeutic with a prescribed use reported effectiveness estimates that might have been affected by nonadherence; only a few (2/20, 10\%) used methods appropriate to evaluate efficacy. Conclusions: This review identifies 5 areas for improving future SaMD trials and studies: use consistent metrics for reporting adherence, use reliable adherence metrics, preregister analyses for observational studies, use less biased efficacy analysis methods, and fully report statistical methods and assumptions. ", doi="10.2196/46237", url="https://mhealth.jmir.org/2023/1/e46237", url="http://www.ncbi.nlm.nih.gov/pubmed/37966871" } @Article{info:doi/10.2196/50419, author="Alsahli, Sultan and Hor, Su-yin and Lam, Mary", title="Factors Influencing the Acceptance and Adoption of Mobile Health Apps by Physicians During the COVID-19 Pandemic: Systematic Review", journal="JMIR Mhealth Uhealth", year="2023", month="Nov", day="8", volume="11", pages="e50419", keywords="mobile health", keywords="mHealth", keywords="mobile app", keywords="adoption", keywords="acceptance", keywords="barrier", keywords="attitude", keywords="physician", keywords="doctor", keywords="practitioner", keywords="mobile phone", abstract="Background: During the COVID-19 pandemic, the provision of and access to health care have been uniquely challenging, particularly during lockdowns or when dealing with COVID-19 cases. Health care professionals have had to provide patients with the necessary health care. However, delivering health care services while reducing face-to-face interaction puts an immense strain on health systems that are already overburdened. Against this backdrop, it is now more critical than ever to ensure the accessibility of health care services. Such access has been made increasingly available through mobile health (mHealth) apps. These apps have the potential to significantly improve health care outcomes and expectations and address some of the challenges confronting health care systems worldwide. Despite the advantages of mHealth, its acceptance and adoption remain low. Hence, health care organizations must consider the perceptions and opinions of physicians if the technology is to be successfully implemented. Objective: The objective of this systematic review was to explore and synthesize the scientific literature on the factors influencing the acceptance and adoption of mHealth among physicians during the COVID-19 pandemic. Methods: A systematic review of the studies published between March 2020 and December 2022 was conducted using the MEDLINE, Scopus, Embase, and ProQuest databases. The database search yielded an initial sample of 455 potential publications for analysis, of which 9 (2\%) met the inclusion criteria. The methodology of this review was based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Results: The factors influencing mHealth acceptance and adoption by physicians were divided into perceived barriers and perceived facilitators, which were further grouped into the following 3 major thematic categories: technological, individual, and organizational barriers and facilitators, respectively. The technological barriers were accessibility, technical issues, usefulness, and data management; individual barriers were perceived patient barriers, time and workload pressure, technical literacy, knowledge of mHealth, and peer support; and organizational barriers were financial factors, management support and engagement, data security, telemonitoring policy, and collaboration. The technological facilitators of uptake were technical factors, clinical usefulness, and data management; individual facilitators were patient-related care, intrinsic motivation, collaboration, and data sharing (individual); and organizational facilitators were workflow-related determinants, organizational financial support, recommendation of mHealth services, and evidence-based guidelines. Conclusions: This review summarized the evidence on the factors influencing mHealth acceptance and adoption by physicians during the COVID-19 pandemic. The main findings highlighted the importance of addressing organizational readiness to support physicians with adequate resources, shifting the focus from technological to patient-centered factors, and the seamless integration of mHealth into routine practice during and beyond the pandemic. Trial Registration: PROSPERO CRD42022356125; https://tinyurl.com/2mmhn5yu ", doi="10.2196/50419", url="https://mhealth.jmir.org/2023/1/e50419", url="http://www.ncbi.nlm.nih.gov/pubmed/37938873" } @Article{info:doi/10.2196/48204, author="de Melo Santana, Bruna and Raffin Moura, Julia and Martins de Toledo, Aline and Burke, Nogueira Thomaz and Fernandes Probst, Livia and Pasinato, Fernanda and Luiz Carregaro, Rodrigo", title="Efficacy of mHealth Interventions for Improving the Pain and Disability of Individuals With Chronic Low Back Pain: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2023", month="Nov", day="2", volume="11", pages="e48204", keywords="physiotherapy", keywords="back pain", keywords="mobile technology", keywords="efficacy", keywords="disability", keywords="chronic condition", keywords="chronic", keywords="effectiveness", keywords="self-management", keywords="systematic review", keywords="pain", keywords="meta-analysis", keywords="treatment", keywords="mHealth", keywords="mobile health", abstract="Background: Low back pain is one of the main causes of disability worldwide. Individuals with chronic conditions have been widely affected by the COVID-19 pandemic. In this context, mobile health (mHealth) has become popular, mostly due to the widespread use of smartphones. Despite the considerable number of apps for low back pain available in app stores, the effectiveness of these technologies is not established, and there is a lack of evidence regarding the effectiveness of the isolated use of mobile apps in the self-management of low back pain. Objective: We summarized the evidence on the effectiveness of mHealth interventions on pain and disability for individuals with chronic low back pain. Methods: We conducted a systematic review and meta-analysis comparing mHealth to usual care or no intervention. The search terms used were related to low back pain and mHealth. Only randomized controlled trials were included. The primary outcomes were pain intensity and disability, and the secondary outcome was quality of life. Searches were carried out in the following databases, without date or language restriction: PubMed, Scopus, Embase, Physiotherapy Evidence Database (PEDro), the Cochrane Library, and OpenGrey, in addition to article references. The risk of bias was analyzed using the PEDro scale. Data were summarized descriptively and through meta-analysis (pain intensity and disability). In the meta-analysis, eligible studies were combined while considering clinical and methodological homogeneity. The certainty of evidence was assessed using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) criteria. Results: A total of 5 randomized controlled trials were included, totaling 894 participants (447 allocated to the mHealth group and 445 to the usual care group), and they had similar methodological structure and interventions. Follow-up ranged from 6 weeks to 12 months. The studies did not demonstrate significant differences for pain intensity (mean difference ?0.86, 95\% CI ?2.29 to 0.58; P=.15) and disability (standardized mean difference ?0.24, 95\% CI ?0.69 to 0.20; P=.14) when comparing mHealth and usual care. All studies showed biases, with emphasis on nonconcealed allocation and nonblinding of the outcome evaluator. The certainty of evidence was rated as low for the analyzed outcomes. Conclusions: mHealth alone was no more effective than usual care or no treatment in improving pain intensity and disability in individuals with low back pain. Due to the biases found and the low certainty of evidence, the evidence remains inconclusive, and future quality clinical trials are needed. Trial Registration: PROSPERO CRD42022338759; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=338759 ", doi="10.2196/48204", url="https://mhealth.jmir.org/2023/1/e48204" } @Article{info:doi/10.2196/42968, author="Bentlage, Ellen and Nyamadi, Jnr John and Dubbeldam, Rosemary", title="The Importance of Activating Factors in Physical Activity Interventions for Older Adults Using Information and Communication Technologies: Systematic Review", journal="JMIR Mhealth Uhealth", year="2023", month="Oct", day="24", volume="11", pages="e42968", keywords="older adults", keywords="information and communication technology", keywords="healthy aging", keywords="activation factors", keywords="skills", keywords="knowledge", keywords="motivation", keywords="behavior change techniques", keywords="physical activity", abstract="Background: In an aging population, it is important to activate older adults in taking care of their own health. Increasing physical activity is one way to avoid or lessen age-related physical and mental impairments. Interest in the use of information and communication technology (ICT) tools to promote physical activity among older adults is growing considerably. Such tools are suitable for communicating activation factors---skills, knowledge, and motivation---by integrating a variety of behavior change techniques (BCTs) to enhance physical activity. Although activation factors have been incorporated into physical activity interventions using ICT, little is known about the actual integration methods used in such interventions or about the effects of activation factors on influencing behavior change. Objective: The first aim of this study was to identify which of the activation factors were covered in physical activity--promoting ICT interventions for older adults and which BCTs were used to address them. The second objective was to classify the user interaction interfaces and delivery modes that were used to promote these activation factors. Methods: The search engines of PubMed, Web of Science, and ScienceDirect were used to search for and identify articles examining the effectiveness of ICT interventions for promoting physical activity in older adults. References and related data were selected, extracted, and reviewed independently by 2 reviewers. The risk of bias was assessed, and any conflict was addressed by a third separate reviewer. Selected articles included older adults aged ?55 years without pre-existing medical diseases and other physical or mental conditions that could hinder movement. Results: In total, 368 records were retrieved, and 13 studies met all inclusion criteria. Articles differed in terms of themes, timescales, user interaction interfaces, and outcome measures; therefore, a quantitative data synthesis was not feasible. Motivation was the most promoted activation factor among all trials (33 times). An app and a smartwatch were used in the majority of intervention groups (7/20, 35\%) for tracking physical activity and receiving personalized feedback based on the individual goals. Skills (25 times) and knowledge (17 times) were the next most commonly addressed activation factors. Face-to-face interaction was the most used approach to targeting users' skills, including providing instructions on how to perform a behavior and exchanging knowledge via education on the health consequences of insufficient physical activity. Overall, integrating all 3 activation factors and using multiple user interaction interfaces with a variety of delivery modes proved the most effective in improving physical activity. Conclusions: This study highlights commonly used BCTs and preferred modes of their delivery. So far, only a limited number of available BCTs (21/102, 21\%) have been integrated. Considering their effectiveness, a larger variety of BCTs that address skills, knowledge, and motivation should be exploited in future ICT interventions. ", doi="10.2196/42968", url="https://mhealth.jmir.org/2023/1/e42968" } @Article{info:doi/10.2196/49051, author="Li, Yufei and Chen, Weihong and Liang, Yanjing and Yang, Ling and Hou, Lili", title="Evaluation of Mobile Health Technology Interventions for the Postdischarge Management of Patients With Head and Neck Cancer: Scoping Review", journal="JMIR Mhealth Uhealth", year="2023", month="Oct", day="23", volume="11", pages="e49051", keywords="head and neck cancer", keywords="mobile health technology", keywords="postdischarge", keywords="self-management", keywords="rehabilitation", abstract="Background: Patients with head and neck cancer (HNC) often experience various types and degrees of complications and functional impairment following surgery or radiotherapy. Consequently, these patients require extensive postdischarge rehabilitation, either at home or in the community. Numerous studies have shown the advantages of mobile Health (mHealth) technology in assisting patients with cancer with self-management and rehabilitation during the postdischarge period. However, few reviews have focused on the intervention, management, and evaluation of mHealth technology in postdischarge patients with HNC. Objective: This study aimed to conduct a scoping review of mHealth technology apps and interventions currently available to patients discharged from hospitals after receiving treatment for HNC. This study sought to identify and summarize the types and effectiveness of existing mHealth interventions as well as the differences in their outcome assessments. Methods: The PubMed, Embase, Web of Science, and CINAHL databases were used to identify studies with no publication time limits. The keywords ``mobile health technology'' and ``head and neck cancer'' were combined to address the main concepts of the research questions. Results: Of the 1625 papers identified, 13 (0.8\%) met the inclusion and exclusion criteria. Most studies (n=8, 61.5\%) were randomized controlled trials (RCTs) and cohort studies. These studies were conducted in 6 countries. The main aims of the mHealth interventions in these studies are as follows: (1) symptom monitoring and assessment, (2) rehabilitation training, (3) access to medical health information, (4) telehealth advisers, (5) peer communication and support, and (6) follow-up/review reminders. The outcome evaluations of the 13 included studies were grouped into 4 categories: (1) technology usability and patient satisfaction, (2) self-management of symptoms and patient-reported outcome--related indicators, (3) adherence, and (4) health-related quality of life. Conclusions: A limited number of studies have investigated the use of mHealth technology in the postdischarge self-management of patients with HNC. The existing literature suggests that mHealth technology can effectively assist patients with HNC in self-management and postdischarge interventions. It plays an important role in addressing patients' health information needs, reducing both their somatic and psychological burdens, and improving their overall quality of life. Future research should prioritize conducting additional high-quality RCTs to evaluate the usability and analyze the cost-effectiveness of mHealth technology. ", doi="10.2196/49051", url="https://mhealth.jmir.org/2023/1/e49051", url="http://www.ncbi.nlm.nih.gov/pubmed/37870887" } @Article{info:doi/10.2196/49003, author="van Kessel, Robin and Srivastava, Divya and Kyriopoulos, Ilias and Monti, Giovanni and Novillo-Ortiz, David and Milman, Ran and Zhang-Czabanowski, Wilhelm Wojciech and Nasi, Greta and Stern, Dora Ariel and Wharton, George and Mossialos, Elias", title="Digital Health Reimbursement Strategies of 8 European Countries and Israel: Scoping Review and Policy Mapping", journal="JMIR Mhealth Uhealth", year="2023", month="Sep", day="29", volume="11", pages="e49003", keywords="digital health", keywords="telehealth", keywords="telemedicine", keywords="reimbursement", keywords="policy", keywords="Europe", keywords="policy mapping", keywords="mapping", keywords="pricing", keywords="digital health app", keywords="application", keywords="health care ecosystem", keywords="framework", keywords="integration", abstract="Background: The adoption of digital health care within health systems is determined by various factors, including pricing and reimbursement. The reimbursement landscape for digital health in Europe remains underresearched. Although various emergency reimbursement decisions were made during the COVID-19 pandemic to enable health care delivery through videoconferencing and asynchronous care (eg, digital apps), research so far has primarily focused on the policy innovations that facilitated this outside of Europe. Objective: This study examines the digital health reimbursement strategies in 8 European countries (Belgium, France, Germany, Italy, the Netherlands, Poland, Sweden, and the United Kingdom) and Israel. Methods: We mapped available digital health reimbursement strategies using a scoping review and policy mapping framework. We reviewed the literature on the MEDLINE, Embase, Global Health, and Web of Science databases. Supplementary records were identified through Google Scholar and country experts. Results: Our search strategy yielded a total of 1559 records, of which 40 (2.57\%) were ultimately included in this study. As of August 2023, digital health solutions are reimbursable to some extent in all studied countries except Poland, although the mechanism of reimbursement differs significantly across countries. At the time of writing, the pricing of digital health solutions was mostly determined through discussions between national or regional committees and the manufacturers of digital health solutions in the absence of value-based assessment mechanisms. Financing digital health solutions outside traditional reimbursement schemes was possible in all studied countries except Poland and typically occurs via health innovation or digital health--specific funding schemes. European countries have value-based pricing frameworks that range from nonexistent to embryonic. Conclusions: Studied countries show divergent approaches to the reimbursement of digital health solutions. These differences may complicate the ability of patients to seek cross-country health care in another country, even if a digital health app is available in both countries. Furthermore, the fragmented environment will present challenges for developers of such solutions, as they look to expand their impact across countries and health systems. An increased emphasis on developing a clear conceptualization of digital health, as well as value-based pricing and reimbursement mechanisms, is needed for the sustainable integration of digital health. This study can therein serve as a basis for further, more detailed research as the field of digital health reimbursement evolves. ", doi="10.2196/49003", url="https://mhealth.jmir.org/2023/1/e49003", url="http://www.ncbi.nlm.nih.gov/pubmed/37773610" } @Article{info:doi/10.2196/48253, author="Zhou, Xinmei and Wei, Xiaowen and Cheng, Anqi and Liu, Zhao and Su, Zheng and Li, Jinxuan and Qin, Rui and Zhao, Liang and Xie, Ying and Huang, Zhenxiao and Xia, Xin and Liu, Yi and Song, Qingqing and Xiao, Dan and Wang, Chen", title="Mobile Phone--Based Interventions for Smoking Cessation Among Young People: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2023", month="Sep", day="12", volume="11", pages="e48253", keywords="smoking cessation", keywords="young people", keywords="mobile health", keywords="text messaging", keywords="mHealth", keywords="PRISMA", abstract="Background: Mobile phone--based cessation interventions have emerged as a promising alternative for smoking cessation, while evidence of the efficacy of mobile phone--based smoking cessation programs among young people is mixed. Objective: This study aimed to determine the efficacy of mobile phone--based interventions compared to usual practice or assessment-only controls on smoking cessation in young people. Methods: In this systematic review and meta-analysis, we searched Cochrane Library, Embase, PubMed, and Web of Science on March 8, 2023. We included randomized controlled trials that examined the efficacy of mobile phone--based interventions on smoking cessation in young people (age ?30 years). The risk of bias was assessed with Cochrane Risk of Bias 2. Results: A total of 13 eligible studies, comprising 27,240 participants, were included in this analysis. The age range of the participants was between 16 and 30 years. Nine studies were SMS text messaging interventions, and 4 studies were app-based interventions. The duration of the smoking cessation intervention varied from 5 days to 6 months. The included studies were conducted in the following countries: the United States, China, Sweden, Canada, Switzerland, and Thailand. The meta-analysis revealed that SMS text messaging interventions significantly improved continuous abstinence rates compared to inactive control conditions (risk ratio [RR] 1.51, 95\% CI 1.24-1.84). The subgroup analysis showed pooled RRs of 1.90 (95\% CI 1.29-2.81), 1.64 (95\% CI 1.23-2.18), and 1.35 (95\% CI 1.04-1.76) for continuous abstinence at the 1-, 3-, and 6- month follow-up, respectively. Pooling across 7 studies, SMS text messaging interventions showed efficacy in promoting 7-day point prevalence abstinence (PPA), with an RR of 1.83 (95\% CI 1.34-2.48). The subgroup analysis demonstrated a significant impact at the 1- and 3-month follow-ups, with pooled RRs of 1.72 (95\% CI 1.13-2.63) and 2.54 (95\% CI 2.05-3.14), respectively, compared to inactive control conditions. However, at the 6-month follow-up, the efficacy of SMS text messaging interventions in promoting 7-day PPA was not statistically significant (RR 1.45, 95\% CI 0.92-2.28). In contrast, app-based interventions did not show significant efficacy in promoting continuous abstinence or 7-day PPA. However, it is important to note that the evidence for app-based interventions was limited. Conclusions: SMS text messaging--based smoking cessation interventions compared to inactive controls were associated with abstinence among young people and could be considered a viable option for smoking cessation in this population. More research is needed on smoking cessation apps, especially apps that target young people. Future research should focus on identifying the most effective mobile phone--based cessation approaches and on developing strategies to increase their uptake and intention. Trial Registration: PROSPERO CRD42022318845; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=318845 ", doi="10.2196/48253", url="https://mhealth.jmir.org/2023/1/e48253" } @Article{info:doi/10.2196/46143, author="V{\"a}yrynen, Elina and Hakola, Sanna and Keski-Salmi, Anniina and J{\"a}ms{\"a}, Hannaleena and Vainionp{\"a}{\"a}, Raija and Karki, Saujanya", title="The Use of Patient-Oriented Mobile Phone Apps in Oral Health: Scoping Review", journal="JMIR Mhealth Uhealth", year="2023", month="Sep", day="6", volume="11", pages="e46143", keywords="oral health", keywords="dentistry", keywords="mobile apps", keywords="mobile health", keywords="mHealth", keywords="mobile phone", abstract="Background: Oral health is a significant part of general health. Poor oral health can influence an individual's appearance, self-esteem, eating, and speaking. The use of mobile phone apps has been growing in the field of medicine, including dentistry. However, to date, there is no evidence related to the availability of mobile apps focusing on various branches of dentistry. Objective: The aim of this study was to review the scientific literature on the use of patient-oriented mobile phone apps in oral health and summarize the key findings. Methods: A scoping review of published scientific literature on the use of patient-oriented mobile phone apps in oral health was conducted in accordance with the Joanna Briggs Institute. A search was performed in PubMed and Scopus for studies published between January 2000 and June 2021 that were written in English. All study types except for those reporting developmental protocols were included in this review. In total, 2 reviewers independently screened the studies using the eligibility criteria. The study protocol was registered in the Open Science Framework registries in June 2021. Results: The initial search yielded a total of 977 studies, 45 (4.6\%) of which met the inclusion criteria. All the studies (45/45, 100\%) were published after 2009. Most studies (31/45, 69\%) concerned oral health promotion using mobile phone apps, followed by behavior management (5/45, 11\%). More than half (23/45, 51\%) of the included studies were conducted in Asian countries. Overall, 31\% (14/45) of the studies focused on adolescents. A total of 51\% (23/45) of the studies were randomized controlled trials (RCTs). Approximately 39\% (9/23) of the included RCT studies reported a substantial reduction in dental plaque, and 26\% (6/23) of the studies reported significant improvement in gingival health. Regarding dental anxiety management, 13\% (3/23) of the RCT studies reported a significant decrease in mean heart rate and lower Facial Image Scale scores. Conclusions: According to the literature, the use of mobile apps in oral health is increasing among patients, mainly children and adolescents. Many studies that have used mobile apps have focused on promoting oral health. However, other areas such as diagnostic and remote consultations (teledentistry) have until recently been neglected despite their great potential. ", doi="10.2196/46143", url="https://mhealth.jmir.org/2023/1/e46143", url="http://www.ncbi.nlm.nih.gov/pubmed/37672331" } @Article{info:doi/10.2196/43742, author="Aovare, Pearl and Abdulai, Kasim and Laar, Amos and van der Linden, L. Eva and Moens, Nicolaas and Richard, Edo and Moll van Charante, P. Eric and Agyemang, Charles", title="Assessing the Effectiveness of mHealth Interventions for Diabetes and Hypertension Management in Africa: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2023", month="Aug", day="29", volume="11", pages="e43742", keywords="mobile health", keywords="interventions", keywords="diabetes", keywords="blood sugar", keywords="hypertension", keywords="management", keywords="effectiveness", keywords="chronic disease", keywords="Africa", keywords="blood pressure", keywords="glycemic", keywords="intervention", keywords="mHealth", keywords="efficiency", keywords="resource", abstract="Background: Mobile health (mHealth) interventions are effective in improving chronic disease management, mainly in high-income countries. However, less is known about the efficacy of mHealth interventions for the reduction of cardiovascular risk factors, including for hypertension and diabetes, which are rapidly increasing in low- and middle-income countries. Objective: This study aimed to assess the efficacy of mHealth interventions for diabetes and hypertension management in Africa. Methods: We searched PubMed, Cochrane Library, Google Scholar, African Journals Online, and Web of Science for relevant studies published from inception to July 2022. The main outcomes of interest were changes in hemoglobin A1c (HbA1c), systolic blood pressure, and diastolic blood pressure. The random or fixed effect model was used for the meta-analysis, and the I2 statistic was used to gauge study heterogeneity. Z tests and P values were used to evaluate the effect of mHealth interventions on HbA1c and blood pressure levels. Results: This review included 7 studies (randomized controlled trials) with a total of 2249 participants. Two studies assessed the effect of mHealth on glycemic control, and 5 studies assessed the effect of mHealth on blood pressure control. The use of mHealth interventions was not associated with significant reductions in HbA1c levels (weighted mean difference [WMD] 0.20, 95\% CI ?0.40 to 0.80; P=.51) among patients with diabetes and systolic blood pressure (WMD ?1.39, 95\% CI ?4.46 to 1.68; P=.37) and diastolic blood pressure (WMD 0.36, 95\% CI ?1.37 to 2.05; P=.69) among patients with hypertension. After conducting sensitivity analyses using the leave-one-out method, the Kingue et al study had an impact on the intervention, resulting in a 2 mm Hg reduction in systolic blood pressure (WMD ?2.22, 95\% CI ?3.94 to ?0.60; P=.01) but was nonsignificant for diastolic blood pressure and HbA1c levels after omitting the study. Conclusions: Our review provided no conclusive evidence for the effectiveness of mHealth interventions in reducing blood pressure and glycemic control in Africa among persons with diabetes and hypertension. To confirm these findings, larger randomized controlled trials are required. Trial Registration: PROSPERO CRD42021230642; https://?www.crd.york.ac.uk/?prospero/?display\_record.php??RecordID=?230642 ", doi="10.2196/43742", url="https://mhealth.jmir.org/2023/1/e43742" } @Article{info:doi/10.2196/47553, author="Hu, Yuanjia and Lu, Yang and Tian, Chenghua and He, Yunfan and Rong, Kaiyi and Pan, Sijia and Lei, Jianbo", title="Current Status and Trends in mHealth-Based Research for Treatment and Intervention in Tinnitus: Bibliometric and Comparative Product Analysis", journal="JMIR Mhealth Uhealth", year="2023", month="Aug", day="24", volume="11", pages="e47553", keywords="tinnitus", keywords="mobile health", keywords="mHealth", keywords="internet", keywords="application", keywords="software", keywords="bibliometrics", keywords="mobile phone", abstract="Background: As a global medical problem, tinnitus can seriously harm human health and is difficult to alleviate, ranking among the top 3 complex diseases in the otolaryngology field. Traditional cognitive behavioral therapy and sound therapy require offline face-to-face treatment with medical staff and have limited effectiveness. Mobile health (mHealth), which, in recent decades, has been greatly applied in the field of rehabilitation health care, improving access to health care resources and the quality of services, has potential research value in the adjunctive treatment of tinnitus. Objective: This study aimed to understand the research trends, product characteristics, problems, and research transformation of tinnitus treatment software by analyzing the research progress of mHealth for tinnitus treatment based on the literature and related marketed apps. Methods: Bibliometric methods were used to describe the characteristics of the relevant literature in terms of the number and topics of publications, authors, and institutions. We further compared the features and limitations of the currently available tinnitus treatment software. Results: Data published until February 28, 2022, were collected. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) standardized screening process, 75 papers were included. The country with the highest number of publications was Germany, followed by the United Kingdom and the United States, whereas China had only a single relevant study. The most frequently found journals were the American Journal of Audiology and the Journal of the American Academy of Audiology (18/75, 24\%). With regard to publication topics, cognitive behavioral therapy started to become a hot topic in 2017, and research on mHealth apps has increased. In this study, 28 tinnitus treatment apps were obtained (n=24, 86\% from product data and n=4, 14\% from literature data); these apps were developed mainly in the United States (10/28, 36\%) or China (9/28, 32\%). The main treatment methods were sound therapy (10/28, 36\%) and cognitive behavioral therapy (2/28, 7\%). Of the 75 publications, 7 (9\%) described apps in the market stage. Of the 28 apps, 22 (79\%) lacked literature studies or evidence from professional bodies. Conclusions: We found that, as a whole, the use of mHealth for treatment and intervention in tinnitus was showing a rapid development, in which good progress had been made in studies around sound therapy and cognitive behavioral therapy, although most of the studies (50/75, 67\%) focused on treatment effects. However, the field is poorly accepted in top medical journals, and the majority are in the research design phase, with a lack of translation of the literature results and clinical validation of the marketed apps. Furthermore, in the future, novel artificial intelligence techniques should be used to address the issue of staged monitoring of tinnitus. ", doi="10.2196/47553", url="https://mhealth.jmir.org/2023/1/e47553", url="http://www.ncbi.nlm.nih.gov/pubmed/37616044" } @Article{info:doi/10.2196/46359, author="Zhong, Wen and Liu, Rui and Cheng, Hongxin and Xu, Lin and Wang, Lu and He, Chengqi and Wei, Quan", title="Longer-Term Effects of Cardiac Telerehabilitation on Patients With Coronary Artery Disease: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2023", month="Jul", day="28", volume="11", pages="e46359", keywords="cardiac telerehabilitation", keywords="coronary artery disease", keywords="CAD", keywords="cardiac rehabilitation", keywords="CR", keywords="long-term effect", keywords="meta-analysis", abstract="Background: Cardiac telerehabilitation offers a flexible and accessible model for patients with coronary artery disease (CAD), effectively transforming the traditional cardiac rehabilitation (CR) approach. Objective: This systematic review and meta-analysis aimed to evaluate the long-term effectiveness of cardiac telerehabilitation. Methods: We searched randomized controlled trials (RCTs) in 7 electronic databases: PubMed, Web of Science, EMBASE, the Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, the China National Knowledge Infrastructure, and WANFANG. The primary outcome focused on cardiopulmonary fitness. For secondary outcomes, we examined cardiovascular risk factors (blood pressure, BMI, and serum lipids), psychological scales of depression and anxiety, quality of life (QoL), cardiac telerehabilitation adherence, and adverse events. Results: In total, 10 RCTs fulfilled the predefined criteria, which were reviewed in our meta-analysis. The results showed that after cardiac telerehabilitation, there was a significant difference in the improvement in long-term peak oxygen uptake compared to center-based CR (mean difference [MD] 1.61, 95\% CI 0.38-2.85, P=.01), particularly after 6-month rehabilitation training (MD 1.87, 95\% CI 0.34-3.39, P=.02). The pooled effect size of the meta-analysis indicated that there were no significant differences in the reduction in cardiovascular risk factor control. There was also no practical demonstration of anxiety scores or depression scores. However, cardiac telerehabilitation demonstrated an improvement in the long-term QoL of patients (MD 0.92, 95\% CI 0.06-1.78, P=.04). In addition, the study reported a high completion rate (80\%) for cardiac telerehabilitation interventions. The incidence of adverse events was also low during long-term follow-up. Conclusions: Cardiac telerehabilitation proves to be more effective in improving cardiopulmonary fitness and QoL during the long-term follow-up for patients with CAD. Our study highlights monitoring-enabled and patient-centered telerehabilitation programs, which play a vital role in the recovery and development of CAD and in the long-term prognosis of patients. ", doi="10.2196/46359", url="https://mhealth.jmir.org/2023/1/e46359", url="http://www.ncbi.nlm.nih.gov/pubmed/37505803" } @Article{info:doi/10.2196/44753, author="Visier-Alfonso, Eugenia Mar{\'i}a and S{\'a}nchez-L{\'o}pez, Mairena and Rodr{\'i}guez-Mart{\'i}n, Beatriz and Ruiz-Hermosa, Abel and Bartolom{\'e}-Guti{\'e}rrez, Raquel and Sequ{\'i}-Dom{\'i}nguez, Irene and Mart{\'i}nez-Vizca{\'i}no, Vicente", title="Parents' Perceptions of Children's and Adolescents' Use of Electronic Devices to Promote Physical Activity: Systematic Review of Qualitative Evidence", journal="JMIR Mhealth Uhealth", year="2023", month="Jul", day="20", volume="11", pages="e44753", keywords="physical activity", keywords="electronic devices", keywords="eHealth", keywords="parents' perceptions", keywords="children", keywords="adolescents", keywords="systematic review", keywords="qualitative", abstract="Background: The use of physical activity (PA) electronic devices offers a unique opportunity to engage children and adolescents in PA. For this age group (2-17 years), parents play a key role in promoting healthy lifestyles and regulating the use of electronic devices. Therefore, parents' perceptions of the use of electronic devices for PA in children and adolescents are critical for efficient intervention. Objective: The aim of this qualitative systematic review was to improve the understanding of parents' perceptions of the use of electronic devices for PA in children and adolescents. Methods: A systematic search of electronic databases (Medline/PubMed, SPORTDiscus, Web of Science, Scopus, OpenGrey, and Deep Blue) was conducted. Studies from inception (2010) to May 2022 were identified. Qualitative studies on the perceptions of healthy children's and adolescents' (aged 2-17 years) parents regarding PA interventions performed on electronic devices were included according to the Cochrane Qualitative and Implementation Methods Group Guidance Series and the Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) statement. The Joanna Briggs Institute Qualitative Assessment and Review Instrument was used for methodological validity. Results: In total, 18 studies with 410 parents, mostly mothers, were included. Parents' perceptions were grouped into 4 categories: usefulness, advantages, general perceptions (electronic devices for health promotion, preferences for real-life PA, and concerns), and acceptability (barriers and facilitators) of electronic devices for PA. Parents perceived electronic devices as useful for increasing PA, learning new skills, and increasing motivation for PA and valued those devices that promoted socialization and family and peer bonding. In terms of general perceptions, parents had positive attitudes toward PA electronic devices; however, they preferred outdoor and real-life PA, especially for preschoolers and children. Concerns, such as physical and psychological harm, addiction, conflicts, and compliance difficulties, were found. Facilitators were identified as ease of use, appropriate feedback, promotion of socialization, and motivational strategies, such as rewards, challenges, and attractiveness. Barriers, such as discomfort, price, and difficulties in using or understanding electronic devices, were also identified. For older children and adolescents, parents were more concerned about high levels of screen time and setting limits on electronic devices and therefore preferred PA electronic devices rather than traditional ones. Conclusions: Overall, the participants had positive attitudes toward electronic devices for PA and perceived them as an effective way to promote PA in children and adolescents. They also perceived several benefits of using electronic devices, such as health promotion, increased awareness and motivation, and socialization, as well as barriers, facilitators, and age differences. The results of this study could provide researchers with insights into designing more effective, age-appropriate PA electronic devices for children and adolescents and improving adherence to their use. Trial Registration: PROSPERO CRD42021292340; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=292340 ", doi="10.2196/44753", url="https://mhealth.jmir.org/2023/1/e44753", url="http://www.ncbi.nlm.nih.gov/pubmed/37471127" } @Article{info:doi/10.2196/39929, author="Blakeslee, B. Sarah and Vieler, Kristin and Horak, Ingo and Stritter, Wiebke and Seifert, Georg", title="Planting Seeds for the Future: Scoping Review of Child Health Promotion Apps for Parents", journal="JMIR Mhealth Uhealth", year="2023", month="Jul", day="20", volume="11", pages="e39929", keywords="scoping review", keywords="child health promotion", keywords="parents", keywords="mobile apps", keywords="health apps", keywords="digital prevention", keywords="behavior change", keywords="mHealth", abstract="Background: Increasingly, parents use child health promotion apps to find health information. An overview of child health promotion apps for parents currently does not exist. The scope of child health topics addressed by parent apps is thus needed, including how they are evaluated. Objective: This scoping review aims to describe existing reported mobile health (mHealth) parent apps of middle- to high-income countries that promote child health. The focus centers on apps developed in the last 5 years, showing how the reported apps are evaluated, and listing reported outcomes found. Methods: A scoping review was conducted according to PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews) guidelines to identify parent apps or web-based programs on child health promotion published between January 2016 and June 2021 in 5 databases: PubMed, ERIC, IEEE Xplore, Web of Science, and Google Scholar. Separate sources were sought through an expert network. Included studies were summarized and analyzed through a systematic and descriptive content analysis, including keywords, year of publication, country of origin, aims/purpose, study population/sample size, intervention type, methodology/method(s), broad topic(s), evaluation, and study outcomes. Results: In total, 39 studies met the inclusion criteria from 1040 database and 60 expert-identified studies. Keywords reflected the health topics and app foci. About 64\% (25/39) of included studies were published after 2019 and most stemmed from the United States, Australian, and European-based research. Studies aimed to review or evaluate apps or conducted app-based study interventions. The number of participants ranged from 7 to 1200. Quantitative and qualitative methods were used. Interventions included 28 primary studies, 6 app feasibility studies, and 5 app or literature reviews. Eight separate topics were found: parental feeding and nutrition, physical activity, maternal-child health, parent-child health, healthy environment, dental health, mental health, and sleep. Study intervention evaluations cited behavior change theories in 26 studies and evaluations were carried out with a variety of topic-specific, adapted, self-developed, or validated questionnaires and evaluation tools. To evaluate apps, user input and qualitative evaluations were often combined with surveys and frequently rated with the Mobile App Rating Scale. Outcomes reported some positive effects, while several intervention studies saw no effect at all. Effectively evaluating changes in behavior through apps, recruiting target groups, and retaining app engagement were challenges cited. Conclusions: New parents are a key target group for child health apps, but evaluating child health promotion apps remains a challenge. Whether tailored to parent needs or adapted to the specific topic, apps should be rooted in a transparent theoretical groundwork. Applicable lessons for parent apps from existing research are to tailor app content, include intuitive and adaptive features, and embed well-founded parameters for long-term effect evaluation on child health promotion. ", doi="10.2196/39929", url="https://mhealth.jmir.org/2023/1/e39929", url="http://www.ncbi.nlm.nih.gov/pubmed/37471125" } @Article{info:doi/10.2196/44929, author="Woodley, J. Stephanie and Moller, Brittany and Clark, R. Alys and Bussey, D. Melanie and Sangelaji, Bahram and Perry, Meredith and Kruger, Jennifer", title="Digital Technologies for Women's Pelvic Floor Muscle Training to Manage Urinary Incontinence Across Their Life Course: Scoping Review", journal="JMIR Mhealth Uhealth", year="2023", month="Jul", day="5", volume="11", pages="e44929", keywords="apps", keywords="culture", keywords="life course", keywords="mobile health", keywords="mHealth", keywords="pelvic floor muscle training", keywords="urinary incontinence", keywords="women's health", keywords="mobile phone", abstract="Background: Women with urinary incontinence (UI) may consider using digital technologies (DTs) to guide pelvic floor muscle training (PFMT) to help manage their symptoms. DTs that deliver PFMT programs are readily available, yet uncertainty exists regarding whether they are scientifically valid, appropriate, and culturally relevant and meet the needs of women at specific life stages. Objective: This scoping review aims to provide a narrative synthesis of DTs used for PFMT to manage UI in women across their life course. Methods: This scoping review was conducted in accordance with the Joanna Briggs Institute methodological framework. A systematic search of 7 electronic databases was conducted, and primary quantitative and qualitative research and gray literature publications were considered. Studies were eligible if they focused on women with or without UI who had engaged with DTs for PFMT, reported on outcomes related to the use of PFMT DTs for managing UI, or explored users' experiences of DTs for PFMT. The identified studies were screened for eligibility. Data on the evidence base for and features of PFMT DTs using the Consensus on Exercise Reporting Template for PFMT, PFMT DT outcomes (eg, UI symptoms, quality of life, adherence, and satisfaction), life stage and culture, and the experiences of women and health care providers (facilitators and barriers) were extracted and synthesized by ?2 independent reviewers. Results: In total, 89 papers were included (n=45, 51\% primary and n=44, 49\% supplementary) involving studies from 14 countries. A total of 28 types of DTs were used in 41 primary studies, including mobile apps with or without a portable vaginal biofeedback or accelerometer-based device, a smartphone messaging system, internet-based programs, and videoconferencing. Approximately half (22/41, 54\%) of the studies provided evidence for or testing of the DTs, and a similar proportion of PFMT programs were drawn from or adapted from a known evidence base. Although PFMT parameters and program compliance varied, most studies that reported on UI symptoms showed improved outcomes, and women were generally satisfied with this treatment approach. With respect to life stage, pregnancy and the postpartum period were the most common focus, with more evidence needed for women of various age ranges (eg, adolescent and older women), including their cultural context, which is a factor that is rarely considered. Women's perceptions and experiences are often considered in the development of DTs, with qualitative data highlighting factors that are usually both facilitators and barriers. Conclusions: DTs are a growing mechanism for delivering PFMT, as evidenced by the recent increase in publications. This review highlighted the heterogeneity in types of DTs, PFMT protocols, the lack of cultural adaptations of most of the DTs reviewed, and a paucity in the consideration of the changing needs of women across their life course. ", doi="10.2196/44929", url="https://mhealth.jmir.org/2023/1/e44929", url="http://www.ncbi.nlm.nih.gov/pubmed/37405818" } @Article{info:doi/10.2196/42750, author="Hoang, Huyen Nhung and Liang, Zilu", title="Knowledge Discovery in Ubiquitous and Personal Sleep Tracking: Scoping Review", journal="JMIR Mhealth Uhealth", year="2023", month="Jun", day="28", volume="11", pages="e42750", keywords="sleep tracking", keywords="knowledge discovery", keywords="data mining", keywords="personal informatics", keywords="self-experimentation", keywords="sleep health", keywords="scoping review", keywords="mobile phone", abstract="Background: Over the past few decades, there has been a rapid increase in the number of wearable sleep trackers and mobile apps in the consumer market. Consumer sleep tracking technologies allow users to track sleep quality in naturalistic environments. In addition to tracking sleep per se, some sleep tracking technologies also support users in collecting information on their daily habits and sleep environments and reflecting on how those factors may contribute to sleep quality. However, the relationship between sleep and contextual factors may be too complex to be identified through visual inspection and reflection. Advanced analytical methods are needed to discover new insights into the rapidly growing volume of personal sleep tracking data. Objective: This review aimed to summarize and analyze the existing literature that applies formal analytical methods to discover insights in the context of personal informatics. Guided by the problem-constraints-system framework for literature review in computer science, we framed 4 main questions regarding general research trends, sleep quality metrics, contextual factors considered, knowledge discovery methods, significant findings, challenges, and opportunities of the interested topic. Methods: Web of Science, Scopus, ACM Digital Library, IEEE Xplore, ScienceDirect, Springer, Fitbit Research Library, and Fitabase were searched to identify publications that met the inclusion criteria. After full-text screening, 14 publications were included. Results: The research on knowledge discovery in sleep tracking is limited. More than half of the studies (8/14, 57\%) were conducted in the United States, followed by Japan (3/14, 21\%). Only a few of the publications (5/14, 36\%) were journal articles, whereas the remaining were conference proceeding papers. The most used sleep metrics were subjective sleep quality (4/14, 29\%), sleep efficiency (4/14, 29\%), sleep onset latency (4/14, 29\%), and time at lights off (3/14, 21\%). Ratio parameters such as deep sleep ratio and rapid eye movement ratio were not used in any of the reviewed studies. A dominant number of the studies applied simple correlation analysis (3/14, 21\%), regression analysis (3/14, 21\%), and statistical tests or inferences (3/14, 21\%) to discover the links between sleep and other aspects of life. Only a few studies used machine learning and data mining for sleep quality prediction (1/14, 7\%) or anomaly detection (2/14, 14\%). Exercise, digital device use, caffeine and alcohol consumption, places visited before sleep, and sleep environments were important contextual factors substantially correlated to various dimensions of sleep quality. Conclusions: This scoping review shows that knowledge discovery methods have great potential for extracting hidden insights from a flux of self-tracking data and are considered more effective than simple visual inspection. Future research should address the challenges related to collecting high-quality data, extracting hidden knowledge from data while accommodating within-individual and between-individual variations, and translating the discovered knowledge into actionable insights. ", doi="10.2196/42750", url="https://mhealth.jmir.org/2023/1/e42750", url="http://www.ncbi.nlm.nih.gov/pubmed/37379057" } @Article{info:doi/10.2196/45162, author="Goodman, Andrew and Mahoney, Ray and Spurling, Geoffrey and Lawler, Sheleigh", title="Influencing Factors to mHealth Uptake With Indigenous Populations: Qualitative Systematic Review", journal="JMIR Mhealth Uhealth", year="2023", month="Jun", day="23", volume="11", pages="e45162", keywords="mHealth", keywords="Indigenous", keywords="Canada", keywords="Australia", keywords="New Zealand", keywords="United States", keywords="Papua New Guinea", keywords="Samoa", keywords="qualitative", keywords="systematic review", keywords="feasibility", keywords="acceptability", keywords="users", keywords="design", keywords="workflow", abstract="Background: The advancements and abundance of mobile phones and portable health devices have created an opportunity to use mobile health (mHealth) for population health systems. There is increasing evidence for the feasibility and acceptance of mHealth with Indigenous populations. Providing a synthesis of qualitative findings of mHealth with Indigenous populations will gain insights into the strengths and challenges to mHealth use in Indigenous populations. Objective: This review aimed to identify and synthesize qualitative data pertaining to the experiences and perceptions of mHealth from the perspectives of end users (patients and service providers) living in the colonial settler democracies of Canada, Australia, New Zealand, the United States, the Pacific Islands, and the S{\'a}pmi region of northern Europe. Methods: In May 2021, systematic searches of peer-reviewed, scientific papers were conducted across the 5 databases of PubMed, CINAHL, Embase, PsycINFO, and Web of Science. Qualitative or mixed method studies were included where a mHealth intervention was the primary focus for responding to health challenges with Indigenous populations. Two authors independently screened papers for eligibility and assessed the risk of bias using a modified version of the Critical Appraisal Skills Programme. A meta-aggregative approach was used to analyze the findings of included studies. Results: Seventeen papers met the eligibility criteria, 8 studies with patients, 7 studies with service providers, and 2 studies that included both patients and service providers. Studies were conducted in Australia (n=10), Canada (n=2), New Zealand (n=2), Papua New Guinea (n=1), the United States (n=1), and Samoa (n=1). Our interpretation of these qualitative findings shows commonalities between Indigenous patients' and service providers' perceptions of mHealth. We summarize our findings in six themes: (1) mHealth literacy, (2) mHealth as a facilitator for connection and support, (3) mHealth content needed to be culturally relevant, (4) mHealth security and confidentiality, (5) mHealth supporting rather than replacing service providers, and (6) workplace and organizational capacity. Conclusions: This research suggests that mHealth can meet the needs of both patients and service providers when the mHealth intervention is culturally relevant, accounts for digital and health literacy, incorporates interactive components, is supported by workplaces, fits into health provider workflows, and meets security and confidentiality standards. Future mHealth research with Indigenous populations should partner with key representatives (eg, patients, service providers, and executive leaders) in the mHealth design appropriate to the purpose, people, setting, and delivery. ", doi="10.2196/45162", url="https://mhealth.jmir.org/2023/1/e45162", url="http://www.ncbi.nlm.nih.gov/pubmed/37351947" } @Article{info:doi/10.2196/44951, author="Ding, Xiaoxu and Wuerth, Kelli and Sakakibara, Brodie and Schmidt, Julia and Parde, Natalie and Holsti, Liisa and Barbic, Skye", title="Understanding Mobile Health and Youth Mental Health: Scoping Review", journal="JMIR Mhealth Uhealth", year="2023", month="Jun", day="16", volume="11", pages="e44951", keywords="adolescent", keywords="COVID-19", keywords="engagement", keywords="health outcome", keywords="illness", keywords="implementation", keywords="mental disorder", keywords="mental health", keywords="mHealth intervention", keywords="mHealth tools", keywords="mHealth", keywords="policy", keywords="scoping review", keywords="young adult", keywords="youth", abstract="Background: A total of 75\% of people with mental health disorders have an onset of illness between the ages of 12 and 24 years. Many in this age group report substantial obstacles to receiving quality youth-centered mental health care services. With the rapid development of technology and the recent COVID-19 pandemic, mobile health (mHealth) has presented new opportunities for youth mental health research, practice, and policy. Objective: The research objectives were to (1) synthesize the current evidence supporting mHealth interventions for youths who experience mental health challenges and (2) identify current gaps in the mHealth field related to youth's access to mental health services and health outcomes. Methods: Guided by the methods of Arksey and O'Malley, we conducted a scoping review of peer-reviewed studies that used mHealth tools to improve youth mental health (January 2016-February 2022). We searched MEDLINE, PubMed, PsycINFO, and Embase databases using the following key terms: (1) mHealth; (2) youth and young adults; and (3) mental health. The current gaps were analyzed using content analysis. Results: The search produced 4270 records, of which 151 met inclusion criteria. Included articles highlight the comprehensive aspects of youth mHealth intervention resource allocation for targeted conditions, mHealth delivery methods, measurement tools, evaluation of mHealth intervention, and youth engagement. The median age for participants in all studies is 17 (IQR 14-21) years. Only 3 (2\%) studies involved participants who reported their sex or gender outside of the binary option. Many studies (68/151, 45\%) were published after the onset of the COVID-19 outbreak. Study types and designs varied, with 60 (40\%) identified as randomized controlled trials. Notably, 143 out of 151 (95\%) studies came from developed countries, suggesting an evidence shortfall on the feasibility of implementing mHealth services in lower-resourced settings. Additionally, the results highlight concerns related to inadequate resources devoted to self-harm and substance uses, weak study design, expert engagement, and the variety of outcome measures selected to capture impact or changes over time. There is also a lack of standardized regulations and guidelines for researching mHealth technologies for youths and the use of non--youth-centered approaches to implementing results. Conclusions: This study may be used to inform future work as well as the development of youth-centered mHealth tools that can be implemented and sustained over time for diverse types of youths. Implementation science research that prioritizes youths' engagement is needed to advance the current understanding of mHealth implementation. Moreover, core outcome sets may support a youth-centered measurement strategy to capture outcomes in a systematic way that prioritizes equity, diversity, inclusion, and robust measurement science. Finally, this study suggests that future practice and policy research are needed to ensure the risk of mHealth is minimized and that this innovative health care service is meeting the emerging needs of youths over time. ", doi="10.2196/44951", url="https://mhealth.jmir.org/2023/1/e44951", url="http://www.ncbi.nlm.nih.gov/pubmed/37220197" } @Article{info:doi/10.2196/39649, author="Lyzwinski, Nathalie Lynnette and Elgendi, Mohamed and Menon, Carlo", title="Conversational Agents and Avatars for Cardiometabolic Risk Factors and Lifestyle-Related Behaviors: Scoping Review", journal="JMIR Mhealth Uhealth", year="2023", month="May", day="25", volume="11", pages="e39649", keywords="chatbots", keywords="avatars", keywords="conversational coach", keywords="diet", keywords="physical activity", keywords="cardiovascular disease", keywords="hypertension", keywords="cardiometabolic", keywords="behavior change", keywords="hypertension diabetes", keywords="metabolic syndrome", keywords="mobile phone", abstract="Background: In recent years, there has been a rise in the use of conversational agents for lifestyle medicine, in particular for weight-related behaviors and cardiometabolic risk factors. Little is known about the effectiveness and acceptability of and engagement with conversational and virtual agents as well as the applicability of these agents for metabolic syndrome risk factors such as an unhealthy dietary intake, physical inactivity, diabetes, and hypertension. Objective: This review aimed to get a greater understanding of the virtual agents that have been developed for cardiometabolic risk factors and to review their effectiveness. Methods: A systematic review of PubMed and MEDLINE was conducted to review conversational agents for cardiometabolic risk factors, including chatbots and embodied avatars. Results: A total of 50 studies were identified. Overall, chatbots and avatars appear to have the potential to improve weight-related behaviors such as dietary intake and physical activity. There were limited studies on hypertension and diabetes. Patients seemed interested in using chatbots and avatars for modifying cardiometabolic risk factors, and adherence was acceptable across the studies, except for studies of virtual agents for diabetes. However, there is a need for randomized controlled trials to confirm this finding. As there were only a few clinical trials, more research is needed to confirm whether conversational coaches may assist with cardiovascular disease and diabetes, and physical activity. Conclusions: Conversational coaches may regulate cardiometabolic risk factors; however, quality trials are needed to expand the evidence base. A future chatbot could be tailored to metabolic syndrome specifically, targeting all the areas covered in the literature, which would be novel. ", doi="10.2196/39649", url="https://mhealth.jmir.org/2023/1/e39649", url="http://www.ncbi.nlm.nih.gov/pubmed/37227765" } @Article{info:doi/10.2196/44685, author="Leong, Utek and Chakraborty, Bibhas", title="Participant Engagement in Microrandomized Trials of mHealth Interventions: Scoping Review", journal="JMIR Mhealth Uhealth", year="2023", month="May", day="22", volume="11", pages="e44685", keywords="microrandomized trials", keywords="engagement", keywords="adherence", keywords="mobile health", keywords="mHealth interventions", keywords="mobile phone", abstract="Background: Microrandomized trials (MRTs) have emerged as the gold standard for the development and evaluation of multicomponent, adaptive mobile health (mHealth) interventions. However, not much is known about the state of participant engagement measurement in MRTs of mHealth interventions. Objective: In this scoping review, we aimed to quantify the proportion of existing or planned MRTs of mHealth interventions to date that have assessed (or have planned to assess) engagement. In addition, for the trials that have explicitly assessed (or have planned to assess) engagement, we aimed to investigate how engagement has been operationalized and to identify the factors that have been studied as determinants of engagement in MRTs of mHealth interventions. Methods: We conducted a broad search for MRTs of mHealth interventions in 5 databases and manually searched preprint servers and trial registries. Study characteristics of each included evidence source were extracted. We coded and categorized these data to identify how engagement has been operationalized and which determinants, moderators, and covariates have been assessed in existing MRTs. Results: Our database and manual search yielded 22 eligible evidence sources. Most of these studies (14/22, 64\%) were designed to evaluate the effects of intervention components. The median sample size of the included MRTs was 110.5. At least 1 explicit measure of engagement was included in 91\% (20/22) of the included MRTs. We found that objective measures such as system usage data (16/20, 80\%) and sensor data (7/20, 35\%) are the most common methods of measuring engagement. All studies included at least 1 measure of the physical facet of engagement, but the affective and cognitive facets of engagement have largely been neglected (only measured by 1 study each). Most studies measured engagement with the mHealth intervention (Little e) and not with the health behavior of interest (Big E). Only 6 (30\%) of the 20 studies that measured engagement assessed the determinants of engagement in MRTs of mHealth interventions; notification-related variables were the most common determinants of engagement assessed (4/6, 67\% studies). Of the 6 studies, 3 (50\%) examined the moderators of participant engagement---2 studies investigated time-related moderators exclusively, and 1 study planned to investigate a comprehensive set of physiological and psychosocial moderators in addition to time-related moderators. Conclusions: Although the measurement of participant engagement in MRTs of mHealth interventions is prevalent, there is a need for future trials to diversify the measurement of engagement. There is also a need for researchers to address the lack of attention to how engagement is determined and moderated. We hope that by mapping the state of engagement measurement in existing MRTs of mHealth interventions, this review will encourage researchers to pay more attention to these issues when planning for engagement measurement in future trials. ", doi="10.2196/44685", url="https://mhealth.jmir.org/2023/1/e44685", url="http://www.ncbi.nlm.nih.gov/pubmed/37213178" } @Article{info:doi/10.2196/37742, author="Martin-Moratinos, Marina and Bella-Fern{\'a}ndez, Marcos and Blasco-Fontecilla, Hilario", title="Effects of Music on Attention-Deficit/Hyperactivity Disorder (ADHD) and Potential Application in Serious Video Games: Systematic Review", journal="J Med Internet Res", year="2023", month="May", day="12", volume="25", pages="e37742", keywords="attention-deficit/hyperactivity disorder", keywords="music therapy", keywords="music", keywords="video games", keywords="rhythm", keywords="timing deficits", abstract="Background: Attention-deficit/hyperactivity disorder (ADHD) has a considerable impact on an individual's daily life. Some difficulties with timing deficits may be associated with deficiencies in attention, reading, language skills, or executive function. Music therapy, either active (playing an instrument) or passive (listening to music) has demonstrated its efficacy in reducing symptomatology in many disorders. Video games may prove to be a useful assessment and treatment tool in compensating for the difficulties with multimodal treatment in ADHD. Objective: The aim of the study is to (1) analyze the evidence that music is beneficial in reducing the symptomatology of ADHD using systematic review and (2) propose the application of music in video games following music therapy strategies. Methods: Searches were conducted in PubMed, Embase, PsycINFO, Cochrane, and gray literature (Google Scholar and WorldCat). We used the following search syntax: ((music[Title/Abstract]) or (music therapy[Title/Abstract])) and (attention deficit disorder[MeSH or thesaurus term]). Results: Of the 70 records identified, 17 provided findings that music can be beneficial in various domains of ADHD. Active music therapy improves hemispheric synchrony, social skills, aggressivity, and impulsivity. Passive music therapy improves academic skills like arithmetic, drawing, and reading comprehension, as well as attention and disruptive behaviors. The effects depend on the music genre, tempo, or task difficulty. Music in video games was generally found to be beneficial for people with ADHD. Music improves immersion and flow while playing video games. Using rhythm may also improve timing skills and immersion in patients with ADHD. Regarding the proposed application of aspects of music to therapeutic video games for ADHD, some paradigms in timing and music therapy were considered in the proposed design of video games. Conclusions: Improving ADHD treatment through the application of music in video games is proposed. Trial Registration: PROSPERO CRD42021288226; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=288226 ", doi="10.2196/37742", url="https://www.jmir.org/2023/1/e37742", url="http://www.ncbi.nlm.nih.gov/pubmed/37171837" } @Article{info:doi/10.2196/43162, author="Stecher, Chad and Pfisterer, Bjorn and Harden, M. Samantha and Epstein, Dana and Hirschmann, M. Jakob and Wunsch, Kathrin and Buman, P. Matthew", title="Assessing the Pragmatic Nature of Mobile Health Interventions Promoting Physical Activity: Systematic Review and Meta-analysis", journal="JMIR Mhealth Uhealth", year="2023", month="May", day="4", volume="11", pages="e43162", keywords="physical activity", keywords="mobile health", keywords="mHealth", keywords="Reach, Effectiveness, Adoption, Implementation, Maintenance", keywords="RE-AIM", keywords="Pragmatic-Explanatory Continuum Indicator Summary-2", keywords="PRECIS-2", keywords="systematic review", keywords="meta-analysis", keywords="digital health", keywords="mobile phone", abstract="Background: Mobile health (mHealth) apps can promote physical activity; however, the pragmatic nature (ie, how well research translates into real-world settings) of these studies is unknown. The impact of study design choices, for example, intervention duration, on intervention effect sizes is also understudied. Objective: This review and meta-analysis aims to describe the pragmatic nature of recent mHealth interventions for promoting physical activity and examine the associations between study effect size and pragmatic study design choices. Methods: The PubMed, Scopus, Web of Science, and PsycINFO databases were searched until April 2020. Studies were eligible if they incorporated apps as the primary intervention, were conducted in health promotion or preventive care settings, included a device-based physical activity outcome, and used randomized study designs. Studies were assessed using the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) and Pragmatic-Explanatory Continuum Indicator Summary-2 (PRECIS-2) frameworks. Study effect sizes were summarized using random effect models, and meta-regression was used to examine treatment effect heterogeneity by study characteristics. Results: Overall, 3555 participants were included across 22 interventions, with sample sizes ranging from 27 to 833 (mean 161.6, SD 193.9, median 93) participants. The study populations' mean age ranged from 10.6 to 61.5 (mean 39.6, SD 6.5) years, and the proportion of males included across all studies was 42.8\% (1521/3555). Additionally, intervention lengths varied from 2 weeks to 6 months (mean 60.9, SD 34.9 days). The primary app- or device-based physical activity outcome differed among interventions: most interventions (17/22, 77\%) used activity monitors or fitness trackers, whereas the rest (5/22, 23\%) used app-based accelerometry measures. Data reporting across the RE-AIM framework was low (5.64/31, 18\%) and varied within specific dimensions (Reach=44\%; Effectiveness=52\%; Adoption=3\%; Implementation=10\%; Maintenance=12.4\%). PRECIS-2 results indicated that most study designs (14/22, 63\%) were equally explanatory and pragmatic, with an overall PRECIS-2 score across all interventions of 2.93/5 (SD 0.54). The most pragmatic dimension was flexibility (adherence), with an average score of 3.73 (SD 0.92), whereas follow-up, organization, and flexibility (delivery) appeared more explanatory with means of 2.18 (SD 0.75), 2.36 (SD 1.07), and 2.41 (SD 0.72), respectively. An overall positive treatment effect was observed (Cohen d=0.29, 95\% CI 0.13-0.46). Meta-regression analyses revealed that more pragmatic studies (?0.81, 95\% CI ?1.36 to ?0.25) were associated with smaller increases in physical activity. Treatment effect sizes were homogenous across study duration, participants' age and gender, and RE-AIM scores. Conclusions: App-based mHealth physical activity studies continue to underreport several key study characteristics and have limited pragmatic use and generalizability. In addition, more pragmatic interventions observe smaller treatment effects, whereas study duration appears to be unrelated to the effect size. Future app-based studies should more comprehensively report real-world applicability, and more pragmatic approaches are needed for maximal population health impacts. Trial Registration: PROSPERO CRD42020169102; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=169102 ", doi="10.2196/43162", url="https://mhealth.jmir.org/2023/1/e43162", url="http://www.ncbi.nlm.nih.gov/pubmed/37140972" } @Article{info:doi/10.2196/42679, author="Bernard, M. Renaldo and Seijas, Vanessa and Davis, Micheal and Volkova, Anel and Diviani, Nicola and L{\"u}scher, Janina and Sabariego, Carla", title="Mobile Health Self-management Support for Spinal Cord Injury: Systematic Literature Review", journal="JMIR Mhealth Uhealth", year="2023", month="Apr", day="26", volume="11", pages="e42679", keywords="mobile phone", keywords="mobile health", keywords="mHealth", keywords="eHealth", keywords="telemedicine", keywords="telehealth", keywords="spinal cord injury", keywords="self-management", keywords="internet-based intervention", keywords="World Wide Web", keywords="systematic review", abstract="Background: Self-management plays a critical role in maintaining and improving the health of persons with spinal cord injury (SCI). Despite their potential, existing mobile health (mHealth) self-management support (SMS) tools for SCI have not been comprehensively described in terms of their characteristics and approaches. It is important to have an overview of these tools to know how best to select, further develop, and improve them. Objective: The objective of this systematic literature review was to identify mHealth SMS tools for SCI and summarize their characteristics and approaches to offering SMS. Methods: A systematic review of the literature published between January 2010 and March 2022 was conducted across 8 bibliographic databases. The data synthesis was guided by the self-management task taxonomy by Corbin and Strauss, the self-management skill taxonomy by Lorig and Holman, and the Practical Reviews in Self-Management Support taxonomy. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) standards guided the reporting. Results: A total of 24 publications reporting on 19 mHealth SMS tools for SCI were included. These tools were introduced from 2015 onward and used various mHealth technologies and multimedia formats to provide SMS using 9 methods identified by the Practical Reviews in Self-Management Support taxonomy (eg, social support and lifestyle advice and support). The identified tools focused on common SCI self-management areas (eg, bowel, bladder, and pain management) and overlooked areas such as sexual dysfunction problems and environmental problems, including barriers in the built environment. Most tools (12/19, 63\%) unexpectedly supported a single self-management task instead of all 3 tasks (ie, medical, role, and emotional management), and emotional management tasks had very little support. All self-management skills (eg, problem-solving, decision-making, and action planning) had coverage, but a single tool addressed resource use. The identified mHealth SMS tools were similar in terms of number, introduction period, geographical distribution, and technical sophistication compared with SMS tools for other chronic conditions. Conclusions: This systematic literature review provides one of the first descriptions of mHealth SMS tools for SCI in terms of their characteristics and approaches to offering SMS. This study's findings highlight a need for increased coverage of key SMS for SCI components; adopting comparable usability, user experience, and accessibility evaluation methods; and related research to provide more detailed reporting. Future research should consider other data sources such as app stores and technology-centric bibliographic databases to complement this compilation by identifying other possibly overlooked mHealth SMS tools. A consideration of this study's findings is expected to support the selection, development, and improvement of mHealth SMS tools for SCI. ", doi="10.2196/42679", url="https://mhealth.jmir.org/2023/1/e42679", url="http://www.ncbi.nlm.nih.gov/pubmed/37099372" } @Article{info:doi/10.2196/45464, author="Dinh, Alana and Yin, Lukas Andrew and Estrin, Deborah and Greenwald, Peter and Fortenko, Alexander", title="Augmented Reality in Real-time Telemedicine and Telementoring: Scoping Review", journal="JMIR Mhealth Uhealth", year="2023", month="Apr", day="18", volume="11", pages="e45464", keywords="augmented reality", keywords="telemedicine", keywords="telehealth", keywords="telementoring", keywords="teleguidance", keywords="telecommunication", keywords="teleconsultation", keywords="telecollaboration", keywords="scoping review", keywords="mobile phone", abstract="Background: Over the last decade, augmented reality (AR) has emerged in health care as a tool for visualizing data and enhancing simulation learning. AR, which has largely been explored for communication and collaboration in nonhealth contexts, could play a role in shaping future remote medical services and training. This review summarized existing studies implementing AR in real-time telemedicine and telementoring to create a foundation for health care providers and technology developers to understand future opportunities in remote care and education. Objective: This review described devices and platforms that use AR for real-time telemedicine and telementoring, the tasks for which AR was implemented, and the ways in which these implementations were evaluated to identify gaps in research that provide opportunities for further study. Methods: We searched PubMed, Scopus, Embase, and MEDLINE to identify English-language studies published between January 1, 2012, and October 18, 2022, implementing AR technology in a real-time interaction related to telemedicine or telementoring. The search terms were ``augmented reality'' OR ``AR'' AND ``remote'' OR ``telemedicine'' OR ``telehealth'' OR ``telementoring.'' Systematic reviews, meta-analyses, and discussion-based articles were excluded from analysis. Results: A total of 39 articles met the inclusion criteria and were categorized into themes of patient evaluation, medical intervention, and education. In total, 20 devices and platforms using AR were identified, with common features being the ability for remote users to annotate, display graphics, and display their hands or tools in the local user's view. Common themes across the studies included consultation and procedural education, with surgery, emergency, and hospital medicine being the most represented specialties. Outcomes were most often measured using feedback surveys and interviews. The most common objective measures were time to task completion and performance. Long-term outcome and resource cost measurements were rare. Across the studies, user feedback was consistently positive for perceived efficacy, feasibility, and acceptability. Comparative trials demonstrated that AR-assisted conditions had noninferior reliability and performance and did not consistently extend procedure times compared with in-person controls. Conclusions: Studies implementing AR in telemedicine and telementoring demonstrated the technology's ability to enhance access to information and facilitate guidance in multiple health care settings. However, AR's role as an alternative to current telecommunication platforms or even in-person interactions remains to be validated, with many disciplines and provider-to-nonprovider uses still lacking robust investigation. Additional studies comparing existing methods may offer more insight into this intersection, but the early stage of technical development and the lack of standardized tools and adoption have hindered the conduct of larger longitudinal and randomized controlled trials. Overall, AR has the potential to complement and advance the capabilities of remote medical care and learning, creating unique opportunities for innovator, provider, and patient involvement. ", doi="10.2196/45464", url="https://mhealth.jmir.org/2023/1/e45464", url="http://www.ncbi.nlm.nih.gov/pubmed/37071458" } @Article{info:doi/10.2196/37347, author="Morita, P. Plinio and Sahu, Sundar Kirti and Oetomo, Arlene", title="Health Monitoring Using Smart Home Technologies: Scoping Review", journal="JMIR Mhealth Uhealth", year="2023", month="Apr", day="13", volume="11", pages="e37347", keywords="monitor", keywords="smart home", keywords="ambient assisted living", keywords="active assisted living", keywords="AAL", keywords="assisted living", keywords="review", keywords="internet of things", keywords="aging", keywords="gerontology", keywords="elder", keywords="older adult", keywords="older people", keywords="geriatric", keywords="digital health", keywords="eHealth", keywords="smart technology", keywords="older population", keywords="independent living", keywords="big data", keywords="machine learning", keywords="algorithm", keywords="deep learning", abstract="Background: The Internet of Things (IoT) has become integrated into everyday life, with devices becoming permanent fixtures in many homes. As countries face increasing pressure on their health care systems, smart home technologies have the potential to support population health through continuous behavioral monitoring. Objective: This scoping review aims to provide insight into this evolving field of research by surveying the current technologies and applications for in-home health monitoring. Methods: Peer-reviewed papers from 2008 to 2021 related to smart home technologies for health care were extracted from 4 databases (PubMed, Scopus, ScienceDirect, and CINAHL); 49 papers met the inclusion criteria and were analyzed. Results: Most of the studies were from Europe and North America. The largest proportion of the studies were proof of concept or pilot studies. Approximately 78\% (38/49) of the studies used real human participants, most of whom were older females. Demographic data were often missing. Nearly 60\% (29/49) of the studies reported on the health status of the participants. Results were primarily reported in engineering and technology journals. Almost 62\% (30/49) of the studies used passive infrared sensors to report on motion detection where data were primarily binary. There were numerous data analysis, management, and machine learning techniques employed. The primary challenges reported by authors were differentiating between multiple participants in a single space, technology interoperability, and data security and privacy. Conclusions: This scoping review synthesizes the current state of research on smart home technologies for health care. We were able to identify multiple trends and knowledge gaps---in particular, the lack of collaboration across disciplines. Technological development dominates over the human-centric part of the equation. During the preparation of this scoping review, we noted that the health care research papers lacked a concrete definition of a smart home, and based on the available evidence and the identified gaps, we propose a new definition for a smart home for health care. Smart home technology is growing rapidly, and interdisciplinary approaches will be needed to ensure integration into the health sector. ", doi="10.2196/37347", url="https://mhealth.jmir.org/2023/1/e37347", url="http://www.ncbi.nlm.nih.gov/pubmed/37052984" } @Article{info:doi/10.2196/44104, author="Bittel, M. Kelsey and O'Briant, Y. Kate and Ragaglia, M. Rena and Buseth, Lake and Murtha, Courtney and Yu, Jessica and Stanely, M. Jennifer and Hudgins, L. Brynn and Hevel, J. Derek and Maher, P. Jaclyn", title="Associations Between Social Cognitive Determinants and Movement-Related Behaviors in Studies Using Ecological Momentary Assessment Methods: Systematic Review", journal="JMIR Mhealth Uhealth", year="2023", month="Apr", day="7", volume="11", pages="e44104", keywords="motivation", keywords="psychosocial", keywords="physical activity", keywords="sedentary behavior", keywords="ambulatory assessment", keywords="mobile phone", abstract="Background: The social cognitive framework is a long-standing framework within physical activity promotion literature to explain and predict movement-related behaviors. However, applications of the social cognitive framework to explain and predict movement-related behaviors have typically examined the relationships between determinants and behavior across macrotimescales (eg, weeks and months). There is more recent evidence suggesting that movement-related behaviors and their social cognitive determinants (eg, self-efficacy and intentions) change across microtimescales (eg, hours and days). Therefore, efforts have been devoted to examining the relationship between social cognitive determinants and movement-related behaviors across microtimescales. Ecological momentary assessment (EMA) is a growing methodology that can capture movement-related behaviors and social cognitive determinants as they change across microtimescales. Objective: The objective of this systematic review was to summarize evidence from EMA studies examining associations between social cognitive determinants and movement-related behaviors (ie, physical activity and sedentary behavior). Methods: Studies were included if they quantitatively tested such an association at the momentary or day level and excluded if they were an active intervention. Using keyword searches, articles were identified across the PubMed, SPORTDiscus, and PsycINFO databases. Articles were first assessed through abstract and title screening followed by full-text review. Each article was screened independently by 2 reviewers. For eligible articles, data regarding study design, associations between social cognitive determinants and movement-related behaviors, and study quality (ie, Methodological Quality Questionnaire and Checklist for Reporting Ecological Momentary Assessment Studies) were extracted. At least 4 articles were required to draw a conclusion regarding the overall associations between a social cognitive determinant and movement-related behavior. For the social cognitive determinants in which a conclusion regarding an overall association could be drawn, 60\% of the articles needed to document a similar association (ie, positive, negative, or null) to conclude that the association existed in a particular direction. Results: A total of 24 articles including 1891 participants were eligible for the review. At the day level, intentions and self-efficacy were positively associated with physical activity. No other associations could be determined because of conflicting findings or the small number of studies investigating associations. Conclusions: Future research would benefit from validating EMA assessments of social cognitive determinants and systematically investigating associations across different operationalizations of key constructs. Despite the only recent emergence of EMA to understand social cognitive determinants of movement-related behaviors, the findings indicate that daily intentions and self-efficacy play an important role in regulating physical activity in everyday life. Trial Registration: PROSPERO CRD42022328500; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=328500 ", doi="10.2196/44104", url="https://mhealth.jmir.org/2023/1/e44104", url="http://www.ncbi.nlm.nih.gov/pubmed/37027185" } @Article{info:doi/10.2196/44765, author="Lee, Mauricette and Bin Mahmood, Shakran Abu Bakar and Lee, Sing Eng and Smith, Elizabeth Helen and Tudor Car, Lorainne", title="Smartphone and Mobile App Use Among Physicians in Clinical Practice: Scoping Review", journal="JMIR Mhealth Uhealth", year="2023", month="Mar", day="31", volume="11", pages="e44765", keywords="evidence-based medicine", keywords="specialist", keywords="general practitioners", keywords="GP", keywords="primary care physicians", keywords="mobile apps", keywords="consultants", keywords="surgeons", keywords="pediatricians", keywords="clinical care", keywords="mobile phone", abstract="Background: Health care professionals are increasingly using smartphones in clinical care. Smartphone use can affect patient quality of care and clinical outcomes. Objective: This scoping review aimed to describe how physicians use smartphones and mobile apps in clinical settings. Methods: We conducted a scoping review using the Joanna Briggs Institute methodology and reported the results according to PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. We used the following databases in our literature search: MEDLINE, Embase, Cochrane Library, Web of Science, Google Scholar, and gray literature for studies published since 2010. An additional search was also performed by scanning the reference lists of included studies. A narrative synthesis approach was used. Results: A total of 10 studies, published between 2016 and 2021, were included in this review. Of these studies, 8 used surveys and 2 used surveys with focus group study designs to explore smartphone use, its adoption, experience of using it, and views on the use of smartphones among physicians. There were studies with only general practitioners (n=3), studies with only specialists (n=3), and studies with both general practitioners and specialists (n=4). Physicians use smartphones and mobile apps for communication (n=9), clinical decision-making (n=7), drug compendium (n=7), medical education and training (n=7), maintaining health records (n=4), managing time (n=4), and monitoring patients (n=2) in clinical practice. The Medscape medical app was frequently used for information gathering. WhatsApp, a nonmedical app, was commonly used for physician-patient communication. The commonly reported barriers were lack of regulatory oversight, privacy concerns, and limited Wi-Fi or internet access. The commonly reported facilitator was convenience and having access to evidence-based medicine, clinical decision-making support, and a wide array of apps. Conclusions: Smartphones and mobile apps were used for communication, medical education and training, clinical decision-making, and drug compendia in most studies. Although the benefits of smartphones and mobile apps for physicians at work were promising, there were concerns about patient privacy and confidentiality. Legislation is urgently needed to protect the liability of health care professionals using smartphones. ", doi="10.2196/44765", url="https://mhealth.jmir.org/2023/1/e44765", url="http://www.ncbi.nlm.nih.gov/pubmed/37000498" } @Article{info:doi/10.2196/42461, author="Nasruddin, Nasriah Nur Izzatun and Murphy, Joey and Armstrong, Glynis Miranda Elaine", title="Physical Activity Surveillance in Children and Adolescents Using Smartphone Technology: Systematic Review", journal="JMIR Pediatr Parent", year="2023", month="Mar", day="29", volume="6", pages="e42461", keywords="physical activity", keywords="surveillance", keywords="children", keywords="adolescents", keywords="smartphone technology", keywords="smartphone apps", keywords="smartphone", keywords="technology", keywords="application", keywords="database", keywords="mobile phone", abstract="Background: Self-reported physical activity (PA) questionnaires have traditionally been used for PA surveillance in children and adolescents, especially in free-living conditions. Objective measures are more accurate at measuring PA, but high cost often creates a barrier for their use in low- and middle-income settings. The advent of smartphone technology has greatly influenced mobile health and has offered new opportunities in health research, including PA surveillance. Objective: This review aimed to systematically explore the use of smartphone technology for PA surveillance in children and adolescents, specifically focusing on the use of smartphone apps. Methods: A literature search was conducted using 5 databases (PubMed, Scopus, CINAHL, MEDLINE, and Web of Science) and Google Scholar to identify articles relevant to the topic that were published from 2008 to 2023. Articles were included if they included children and adolescents within the age range of 5 to 18 years; used smartphone technology as PA surveillance; had PA behavioral outcomes such as energy expenditure, step count, and PA levels; were written in English; and were published between 2008 and 2023. Results: We identified and analyzed 8 studies (5 cross-sectional studies and 3 cohort studies). All participants were aged 12-18 years, and all studies were conducted in high-income countries only. Participants were recruited from schools, primary care facilities, and voluntarily. Five studies used mobile apps specifically and purposely developed for the study, whereas 3 studies used mobile apps downloadable from the Apple App Store and Android Play Store. PA surveillance using these apps was conducted from 24 hours to 4 weeks. Conclusions: Evidence of PA surveillance using smartphone technology in children and adolescents was insufficient, which demonstrated the knowledge gap. Additional research is needed to further study the feasibility and validity of smartphone apps for PA surveillance among children and adolescents, especially in low- and middle-income countries. ", doi="10.2196/42461", url="https://pediatrics.jmir.org/2023/1/e42461", url="http://www.ncbi.nlm.nih.gov/pubmed/36989033" } @Article{info:doi/10.2196/42389, author="Diez Alvarez, Sergio and Fellas, Antoni and Santos, Derek and Sculley, Dean and Wynne, Katie and Acharya, Shamasunder and Navathe, Pooshan and Girones, Xavier and Coda, Andrea", title="The Clinical Impact of Flash Glucose Monitoring---a Digital Health App and Smartwatch Technology in Patients With Type 2 Diabetes: Scoping Review", journal="JMIR Diabetes", year="2023", month="Mar", day="15", volume="8", pages="e42389", keywords="type 2 diabetes", keywords="flash glucose monitoring", keywords="digital health", keywords="smartwatch", keywords="scoping review", keywords="app", keywords="smartphone", keywords="mobile phone", keywords="mHealth", keywords="digital", keywords="application", keywords="technology", keywords="effective", keywords="management", keywords="glucose", keywords="monitoring", keywords="database", keywords="wearable", keywords="diabetes", keywords="diabetic", keywords="glucose monitoring", abstract="Background: Type 2 diabetes has a growing prevalence and confers significant cost burden to the health care system, raising the urgent need for cost-effective and easily accessible solutions. The management of type 2 diabetes requires significant commitment from the patient, caregivers, and the treating team to optimize clinical outcomes and prevent complications. Technology and its implications for the management of type 2 diabetes is a nascent area of research. The impact of some of the more recent technological innovations in this space, such as continuous glucose monitoring, flash glucose monitoring, web-based applications, as well as smartphone- and smart watch--based interactive apps has received limited attention in the research literature. Objective: This scoping review aims to explore the literature available on type 2 diabetes, flash glucose monitoring, and digital health technology to improve diabetic clinical outcomes and inform future research in this area. Methods: A scoping review was undertaken by searching Ovid MEDLINE and CINAHL databases. A second search using all identified keywords and index terms was performed on Ovid MEDLINE (January 1966 to July 2021), EMBASE (January 1980 to July 2021), Cochrane Central Register of Controlled Trials (CENTRAL; the Cochrane Library, latest issue), CINAHL (from 1982), IEEE Xplore, ACM Digital Libraries, and Web of Science databases. Results: There were very few studies that have explored the use of mobile health and flash glucose monitoring in type 2 diabetes. These studies have explored somewhat disparate and limited areas of research, and there is a distinct lack of methodological rigor in this area of research. The 3 studies that met the inclusion criteria have addressed aspects of the proposed research question. Conclusions: This scoping review has highlighted the lack of research in this area, raising the opportunity for further research in this area, focusing on the clinical impact and feasibility of the use of multiple technologies, including flash glucose monitoring in the management of patients with type 2 diabetes. ", doi="10.2196/42389", url="https://diabetes.jmir.org/2023/1/e42389", url="http://www.ncbi.nlm.nih.gov/pubmed/36920464" } @Article{info:doi/10.2196/41153, author="Diaz, Claudio and Caillaud, Corinne and Yacef, Kalina", title="Mining Sensor Data to Assess Changes in Physical Activity Behaviors in Health Interventions: Systematic Review", journal="JMIR Med Inform", year="2023", month="Mar", day="6", volume="11", pages="e41153", keywords="activity tracker", keywords="wearable electronic devices", keywords="fitness trackers", keywords="data mining", keywords="artificial intelligence", keywords="health", keywords="education", keywords="behavior change", keywords="physical activity", keywords="wearable devices", keywords="trackers", keywords="health education", keywords="sensor data", abstract="Background: Sensors are increasingly used in health interventions to unobtrusively and continuously capture participants' physical activity in free-living conditions. The rich granularity of sensor data offers great potential for analyzing patterns and changes in physical activity behaviors. The use of specialized machine learning and data mining techniques to detect, extract, and analyze these patterns has increased, helping to better understand how participants' physical activity evolves. Objective: The aim of this systematic review was to identify and present the various data mining techniques employed to analyze changes in physical activity behaviors from sensors-derived data in health education and health promotion intervention studies. We addressed two main research questions: (1) What are the current techniques used for mining physical activity sensor data to detect behavior changes in health education or health promotion contexts? (2) What are the challenges and opportunities in mining physical activity sensor data for detecting physical activity behavior changes? Methods: The systematic review was performed in May 2021 using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We queried the Association for Computing Machinery (ACM), IEEE Xplore, ProQuest, Scopus, Web of Science, Education Resources Information Center (ERIC), and Springer literature databases for peer-reviewed references related to wearable machine learning to detect physical activity changes in health education. A total of 4388 references were initially retrieved from the databases. After removing duplicates and screening titles and abstracts, 285 references were subjected to full-text review, resulting in 19 articles included for analysis. Results: All studies used accelerometers, sometimes in combination with another sensor (37\%). Data were collected over a period ranging from 4 days to 1 year (median 10 weeks) from a cohort size ranging between 10 and 11615 (median 74). Data preprocessing was mainly carried out using proprietary software, generally resulting in step counts and time spent in physical activity aggregated predominantly at the daily or minute level. The main features used as input for the data mining models were descriptive statistics of the preprocessed data. The most common data mining methods were classifiers, clusters, and decision-making algorithms, and these focused on personalization (58\%) and analysis of physical activity behaviors (42\%). Conclusions: Mining sensor data offers great opportunities to analyze physical activity behavior changes, build models to better detect and interpret behavior changes, and allow for personalized feedback and support for participants, especially where larger sample sizes and longer recording times are available. Exploring different data aggregation levels can help detect subtle and sustained behavior changes. However, the literature suggests that there is still work remaining to improve the transparency, explicitness, and standardization of the data preprocessing and mining processes to establish best practices and make the detection methods easier to understand, scrutinize, and reproduce. ", doi="10.2196/41153", url="https://medinform.jmir.org/2023/1/e41153", url="http://www.ncbi.nlm.nih.gov/pubmed/36877559" } @Article{info:doi/10.2196/40898, author="Schwarz, Ayla and Winkens, H. Laura H. and de Vet, Emely and Ossendrijver, Dian and Bouwsema, Kirsten and Simons, Monique", title="Design Features Associated With Engagement in Mobile Health Physical Activity Interventions Among Youth: Systematic Review of Qualitative and Quantitative Studies", journal="JMIR Mhealth Uhealth", year="2023", month="Mar", day="6", volume="11", pages="e40898", keywords="systematic review", keywords="youth", keywords="physical activity", keywords="design features", keywords="engagement", keywords="mHealth", keywords="mobile health", keywords="mobile phone", abstract="Background: Globally, 81\% of youth do not meet the physical activity (PA) guidelines. Youth of families with a low socioeconomic position are less likely to meet the recommended PA guidelines. Mobile health (mHealth) interventions are preferred by youth over traditional in-person approaches and are in line with their media preferences. Despite the promise of mHealth interventions in promoting PA, a common challenge is to engage users in the long term or effectively. Earlier reviews highlighted the association of different design features (eg, notifications and rewards) with engagement among adults. However, little is known about which design features are important for increasing engagement among youth. Objective: To inform the design process of future mHealth tools, it is important to investigate the design features that can yield effective user engagement. This systematic review aimed to identify which design features are associated with engagement in mHealth PA interventions among youth who were aged between 4 and 18 years. Methods: A systematic search was conducted in EBSCOhost (MEDLINE, APA PsycINFO, and Psychology \& Behavioral Sciences Collection) and Scopus. Qualitative and quantitative studies were included if they documented design features associated with engagement. Design features and related behavior change techniques and engagement measures were extracted. Study quality was assessed according to the Mixed Method Assessment Tool, and one-third of all screening and data extraction were double coded by a second reviewer. Results: Studies (n=21) showed that various features were associated with engagement, such as a clear interface, rewards, multiplayer game mode, social interaction, variety of challenges with personalized difficulty level, self-monitoring, and variety of customization options among others, including self-set goals, personalized feedback, progress, and a narrative. In contrast, various features need to be carefully considered while designing mHealth PA interventions, such as sounds, competition, instructions, notifications, virtual maps, or self-monitoring, facilitated by manual input. In addition, technical functionality can be considered as a prerequisite for engagement. Research addressing youth from low socioeconomic position families is very limited with regard to engagement in mHealth apps. Conclusions: Mismatches between different design features in terms of target group, study design, and content translation from behavior change techniques to design features are highlighted and set up in a design guideline and future research agenda. Trial Registration: PROSPERO CRD42021254989; https://tinyurl.com/5n6ppz24 ", doi="10.2196/40898", url="https://mhealth.jmir.org/2023/1/e40898", url="http://www.ncbi.nlm.nih.gov/pubmed/36877551" } @Article{info:doi/10.2196/43561, author="Alkhaldi, Ohoud and McMillan, Brian and Maddah, Noha and Ainsworth, John", title="Interventions Aimed at Enhancing Health Care Providers' Behavior Toward the Prescription of Mobile Health Apps: Systematic Review", journal="JMIR Mhealth Uhealth", year="2023", month="Feb", day="27", volume="11", pages="e43561", keywords="mHealth", keywords="mobile apps", keywords="prescription", keywords="behavioral change", keywords="mobile phone", abstract="Background: Mobile health (mHealth) apps have great potential to support the management of chronic conditions. Despite widespread acceptance of mHealth apps by the public, health care providers (HCPs) are reluctant to prescribe or recommend such apps to their patients. Objective: This study aimed to classify and evaluate interventions aimed at encouraging HCPs to prescribe mHealth apps. Methods: A systematic literature search was conducted to identify studies published from January 1, 2008, to August 5, 2022, using 4 electronic databases: MEDLINE, Scopus, CINAHL, and PsycINFO. We included studies that evaluated interventions encouraging HCPs to prescribe mHealth apps. Two review authors independently assessed the eligibility of the studies. The ``National Institute of Health's quality assessment tool for before-and-after (pretest-posttest design) studies with no control group'' and ``the mixed methods appraisal tool (MMAT)'' were used to assess the methodological quality. Owing to high levels of heterogeneity between interventions, measures of practice change, specialties of HCPs, and modes of delivery, we conducted a qualitative analysis. We adopted the behavior change wheel as a framework for classifying the included interventions according to intervention functions. Results: In total, 11 studies were included in this review. Most of the studies reported positive findings, with improvements in a number of outcomes, including increased knowledge of mHealth apps among clinicians, improved self-efficacy or confidence in prescribing, and an increased number of mHealth app prescriptions. On the basis of the behavior change wheel, 9 studies reported elements of environmental restructuring such as providing HCPs with lists of apps, technological systems, time, and resources. Furthermore, 9 studies included elements of education, particularly workshops, class lectures, individual sessions with HCPs, videos, or toolkits. Furthermore, training was incorporated in 8 studies using case studies or scenarios or app appraisal tools. Coercion and restriction were not reported in any of the interventions included. The quality of the studies was high in relation to the clarity of aims, interventions, and outcomes but weaker in terms of sample size, power calculations, and duration of follow-up. Conclusions: This study identified interventions to encourage app prescriptions by HCPs. Recommendations for future research should consider previously unexplored intervention functions such as restrictions and coercion. The findings of this review can help inform mHealth providers and policy makers regarding the key intervention strategies impacting mHealth prescriptions and assist them in making informed decisions to encourage this adoption. ", doi="10.2196/43561", url="https://mhealth.jmir.org/2023/1/e43561", url="http://www.ncbi.nlm.nih.gov/pubmed/36848202" } @Article{info:doi/10.2196/42023, author="Greuel, Merlin and Sy, Frithjof and B{\"a}rnighausen, Till and Adam, Maya and Vandormael, Alain and Gates, Jennifer and Harling, Guy", title="Community Health Worker Use of Smart Devices for Health Promotion: Scoping Review", journal="JMIR Mhealth Uhealth", year="2023", month="Feb", day="22", volume="11", pages="e42023", keywords="mobile health", keywords="community health workers", keywords="smart phones", keywords="tablets", keywords="health promotion", keywords="public health", keywords="health worker", keywords="smart devices", keywords="health behaviour", keywords="smart technology", keywords="health message", keywords="health outcome", abstract="Background: Community health workers (CHWs) have become essential to the promotion of healthy behaviors, yet their work is complicated by challenges both within and beyond their control. These challenges include resistance to the change of existing behaviors, disbelief of health messages, limited community health literacy, insufficient CHW communication skills and knowledge, lack of community interest and respect for CHWs, and CHWs' lack of adequate supplies. The rising penetration of ``smart'' technology (eg, smartphones and tablets) in low- and middle-income countries facilitates the use of portable electronic devices in the field. Objective: This scoping review examines to what extent mobile health in the form of smart devices may enhance the delivery of public health messages in CHW-client interactions, thereby addressing the aforementioned challenges and inducing client behavior change. Methods: We conducted a structured search of the PubMed and LILACS databases using subject heading terms in 4 categories: technology user, technology device, use of technology, and outcome. Eligibility criteria included publication since January 2007, CHWs delivering a health message aided by a smart device, and face-to-face communication between CHWs and clients. Eligible studies were analyzed qualitatively using a modified version of the Partners in Health conceptual framework. Results: We identified 12 eligible studies, 10 (83\%) of which used qualitative or mixed methods approaches. We found that smart devices mitigate challenges encountered by CHWs by improving their knowledge, motivation, and creativity (eg, through self-made videos); their status within the community; and the credibility of their health messages. The technology stimulated interest in both CHWs and clients---and sometimes even in bystanders and neighbors. Media content produced locally or reflecting local customs was strongly embraced. Yet, the effect of smart devices on the quality of CHW-client interactions was inconclusive. Interactions suffered as CHWs were tempted to replace educational conversations with clients by passively watching video content. Furthermore, a series of technical difficulties experienced especially by older and less educated CHWs compromised some of the advantages brought about by mobile devices. Adequate CHW training ameliorated these difficulties. Only 1 study (8\%) considered client health behavior change as an end point, thus revealing a major research gap. Conclusions: Smart mobile devices may augment CHWs' field performance and enhance face-to-face interactions with clients, yet they also generate new challenges. The available evidence is scarce, mostly qualitative, and focused on a limited range of health outcomes. Future research should include larger-scale interventions across a wide range of health outcomes and feature client health behavior change as an end point. ", doi="10.2196/42023", url="https://mhealth.jmir.org/2023/1/e42023", url="http://www.ncbi.nlm.nih.gov/pubmed/36811947" } @Article{info:doi/10.2196/41508, author="Li, Suya and Yang, Qing and Niu, Shuya and Liu, Yu", title="Effectiveness of Remote Fetal Monitoring on Maternal-Fetal Outcomes: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2023", month="Feb", day="22", volume="11", pages="e41508", keywords="remote fetal monitoring", keywords="maternal outcomes", keywords="fetal outcomes", keywords="review", abstract="Background: To solve the disadvantages of traditional fetal monitoring such as time-consuming, cumbersome steps and low coverage, it is paramount to develop remote fetal monitoring. Remote fetal monitoring expands time and space, which is expected to popularize fetal monitoring in remote areas with the low availability of health services. Pregnant women can transmit fetal monitoring data from remote monitoring terminals to the central monitoring station so that doctors can interpret it remotely and detect fetal hypoxia in time. Fetal monitoring involving remote technology has also been carried out, but with some conflicting results. Objective: The review aimed to (1) examine the efficacy of remote fetal monitoring in improving maternal-fetal outcomes and (2) identify research gaps in the field to make recommendations for future research. Methods: We did a systematic literature search with PubMed, Cochrane Library, Web of Science, Embase, MEDLINE, CINAHL, ProQuest Dissertations and Theses Global, ClinicalTrials.gov, and Open Grey in March 2022. Randomized controlled trials or quasi-experimental trials of remote fetal monitoring were identified. Two reviewers independently searched articles, extracted data, and assessed each study. Primary outcomes (maternal-fetal outcomes) and secondary outcomes (health care usage) were presented as relative risks or mean difference. The review was registered on PROSPERO as CRD42020165038. Results: Of the 9337 retrieved literature, 9 studies were included in the systematic review and meta-analysis (n=1128). Compared with a control group, remote fetal monitoring reduced the risk of neonatal asphyxia (risk ratio 0.66, 95\% CI 0.45-0.97; P=.04), with a low heterogeneity of 24\%. Other maternal-fetal outcomes did not differ significantly between remote fetal monitoring and routine fetal monitoring, such as cesarean section (P=.21; I2=0\%), induced labor (P=.50; I2=0\%), instrumental vaginal birth (P=.45; I2=0\%), spontaneous delivery (P=.85; I2=0\%), gestational weeks at delivery (P=.35; I2=0\%), premature delivery (P=.47; I2=0\%), and low birth weight (P=.71; I2=0\%). Only 2 studies performed a cost analysis, stating that remote fetal monitoring can contribute to reductions in health care costs when compared with conventional care. In addition, remote fetal monitoring might affect the number of visits and duration in the hospital, but it was not possible to draw definite conclusions about the effects due to the limited number of studies. Conclusions: Remote fetal monitoring seems to reduce the incidence of neonatal asphyxia and health care costs compared with routine fetal monitoring. To strengthen the claims on the efficacy of remote fetal monitoring, further well-designed studies are necessary, especially in high-risk pregnant women, such as pregnant women with diabetes, pregnant women with hypertension, and so forth. ", doi="10.2196/41508", url="https://mhealth.jmir.org/2023/1/e41508", url="http://www.ncbi.nlm.nih.gov/pubmed/36811944" } @Article{info:doi/10.2196/44123, author="Alamoudi, Doaa and Breeze, Emma and Crawley, Esther and Nabney, Ian", title="The Feasibility of Using Smartphone Sensors to Track Insomnia, Depression, and Anxiety in Adults and Young Adults: Narrative Review", journal="JMIR Mhealth Uhealth", year="2023", month="Feb", day="17", volume="11", pages="e44123", keywords="mHealth", keywords="digital", keywords="health", keywords="mental health", keywords="insomnia", keywords="technology", keywords="sleep", keywords="risk", keywords="cardiovascular disease", keywords="diabetes", keywords="men", keywords="mortality", keywords="sleep disorder", keywords="anxiety", keywords="depression", keywords="heart disease", keywords="obesity", keywords="dementia", keywords="sensor", keywords="intervention", keywords="young adult", abstract="Background: Since the era of smartphones started in early 2007, they have steadily turned into an accepted part of our lives. Poor sleep is a health problem that needs to be closely monitored before it causes severe mental health problems, such as anxiety or depression. Sleep disorders (eg, acute insomnia) can also develop to chronic insomnia if not treated early. More specifically, mental health problems have been recognized to have casual links to anxiety, depression, heart disease, obesity, dementia, diabetes, and cancer. Several researchers have used mobile sensors to monitor sleep and to study changes in individual mood that may cause depression and anxiety. Objective: Extreme sleepiness and insomnia not only influence physical health, they also have a significant impact on mental health, such as by causing depression, which has a prevalence of 18\% to 21\% among young adults aged 16 to 24 in the United Kingdom. The main body of this narrative review explores how passive data collection through smartphone sensors can be used in predicting anxiety and depression. Methods: A narrative review of the English language literature was performed. We investigated the use of smartphone sensors as a method of collecting data from individuals, regardless of whether the data source was active or passive. Articles were found from a search of Google Scholar records (from 2013 to 2020) with keywords including ``mobile phone,'' ``mobile applications,'' ``health apps,'' ``insomnia,'' ``mental health,'' ``sleep monitoring,'' ``depression,'' ``anxiety,'' ``sleep disorder,'' ``lack of sleep,'' ``digital phenotyping,'' ``mobile sensing,'' ``smartphone sensors,'' and ``sleep detector.'' Results: The 12 articles presented in this paper explain the current practices of using smartphone sensors for tracking sleep patterns and detecting changes in mental health, especially depression and anxiety over a period of time. Several researchers have been exploring technological methods to detect sleep using smartphone sensors. Researchers have also investigated changes in smartphone sensors and linked them with mental health and well-being. Conclusions: The conducted review provides an overview of the possibilities of using smartphone sensors unobtrusively to collect data related to sleeping pattern, depression, and anxiety. This provides a unique research opportunity to use smartphone sensors to detect insomnia and provide early detection or intervention for mental health problems such as depression and anxiety if insomnia is detected. ", doi="10.2196/44123", url="https://mhealth.jmir.org/2023/1/e44123", url="http://www.ncbi.nlm.nih.gov/pubmed/36800211" } @Article{info:doi/10.2196/40844, author="Moreno-Ligero, Marta and Moral-Munoz, A. Jose and Salazar, Alejandro and Failde, Inmaculada", title="mHealth Intervention for Improving Pain, Quality of Life, and Functional Disability in Patients With Chronic Pain: Systematic Review", journal="JMIR Mhealth Uhealth", year="2023", month="Feb", day="2", volume="11", pages="e40844", keywords="chronic pain", keywords="mHealth", keywords="mobile health", keywords="mobile app", keywords="health app", keywords="digital intervention", keywords="monitoring", keywords="pain intensity", keywords="quality of life", keywords="functionality", keywords="disability", keywords="disabilities", keywords="systematic review", keywords="review methodology", keywords="search strategy", keywords="library science", keywords="RCT", keywords="randomized controlled trial", keywords="pain", keywords="health outcome", keywords="self-management", abstract="Background: Chronic pain (CP) is 1 of the leading causes of disability worldwide and represents a significant burden on individual, social, and economic aspects. Potential tools, such as mobile health (mHealth) systems, are emerging for the self-management of patients with CP. Objective: A systematic review was conducted to analyze the effects of mHealth interventions on CP management, based on pain intensity, quality of life (QoL), and functional disability assessment, compared to conventional treatment or nonintervention. Methods: PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines were followed to conduct a systematic review of randomized controlled trials (RCTs) published in PubMed, Web of Science, Scopus, and Physiotherapy Evidence Database (PEDro) databases from February to March 2022. No filters were used. The eligibility criteria were RCTs of adults (?18 years old) with CP, intervened with mHealth systems based on mobile apps for monitoring pain and health-related outcomes, for pain and behavioral self-management, and for performing therapeutic approaches, compared to conventional treatments (physical, occupational, and psychological therapies; usual medical care; and education) or nonintervention, reporting pain intensity, QoL, and functional disability. The methodological quality and risk of bias (RoB) were assessed using the Checklist for Measuring Quality, the Oxford Centre for Evidence-Based Medicine Levels of Evidence, and the Cochrane RoB 2.0 tool. Results: In total, 22 RCTs, involving 2641 patients with different CP conditions listed in the International Classification of Diseases 11th Revision (ICD-11), including chronic low back pain (CLBP), chronic musculoskeletal pain (CMSP), chronic neck pain (CNP), unspecified CP, chronic pelvic pain (CPP), fibromyalgia (FM), interstitial cystitis/bladder pain syndrome (IC/BPS), irritable bowel syndrome (IBS), and osteoarthritis (OA). A total of 23 mHealth systems were used to conduct a variety of CP self-management strategies, among which monitoring pain and symptoms and home-based exercise programs were the most used. Beneficial effects of the use of mHealth systems in reducing pain intensity (CNP, FM, IC/BPS, and OA), QoL (CLBP, CNP, IBS, and OA), and functional disability (CLBP, CMSP, CNP, and OA) were found. Most of the included studies (18/22, 82\%) reported medium methodological quality and were considered as highly recommendable; in addition, 7/22 (32\%) studies had a low RoB, 10/22 (45\%) had some concerns, and 5/22 (23\%) had a high RoB. Conclusions: The use of mHealth systems indicated positive effects for pain intensity in CNP, FM, IC/BPS, and OA; for QoL in CLBP, CNP, IBS, and OA; and for functional disability in CLBP, CMSP, CNP, and OA. Thus, mHealth seems to be an alternative to improving pain-related outcomes and QoL and could be part of multimodal strategies for CP self-management. High-quality studies are needed to merge the evidence and recommendations of the use of mHealth systems for CP management. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42022315808; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=315808 ", doi="10.2196/40844", url="https://mhealth.jmir.org/2023/1/e40844", url="http://www.ncbi.nlm.nih.gov/pubmed/36729570" } @Article{info:doi/10.2196/37487, author="Kwon, Young Oh and Choi, Jin-young and Jang, Yeonsoo", title="The Effectiveness of eHealth Interventions on Lifestyle Modification in Patients With Nonalcoholic Fatty Liver Disease: Systematic Review and Meta-analysis", journal="J Med Internet Res", year="2023", month="Jan", day="23", volume="25", pages="e37487", keywords="eHealth", keywords="lifestyle modification", keywords="non-alcoholic fatty liver disease", keywords="systematic review", keywords="meta-analysis", abstract="Background: The prevalence of nonalcoholic fatty liver disease (NAFLD) is increasing in parallel with the epidemic of obesity and metabolic syndrome. Lifestyle modification is a crucial strategy for the treatment of NAFLD, which can lead to a reduction in liver fat with concomitant weight loss. The use of eHealth technologies is an effective approach to improve health outcomes in patients as they do not have any time and space limitations. Objective: This study aimed to evaluate published eHealth intervention studies for the improvement of lifestyle modifications among patients with NAFLD and to provide recommendations for future studies. Methods: We conducted a systematic review and meta-analysis. Five electronic databases (PubMed, Cochrane Central, CINAHL, Embase, and Web of Science) were searched for studies reporting the effect of lifestyle modification intervention using eHealth in patients with NAFLD published from inception to November 3, 2022. Study selection, data extraction, and quality assessment were performed by 3 researchers independently. The quality of included studies was assessed using the Cochrane risk of bias tool and the Risk of Bias Assessment Tool for Nonrandomized Studies. Results: In total, 2688 records were identified, and 41 full-text articles were assessed. Seven studies were included in the systematic review. The participants of all interventions were 1257 individuals with NAFLD, and the mean age ranged from 38.3 to 57.9 years. The duration of the interventions was 3-24 months, and all interventions were categorized into 3 types: internet-based computers, telephones, and mobile apps. Of these, 4 studies were randomized controlled trials and were included in the meta-analysis: 3 studies for body weight and BMI and 4 studies for alanine aminotransferase (ALT) and aspartate aminotransferase (AST). According to the meta-analysis, clear improvements in BMI (P=.02; 95\% CI --1.01 to --0.10), AST (P=.02; 95\% CI --1.22 to --0.13), and ALT (P=.01; 95\% CI --1.28 to --0.15) were observed in the eHealth intervention as compared with the control groups. Conclusions: Lifestyle modification interventions using eHealth technologies are significantly effective for BMI, AST, and ALT in patients with NAFLD. Future research should conduct interventions with larger sample sizes and evaluate whether these interventions have sustained benefits, and how we can make these eHealth methods most effective on a large scale. ", doi="10.2196/37487", url="https://www.jmir.org/2023/1/e37487", url="http://www.ncbi.nlm.nih.gov/pubmed/36689264" } @Article{info:doi/10.2196/42799, author="Sun, Liang and Qu, Mengbing and Chen, Bing and Li, Chuancang and Fan, Haohao and Zhao, Yang", title="Effectiveness of mHealth on Adherence to Antiretroviral Therapy in Patients Living With HIV: Meta-analysis of Randomized Controlled Trials", journal="JMIR Mhealth Uhealth", year="2023", month="Jan", day="23", volume="11", pages="e42799", keywords="HIV", keywords="mHealth", keywords="antiretroviral therapy", keywords="meta-analysis", abstract="Background: The World Health Organization recommends that all adults with HIV adhere to antiretroviral therapy (ART). Good adherence to ART is beneficial to patients and the public. Furthermore, mHealth has shown promise in improving HIV medication adherence globally. Objective: The aim of this meta-analysis is to analyze the effectiveness of mHealth on adherence to antiretroviral therapy in patients living with HIV. Methods: Randomized controlled trials (RCTs) of the association between mHealth and adherence to ART published until December 2021 were searched in electronic databases. Odds ratios (ORs), weighted mean differences, and 95\% CIs were calculated. This meta-analysis was performed using the Mantel-Haenszel method or the inverse variance test. We evaluated heterogeneity with the I2 statistic. If I2 was ?50\%, heterogeneity was absent, and a fixed effect model was used. If I2 was >50\%, heterogeneity was present, and a random effects model was used. Results: A total of 2163 participants in 8 studies were included in this meta-analysis. All included studies were RCTs. The random effects model was used for a meta-analysis of the effects of various intervention measures compared to routine nursing; the outcome was not statistically significant (OR 1.54, 95\% CI 0.99-2.38; P=.05). In the subgroups, only short messaging service (SMS)-based interventions significantly increased adherence to ART (OR 1.76, 95\% CI 1.07-2.89; P=.03). Further analysis showed that only interactive or bidirectional SMS could significantly increase ART adherence (OR 1.69, 95\% CI 1.22-2.34; P=.001). After combining the difference in CD4 cell count before and after the interventions, we concluded that there was no statistical heterogeneity among the studies (I2=0\%; tau2=0.37; P=.95). Conclusions: Interactive or bidirectional SMS can enhance intervention effects. However, whether mHealth can improve adherence to ART in patients with HIV needs further study. Owing to a lack of the required significant staff time, training, and ongoing supervision, there is still much more to do to apply mHealth to the clinical use of ART for patients living with HIV. Trial Registration: PROSPERO CRD42022358774; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=358774 ", doi="10.2196/42799", url="https://mhealth.jmir.org/2023/1/e42799", url="http://www.ncbi.nlm.nih.gov/pubmed/36689267" } @Article{info:doi/10.2196/41235, author="Salas-Groves, Emily and Galyean, Shannon and Alcorn, Michelle and Childress, Allison", title="Behavior Change Effectiveness Using Nutrition Apps in People With Chronic Diseases: Scoping Review", journal="JMIR Mhealth Uhealth", year="2023", month="Jan", day="13", volume="11", pages="e41235", keywords="mobile apps", keywords="apps", keywords="mobile health", keywords="mHealth", keywords="eHealth", keywords="nutrition education", keywords="cancer", keywords="obesity", keywords="diabetes", keywords="cardiovascular disease", keywords="mobile phone", abstract="Background: Cardiovascular disease, cancer, diabetes mellitus, and obesity are common chronic diseases, and their prevalence is reaching an epidemic level worldwide. As the impact of chronic diseases continues to increase, finding strategies to improve care, access to care, and patient empowerment becomes increasingly essential. Health care providers use mobile health (mHealth) to access clinical information, collaborate with care teams, communicate over long distances with patients, and facilitate real-time monitoring and interventions. However, these apps focus on improving general health care concerns, with limited apps focusing on specific chronic diseases and the nutrition involved in the disease state. Hence, available evidence on the effectiveness of mHealth apps toward behavior change to improve chronic disease outcomes is limited. Objective: The objective of this scoping review was to provide an overview of behavior change effectiveness using mHealth nutrition interventions in people with chronic diseases (ie, cardiovascular disease, diabetes mellitus, cancer, and obesity). We further evaluated the behavior change techniques and theories or models used for behavior change, if any. Methods: A scoping review was conducted through a systematic literature search in the MEDLINE, EBSCO, PubMed, ScienceDirect, and Scopus databases. Studies were excluded from the review if they did not involve an app or nutrition intervention, were written in a language other than English, were duplicates from other database searches, or were literature reviews. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines, the systematic review process included 4 steps: identification of records through the database search, screening of duplicate and excluded records, eligibility assessment of full-text records, and final analysis of included records. Results: In total, 46 studies comprising 256,430 patients were included. There was diversity in the chronic disease state, study design, number of participants, in-app features, behavior change techniques, and behavior models used in the studies. In addition, our review found that less than half (19/46, 41\%) of the studies based their nutrition apps on a behavioral theory or its constructs. Of the 46 studies, 11 (24\%) measured maintenance of health behavior change, of which 7 (64\%) sustained behavior change for approximately 6 to 12 months and 4 (36\%) showed a decline in behavior change or discontinued app use. Conclusions: The results suggest that mHealth apps involving nutrition can significantly improve health outcomes in people with chronic diseases. Tailoring nutrition apps to specific populations is recommended for effective behavior change and improvement of health outcomes. In addition, some studies (7/46, 15\%) showed sustained health behavior change, and some (4/46, 9\%) showed a decline in the use of nutrition apps. These results indicate a need for further investigation on the sustainability of the health behavior change effectiveness of disease-specific nutrition apps. ", doi="10.2196/41235", url="https://mhealth.jmir.org/2023/1/e41235", url="http://www.ncbi.nlm.nih.gov/pubmed/36637888" } @Article{info:doi/10.2196/40210, author="Brobbin, Eileen and Deluca, Paolo and Hemrage, Sofia and Drummond, Colin", title="Acceptability and Feasibility of Wearable Transdermal Alcohol Sensors: Systematic Review", journal="JMIR Hum Factors", year="2022", month="Dec", day="23", volume="9", number="4", pages="e40210", keywords="alcohol consumption", keywords="alcohol monitoring", keywords="digital technology", keywords="transdermal alcohol sensors", keywords="wearables", keywords="acceptability", keywords="feasibility", keywords="monitoring", keywords="sensors", keywords="real-time feedback", keywords="health promotion", keywords="alcohol intake", abstract="Background: Transdermal alcohol sensors (TASs) have the potential to be used to monitor alcohol consumption objectively and continuously. These devices can provide real-time feedback to the user, researcher, or health professional and measure alcohol consumption and peaks of use, thereby addressing some of the limitations of the current methods, including breathalyzers and self-reports. Objective: This systematic review aims to evaluate the acceptability and feasibility of the currently available TAS devices. Methods: A systematic search was conducted in CINAHL, EMBASE, Google Scholar, MEDLINE, PsycINFO, PubMed, and Scopus bibliographic databases in February 2021. Two members of our study team independently screened studies for inclusion, extracted data, and assessed the risk of bias. The study's methodological quality was appraised using the Mixed Methods Appraisal Tool. The primary outcome was TAS acceptability. The secondary outcome was feasibility. The data are presented as a narrative synthesis. Results: We identified and analyzed 22 studies. Study designs included laboratory- and ambulatory-based studies, mixed designs, randomized controlled trials, and focus groups, and the length the device was worn ranged from days to weeks. Although views on TASs were generally positive with high compliance, some factors were indicated as potential barriers and there are suggestions to overcome these. Conclusions: There is a lack of research investigating the acceptability and feasibility of TAS devices as a tool to monitor alcohol consumption in clinical and nonclinical populations. Although preliminary evidence suggests their potential in short-term laboratory-based studies with volunteers, more research is needed to establish long-term daily use with other populations, specifically, in the clinical and the criminal justice system. Trial Registration: PROSPERO CRD42021231027; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=231027 ", doi="10.2196/40210", url="https://humanfactors.jmir.org/2022/4/e40210", url="http://www.ncbi.nlm.nih.gov/pubmed/36563030" } @Article{info:doi/10.2196/40271, author="AlSwayied, Ghada and Guo, Haoyue and Rookes, Tasmin and Frost, Rachael and Hamilton, L. Fiona", title="Assessing the Acceptability and Effectiveness of Mobile-Based Physical Activity Interventions for Midlife Women During Menopause: Systematic Review of the Literature", journal="JMIR Mhealth Uhealth", year="2022", month="Dec", day="9", volume="10", number="12", pages="e40271", keywords="mobile app", keywords="mobile health", keywords="mHealth", keywords="smartphone", keywords="smartphone apps", keywords="physical activity", keywords="exercise", keywords="midlife women", keywords="menopause", keywords="menopausal symptoms", keywords="behavior change", keywords="women's health", keywords="wearable", keywords="activity tracker", keywords="effectiveness", keywords="acceptability", keywords="review", keywords="meta-analysis", keywords="mobile phone", abstract="Background: Midlife women with menopausal symptoms are less likely to meet the recommended level of physical activity (PA). Promoting PA among women in midlife could reduce their risk of cardiovascular diseases and perhaps improve menopausal symptoms. Mobile PA interventions in the form of smartphone apps and wearable activity trackers can potentially encourage users to increase PA levels and address time and resource barriers to PA. However, evidence on the acceptability and effectiveness of these interventions among midlife women is unclear. Objective: This systematic review evaluated the effectiveness, acceptability, and active behavior change techniques (BCTs) of mobile PA technologies among midlife menopausal women. Methods: A mixed methods systematic review of qualitative and quantitative studies was conducted. MEDLINE (Ovid), Embase, Scopus, CINAHL, Web of Science, SPORTDiscus, CENTRAL, PsycINFO, and the ProQuest Sports Medicine and Education Index were systematically searched. Studies were selected and screened according to predetermined eligibility criteria. In total, 2 reviewers independently assessed the risk of bias using the Mixed Methods Appraisal Tool and completed BCT mapping of the included interventions using the BCT Taxonomy v1. Results: A total of 12 studies were included in this review. Overall risk of bias was ``Moderate to high'' in 58\% (7/12) of the included studies and ``low'' in 42\% (5/12) of the studies. Of the 12 studies, 7 (58\%) assessed changes in PA levels. The pooled effect size of 2 randomized controlled trials resulted in a small to moderate increase in moderate to vigorous PA of approximately 61.36 weekly minutes among midlife women, at least in the short term (95\% CI 17.70-105.01; P=.006). Although a meta-analysis was not feasible because of heterogeneity, positive improvements were also found in a range of menopause-related outcomes such as weight reduction, anxiety management, sleep quality, and menopause-related quality of life. Midlife women perceived mobile PA interventions to be acceptable and potentially helpful in increasing PA and daily steps. The average number of BCTs per mobile PA intervention was 8.8 (range 4-13) according to the BCT Taxonomy v1. ``Self-monitoring of behaviour,'' ``Biofeedback,'' and ``Goal setting (behaviour)'' were the most frequently described BCTs across the included interventions. Conclusions: This review demonstrated that mobile PA interventions in the form of smartphone apps and wearable trackers are potentially effective for small to moderate increases in moderate to vigorous PA among midlife women with menopausal symptoms. Although menopause is a natural condition affecting half the population worldwide, there is a substantial lack of evidence to support the acceptability and effectiveness of mobile PA interventions on menopause-related outcomes, which needs further investigation. Trial Registration: PROSPERO CRD42021273062; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=273062 ", doi="10.2196/40271", url="https://mhealth.jmir.org/2022/12/e40271", url="http://www.ncbi.nlm.nih.gov/pubmed/36485026" } @Article{info:doi/10.2196/35802, author="Healy, David and Flynn, Aisling and Conlan, Owen and McSharry, Jenny and Walsh, Jane", title="Older Adults' Experiences and Perceptions of Immersive Virtual Reality: Systematic Review and Thematic Synthesis", journal="JMIR Serious Games", year="2022", month="Dec", day="6", volume="10", number="4", pages="e35802", keywords="older adults", keywords="virtual reality", keywords="immersive virtual reality", keywords="aging", keywords="systematic review", keywords="qualitative evidence synthesis", keywords="thematic synthesis", abstract="Background: Immersive virtual reality (IVR) can be defined as a fully computer-generated environment shown on a head-mounted display. Existing research suggests that key features of IVR can assist older adults in their everyday lives, providing opportunities for health promotion and tackling social isolation and loneliness. There has been a surge in qualitative studies exploring older adults' experiences and perceptions of IVR. However, there has been no systematic synthesis of these studies to inform the design of new, more accessible IVR technologies. Objective: This study aimed to systematically review and synthesize qualitative studies exploring older adults' experiences and perceptions of IVR. Methods: A systematic review and thematic synthesis were conducted following the ENTREQ (Enhancing Transparency in Reporting the Synthesis of Qualitative Research) guidelines. In total, 2 reviewers completed title and abstract screening, full-text screening, data extraction, and quality appraisal. Thematic synthesis is derived from the qualitative method, thematic analysis. It involves 3 key steps: initial coding and grouping of these codes, the formation of descriptive themes from these codes, and going beyond these data to form analytical themes. Confidence in the evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation-Confidence in the Evidence from Reviews of Qualitative Research approach. Results: Overall, 13 studies were included in the final synthesis, including 224 participants across 9 countries and 5 continents. Confidence in the evidence ranged from high to moderate. Three descriptive themes were generated: practical aspects of IVR use, experiencing unique features of IVR, and perceptions of IVR. The findings from the descriptive themes suggested that there are several improvements that need to be made to existing IVR devices to facilitate older adults' use of this technology. However, older adults' responses to IVR were generally positive. Three analytical themes were generated: tolerating the bad to experience the good, buying in to IVR (don't judge a book by its cover), and ``it proves to me I can do it.'' The analytical themes illustrated that older adults were willing to tolerate discomforts that accompany existing IVR technologies to experience features such as immersive social networking. There was a discrepancy between older adults' perceptions of IVR before use---which were generally negative---and after use---which were generally positive---and IVR provided a platform for older adults to access certain activities and environments more easily than in the real world because of limitations caused by aging. Conclusions: This review offers insights into older adults' experiences and perceptions of IVR and suggests how a few improvements to its existing hardware and software as well as how it is first presented could offer new opportunities for older adults to take part in meaningful activities tailored to their needs and preferences. Trial Registration: PROSPERO CRD42020200774; https://tinyurl.com/8f48w2vt International Registered Report Identifier (IRRID): RR2-10.1177/16094069211009682 ", doi="10.2196/35802", url="https://games.jmir.org/2022/4/e35802", url="http://www.ncbi.nlm.nih.gov/pubmed/36472894" } @Article{info:doi/10.2196/26041, author="M{\"u}ller, Alison and Cau, Alessandro and Muhammed, Semakula and Abdullahi, Osman and Hayward, Andrew and Nsanzimana, Sabin and Lester, Richard", title="Digital mHealth and Virtual Care Use During COVID-19 in 4 Countries: Rapid Landscape Review", journal="JMIR Form Res", year="2022", month="Nov", day="30", volume="6", number="11", pages="e26041", keywords="COVID-19", keywords="virtual care", keywords="public health", keywords="mHealth", keywords="contact tracing", keywords="telehealth", keywords="Canada", keywords="United Kingdom", keywords="Kenya", keywords="Rwanda", keywords="global health", keywords="apps", abstract="Background: As a result of the COVID-19 pandemic, providing health care while maintaining social distancing has resulted in the need to provide care remotely, support quarantined or isolated individuals, monitor infected individuals and their close contacts, as well as disseminate accurate information regarding COVID-19 to the public. This has led to an unprecedented rapid expansion of digital tools to provide digitized virtual care globally, especially mobile phone--facilitated health interventions, called mHealth. To help keep abreast of different mHealth and virtual care technologies being used internationally to facilitate patient care and public health during the COVID-19 pandemic, we carried out a rapid investigation of solutions being deployed and considered in 4 countries. Objective: The aim of this paper was to describe mHealth and the digital and contact tracing technologies being used in the health care management of the COVID-19 pandemic among 2 high-income and 2 low-middle income countries. Methods: We compared virtual care interventions used for COVID-19 management among 2 high-income countries (the United Kingdom and Canada) and 2 low-middle income (Kenya and Rwanda) countries. We focused on interventions used to facilitate patient care and public health. Information regarding specific virtual care technologies was procured from a variety of resources including gray literature, government and health organization websites, and coauthors' personal experiences as implementers of COVID-19 virtual care strategies. Search engine queries were performed to find health information that would be easily accessible to the general public, with keywords including ``COVID-19,'' ``contact-tracing,'' ``tool-kit,'' ``telehealth,'' and ``virtual care,'' in conjunction with corresponding national health authorities. Results: We identified a variety of technologies in Canada, the United Kingdom, Rwanda, and Kenya being used for patient care and public health. These countries are using both video and text message--based platforms to facilitate communication with health care providers (eg, WelTel and Zoom). Nationally developed contact tracing apps are provided free to the public, with most of them using Bluetooth-based technology. We identified that often multiple complimentary technologies are being utilized for different aspects of patient care and public health with the common purpose to disseminate information safely. There was a negligible difference among the types of technologies used in both high-income and low-middle income countries, although the latter implemented virtual care interventions earlier during the pandemic's first wave, which may account for their effective response. Conclusions: Virtual care and mHealth technologies have evolved rapidly as a tool for health care support for both patient care and public health. It is evident that, on an international level, a variety of mHealth and virtual care interventions, often in combination, are required to be able to address patient care and public health concerns during the COVID-19 pandemic, independent of a country's economic standing. ", doi="10.2196/26041", url="https://formative.jmir.org/2022/11/e26041", url="http://www.ncbi.nlm.nih.gov/pubmed/34932498" } @Article{info:doi/10.2196/40797, author="Lee, Peter and Kim, Heepyung and Zitouni, Sami M. and Khandoker, Ahsan and Jelinek, F. Herbert and Hadjileontiadis, Leontios and Lee, Uichin and Jeong, Yong", title="Trends in Smart Helmets With Multimodal Sensing for Health and Safety: Scoping Review", journal="JMIR Mhealth Uhealth", year="2022", month="Nov", day="15", volume="10", number="11", pages="e40797", keywords="Internet of Things", keywords="IoT", keywords="sensor technology", keywords="smart helmet", keywords="smart sensor", keywords="wearable device", keywords="mobile phone", abstract="Background: As a form of the Internet of Things (IoT)--gateways, a smart helmet is one of the core devices that offers distinct functionalities. The development of smart helmets connected to IoT infrastructure helps promote connected health and safety in various fields. In this regard, we present a comprehensive analysis of smart helmet technology and its main characteristics and applications for health and safety. Objective: This paper reviews the trends in smart helmet technology and provides an overview of the current and future potential deployments of such technology, the development of smart helmets for continuous monitoring of the health status of users, and the surrounding environmental conditions. The research questions were as follows: What are the main purposes and domains of smart helmets for health and safety? How have researchers realized key features and with what types of sensors? Methods: We selected studies cited in electronic databases such as Google Scholar, Web of Science, ScienceDirect, and EBSCO on smart helmets through a keyword search from January 2010 to December 2021. In total, 1268 papers were identified (Web of Science: 87/1268, 6.86\%; EBSCO: 149/1268, 11.75\%; ScienceDirect: 248/1268, 19.55\%; and Google Scholar: 784/1268, 61.82\%), and the number of final studies included after PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) study selection was 57. We also performed a self-assessment of the reviewed articles to determine the quality of the paper. The scoring was based on five criteria: test environment, prototype quality, feasibility test, sensor calibration, and versatility. Results: Smart helmet research has been considered in industry, sports, first responder, and health tracking scenarios for health and safety purposes. Among 57 studies, most studies with prototype development were industrial applications (18/57, 32\%), and the 2 most frequent studies including simulation were industry (23/57, 40\%) and sports (23/57, 40\%) applications. From our assessment-scoring result, studies tended to focus on sensor calibration results (2.3 out of 3), while the lowest part was a feasibility test (1.6 out of 3). Further classification of the purpose of smart helmets yielded 4 major categories, including activity, physiological and environmental (hazard) risk sensing, as well as risk event alerting. Conclusions: A summary of existing smart helmet systems is presented with a review of the sensor features used in the prototyping demonstrations. Overall, we aimed to explore new possibilities by examining the latest research, sensor technologies, and application platform perspectives for smart helmets as promising wearable devices. The barriers to users, challenges in the development of smart helmets, and future opportunities for health and safety applications are also discussed. In conclusion, this paper presents the current status of smart helmet technology, main issues, and prospects for future smart helmet with the objective of making the smart helmet concept a reality. ", doi="10.2196/40797", url="https://mhealth.jmir.org/2022/11/e40797", url="http://www.ncbi.nlm.nih.gov/pubmed/36378505" } @Article{info:doi/10.2196/36696, author="Choi, Jin-Young and Jeon, Seonghee and Kim, Hana and Ha, Jaeyoung and Jeon, Gyeong-suk and Lee, Jeong and Cho, Sung-il", title="Health-Related Indicators Measured Using Earable Devices: Systematic Review", journal="JMIR Mhealth Uhealth", year="2022", month="Nov", day="15", volume="10", number="11", pages="e36696", keywords="digital public health", keywords="earable", keywords="wearable", keywords="biomarker", keywords="health status", keywords="disease monitoring", keywords="prevention strategy", keywords="Internet of Things", keywords="systematic review", keywords="mobile phone", abstract="Background: Earable devices are novel, wearable Internet of Things devices that are user-friendly and have potential applications in mobile health care. The position of the ear is advantageous for assessing vital status and detecting diseases through reliable and comfortable sensing devices. Objective: Our study aimed to review the utility of health-related indicators derived from earable devices and propose an improved definition of disease prevention. We also proposed future directions for research on the health care applications of earable devices. Methods: A systematic review was conducted of the PubMed, Embase, and Web of Science databases. Keywords were used to identify studies on earable devices published between 2015 and 2020. The earable devices were described in terms of target health outcomes, biomarkers, sensor types and positions, and their utility for disease prevention. Results: A total of 51 articles met the inclusion criteria and were reviewed, and the frequency of 5 health-related characteristics of earable devices was described. The most frequent target health outcomes were diet-related outcomes (9/51, 18\%), brain status (7/51, 14\%), and cardiovascular disease (CVD) and central nervous system disease (5/51, 10\% each). The most frequent biomarkers were electroencephalography (11/51, 22\%), body movements (6/51, 12\%), and body temperature (5/51, 10\%). As for sensor types and sensor positions, electrical sensors (19/51, 37\%) and the ear canal (26/51, 51\%) were the most common, respectively. Moreover, the most frequent prevention stages were secondary prevention (35/51, 69\%), primary prevention (12/51, 24\%), and tertiary prevention (4/51, 8\%). Combinations of ?2 target health outcomes were the most frequent in secondary prevention (8/35, 23\%) followed by brain status and CVD (5/35, 14\% each) and by central nervous system disease and head injury (4/35, 11\% each). Conclusions: Earable devices can provide biomarkers for various health outcomes. Brain status, healthy diet status, and CVDs were the most frequently targeted outcomes among the studies. Earable devices were mostly used for secondary prevention via monitoring of health or disease status. The potential utility of earable devices for primary and tertiary prevention needs to be investigated further. Earable devices connected to smartphones or tablets through cloud servers will guarantee user access to personal health information and facilitate comfortable wearing. ", doi="10.2196/36696", url="https://mhealth.jmir.org/2022/11/e36696", url="http://www.ncbi.nlm.nih.gov/pubmed/36239201" } @Article{info:doi/10.2196/37624, author="Angerer, Alfred and Stahl, Johanna and Krasniqi, Egzona and Banning, Stefan", title="The Management Perspective in Digital Health Literature: Systematic Review", journal="JMIR Mhealth Uhealth", year="2022", month="Nov", day="10", volume="10", number="11", pages="e37624", keywords="digital health", keywords="management", keywords="health care management", keywords="literature review", keywords="health technology", keywords="eHealth", keywords="data health", keywords="trend health", keywords="tech health", abstract="Background: New digital health technologies are considered one solution to challenges in the health sector, which include rising numbers of chronic diseases and increased health spending. As digitalization in health care is still in its infancy, there are many unanswered questions about the impact of digital health on management. Objective: This paper assesses the current state of knowledge in the field of digital health from a management perspective. It highlights research gaps within this field to determine future research opportunities. Methods: A systematic review of digital health literature was conducted using 3 databases. The chosen articles (N=38) were classified according to a taxonomy developed for the purpose, and research gaps were identified based on the topic areas discussed. Results: The literature review revealed a slight prevalence of practical (n=21, 55\%) over theoretical (n=17, 45\%) approaches. Most of the papers (n=23, 61\%) deal with information technology (IT) and are, therefore, focused more on technology and less on management. The research question in most of the papers (n=31, 82\%) deals with the creation of concepts, and very few (n=4, 11\%) evaluate or even question existing solutions. Most consider the main reason for digitalization to be the optimization of operational processes (n=26, 68\%), and 42\% (n=16) deal with new business models. The topic area discussed most frequently was found to be eHealth (n=30, 79\%). By contrast, the field of tech health with topics such as sensors receives the least attention (n=3, 8\%), despite its significant potential for health care processes and strategy. Conclusions: Three main research propositions were identified. First, research into digital health innovation should not focus solely on the technology aspects but also on its implications for strategic and operational management. Second, the research community should target other domains besides eHealth. Third, we observed a lack of quantitative research on the real impact of digital health on organizations and their management. More quantitative evidence is required regarding the expected outcome and impact of the implementation of digital health solutions into our health care organizations. ", doi="10.2196/37624", url="https://mhealth.jmir.org/2022/11/e37624", url="http://www.ncbi.nlm.nih.gov/pubmed/36355426" } @Article{info:doi/10.2196/37234, author="Sediva, Hana and Cartwright, Tina and Robertson, Claire and Deb, K. Sanjoy", title="Behavior Change Techniques in Digital Health Interventions for Midlife Women: Systematic Review", journal="JMIR Mhealth Uhealth", year="2022", month="Nov", day="9", volume="10", number="11", pages="e37234", keywords="menopause", keywords="midlife", keywords="women's health", keywords="lifestyle", keywords="behavior change technique", keywords="BCT", keywords="behavioral intervention", keywords="digital health", keywords="mobile health", keywords="mHealth", keywords="menopausal symptom", keywords="behavior change", keywords="review", keywords="mobile phone", abstract="Background: Digital health interventions are efficacious in health-promoting behaviors (eg, healthy eating and regular physical activity) that mitigate health risks and menopausal symptoms in midlife. However, integrated evidence-based knowledge about the mechanisms of change in these interventions is unclear. Objective: This systematic review aimed to evaluate studies on behavior change techniques (BCTs) and mechanisms of change in digital health interventions aimed at promoting health-enhancing behaviors in midlife women (aged 40-65 years). Methods: A systematic literature search of the electronic databases PubMed, Web of Science, PsycINFO, and Cochrane Central Register of Controlled Trials in the Cochrane Library was conducted. In total, 2 independent reviewers selected the studies for inclusion, extracted data, and completed BCT mapping of eligible studies. The mechanism of action and intervention functions of eligible studies were evaluated using the behavior change wheel framework. Reporting of psychological theory use within these interventions was explored using the Theory Coding Scheme. Mode of delivery, psychological theory, and BCTs were presented as descriptive statistics. Results: In total, 13 interventions (including 1315 women) reviewed used 13 (SD 4.30, range 6-21) BCTs per intervention on average. The ``Shaping knowledge'' and ``Repetition and substitution'' behavior change categories were used most frequently, with 92\% (12/13) of the interventions implementing at least one of the BCTs from these 2 categories. Only 13.98\% (169/1209) of the 93 available BCTs were used, with ``Instructions on behaviour'' most frequently used (12/13, 92\%). The behavior change wheel mapping suggests that half of the intervention content aimed to increase ``Capability'' (49/98, 50\% of the intervention strategies), ``Motivation'' (41/98, 42\%), and ``Opportunity'' (8/98, 8\%). ``Behavioural Regulation'' was the most frequently used mechanism of action (15/98, 15\%), followed by increasing ``Knowledge'' (13/98, 13\%) and ``Cognitive and Interpersonal skills'' (10/98, 10\%). A total of 78\% (7/9) of the intervention functions were used in the studies to change behavior, primarily through ``Enablement'' (60/169, 35.5\%), whereas no study used ``Restriction'' or ``Modelling'' functions. Although 69\% (9/13) of the interventions mentioned a psychological theory or model, most (10/13, 77\%) stated or suggested rather than demonstrated the use of a theoretical base, and none reported explicit links between all BCTs within the intervention and the targeted theoretical constructs. Technological components were primarily based on web-based (9/13, 69\%) modes of delivery, followed by phone or SMS text message (8/13, 62\%) and wearables (7/13, 54\%). Conclusions: The findings of this review indicate an overall weak use of theory, low levels of treatment fidelity, insignificant outcomes, and insufficient description of several interventions to support the assessment of how specific BCTs were activated. Thus, the identified limitations in the current literature provide an opportunity to improve the design of lifestyle health-enhancing interventions for women in midlife. Trial Registration: PROSPERO CRD42021259246; https://tinyurl.com/4ph74a9u ", doi="10.2196/37234", url="https://mhealth.jmir.org/2022/11/e37234", url="http://www.ncbi.nlm.nih.gov/pubmed/36350694" } @Article{info:doi/10.2196/35876, author="Alnooh, Ghadah and Alessa, Tourkiah and Hawley, Mark and de Witte, Luc", title="The Use of Dietary Approaches to Stop Hypertension (DASH) Mobile Apps for Supporting a Healthy Diet and Controlling Hypertension in Adults: Systematic Review", journal="JMIR Cardio", year="2022", month="Nov", day="2", volume="6", number="2", pages="e35876", keywords="DASH diet", keywords="Dietary Approaches to Stop Hypertension", keywords="smartphone app", keywords="mobile app", keywords="blood pressure", abstract="Background: Uncontrolled hypertension is a public health issue, with increasing prevalence worldwide. The Dietary Approaches to Stop Hypertension (DASH) diet is one of the most effective dietary approaches for lowering blood pressure (BP). Dietary mobile apps have gained popularity and are being used to support DASH diet self-management, aiming to improve DASH diet adherence and thus lower BP. Objective: This systematic review aimed to assess the effectiveness of smartphone apps that support self-management to improve DASH diet adherence and consequently reduce BP. A secondary aim was to assess engagement, satisfaction, acceptance, and usability related to DASH mobile app use. Methods: The Embase (OVID), Cochrane Library, CINAHL, Web of Science, Scopus, and Google Scholar electronic databases were used to conduct systematic searches for studies conducted between 2008 and 2021 that used DASH smartphone apps to support self-management. The reference lists of the included articles were also checked. Studies were eligible if they (1) were randomized controlled trials (RCTs) or pre-post studies of app-based interventions for adults (aged 18 years or above) with prehypertension or hypertension, without consideration of gender or sociodemographic characteristics; (2) used mobile phone apps alone or combined with another component, such as communication with others; (3) used or did not use any comparator; and (4) had the primary outcome measures of BP level and adherence to the DASH diet. For eligible studies, data were extracted and outcomes were organized into logical categories, including clinical outcomes (eg, systolic BP, diastolic BP, and weight loss), DASH diet adherence, app usability and acceptability, and user engagement and satisfaction. The quality of the studies was evaluated using the Cochrane Collaboration's Risk of Bias tool for RCTs, and nonrandomized quantitative studies were evaluated using a tool provided by the US National Institutes of Health. Results: A total of 5 studies (3 RCTs and 2 pre-post studies) including 334 participants examined DASH mobile apps. All studies found a positive trend related to the use of DASH smartphone apps, but the 3 RCTs had a high risk of bias. One pre-post study had a high risk of bias, while the other had a low risk. As a consequence, no firm conclusions could be drawn regarding the effectiveness of DASH smartphone apps for increasing DASH diet adherence and lowering BP. All the apps appeared to be acceptable and easy to use. Conclusions: There is weak emerging evidence of a positive effect of using DASH smartphone apps for supporting self-management to improve DASH diet adherence and consequently lower BP. Further research is needed to provide high-quality evidence that can determine the effectiveness of DASH smartphone apps. ", doi="10.2196/35876", url="https://cardio.jmir.org/2022/2/e35876", url="http://www.ncbi.nlm.nih.gov/pubmed/36322108" } @Article{info:doi/10.2196/37980, author="Maa{\ss}, Laura and Freye, Merle and Pan, Chen-Chia and Dassow, Hans-Henrik and Niess, Jasmin and Jahnel, Tina", title="The Definitions of Health Apps and Medical Apps From the Perspective of Public Health and Law: Qualitative Analysis of an Interdisciplinary Literature Overview", journal="JMIR Mhealth Uhealth", year="2022", month="Oct", day="31", volume="10", number="10", pages="e37980", keywords="mobile health", keywords="health app", keywords="medical app", keywords="digital health", keywords="regulation", keywords="mobile medical device", keywords="digital health applications", keywords="DiGA", keywords="digital care applications", keywords="DiPA", keywords="snowball search", keywords="mobile phone", abstract="Background: The terms health app and medical app are often used interchangeably but do not necessarily mean the same thing. To better understand these terms and better regulate such technologies, we need distinct definitions of health and medical apps. Objective: This study aimed to provide an overview of the definitions of health and medical apps from an interdisciplinary perspective. We summarized the core elements of the identified definitions for their holistic understanding in the context of digital public health. Methods: The legal frameworks for medical device regulation in the United States, the European Union, and Germany formed the basis of this study. We then searched 6 databases for articles defining health or medical apps from an interdisciplinary perspective. The narrative literature review was supported by a forward and backward snowball search for more original definitions of health and medical apps. A qualitative analysis was conducted on the identified relevant aspects and core elements of each definition. On the basis of these findings, we developed a holistic definition of health and medical apps and created a decision flowchart to highlight the differences between the 2 types. Results: The legal framework showed that medical apps could be regulated as mobile medical devices, whereas there is no legal term for health apps. Our narrative literature review identified 204 peer-reviewed publications that offered a definition of health and medical apps. After screening for original definitions and applying the snowball method, 11.8\% (24/204) of the publications were included in the qualitative analysis. Of these 24 publications, 22 (88\%) provided an original definition of health apps and 11 (44\%) described medical apps. The literature suggests that medical apps are a part of health apps. To describe health or medical apps, most definitions used the user group, a description of health, the device, the legal regulation, collected data, or technological functions. However, the regulation should not be a distinction criterion as it requires legal knowledge, which is neither suitable nor practical. An app's intended medical or health use enables a clear differentiation between health and medical apps. Ultimately, the health aim of an app and its main target group are the only distinction criteria. Conclusions: Health apps are software programs on mobile devices that process health-related data on or for their users. They can be used by every health-conscious person to maintain, improve, or manage the health of an individual or the community. As an umbrella term, health apps include medical apps. Medical apps share the same technological functions and devices. Health professionals, patients, and family caregivers are the main user groups. Medical apps are intended for clinical and medical purposes and can be legally regulated as mobile medical devices. ", doi="10.2196/37980", url="https://mhealth.jmir.org/2022/10/e37980", url="http://www.ncbi.nlm.nih.gov/pubmed/36315221" } @Article{info:doi/10.2196/35722, author="Motahari-Nezhad, Hossein and Fgaier, Meriem and Mahdi Abid, Mohamed and P{\'e}ntek, M{\'a}rta and Gul{\'a}csi, L{\'a}szl{\'o} and Zrubka, Zsombor", title="Digital Biomarker--Based Studies: Scoping Review of Systematic Reviews", journal="JMIR Mhealth Uhealth", year="2022", month="Oct", day="24", volume="10", number="10", pages="e35722", keywords="scoping review", keywords="digital biomarkers", keywords="health", keywords="behavioral data", keywords="physiological data", keywords="digital health", keywords="remote monitoring", keywords="wearable", keywords="implantable", keywords="digestible", keywords="portable", keywords="sensor", keywords="mobile phone", abstract="Background: Sensors and digital devices have revolutionized the measurement, collection, and storage of behavioral and physiological data, leading to the new term digital biomarkers. Objective: This study aimed to investigate the scope of clinical evidence covered by systematic reviews (SRs) of randomized controlled trials involving digital biomarkers. Methods: This scoping review was organized using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. With the search limited to English publications, full-text SRs of digital biomarkers included randomized controlled trials that involved a human population and reported changes in participants' health status. PubMed and the Cochrane Library were searched with time frames limited to 2019 and 2020. The World Health Organization's classification systems for diseases (International Classification of Diseases, Eleventh Revision), health interventions (International Classification of Health Interventions), and bodily functions (International Classification of Functioning, Disability, and Health [ICF]) were used to classify populations, interventions, and outcomes, respectively. Results: A total of 31 SRs met the inclusion criteria. The majority of SRs studied patients with circulatory system diseases (19/31, 61\%) and respiratory system diseases (9/31, 29\%). Most of the prevalent interventions focused on physical activity behavior (16/31, 52\%) and conversion of cardiac rhythm (4/31, 13\%). Looking after one's health (physical activity; 15/31, 48\%), walking (12/31, 39\%), heart rhythm functions (8/31, 26\%), and mortality (7/31, 23\%) were the most commonly reported outcomes. In total, 16 physiological and behavioral data groups were identified using the ICF tool, such as looking after one's health (physical activity; 14/31, 45\%), walking (11/31, 36\%), heart rhythm (7/31, 23\%), and weight maintenance functions (7/31, 23\%). Various digital devices were also studied to collect these data in the included reviews, such as smart glasses, smartwatches, smart bracelets, smart shoes, and smart socks for measuring heart functions, gait pattern functions, and temperature. A substantial number (24/31, 77\%) of digital biomarkers were used as interventions. Moreover, wearables (22/31, 71\%) were the most common types of digital devices. Position sensors (21/31, 68\%) and heart rate sensors and pulse rate sensors (12/31, 39\%) were the most prevalent types of sensors used to acquire behavioral and physiological data in the SRs. Conclusions: In recent years, the clinical evidence concerning digital biomarkers has been systematically reviewed in a wide range of study populations, interventions, digital devices, and sensor technologies, with the dominance of physical activity and cardiac monitors. We used the World Health Organization's ICF tool for classifying behavioral and physiological data, which seemed to be an applicable tool to categorize the broad scope of digital biomarkers identified in this review. To understand the clinical value of digital biomarkers, the strength and quality of the evidence on their health consequences need to be systematically evaluated. ", doi="10.2196/35722", url="https://mhealth.jmir.org/2022/10/e35722", url="http://www.ncbi.nlm.nih.gov/pubmed/36279171" } @Article{info:doi/10.2196/39085, author="Parmenter, Belinda and Burley, Claire and Stewart, Courtney and Whife, Jesse and Champion, Katrina and Osman, Bridie and Newton, Nicola and Green, Olivia and Wescott, B. Annie and Gardner, A. Lauren and Visontay, Rachel and Birrell, Louise and Bryant, Zachary and Chapman, Cath and Lubans, R. David and Sunderland, Matthew and Slade, Tim and Thornton, Louise", title="Measurement Properties of Smartphone Approaches to Assess Physical Activity in Healthy Young People: Systematic Review", journal="JMIR Mhealth Uhealth", year="2022", month="Oct", day="21", volume="10", number="10", pages="e39085", keywords="smartphone", keywords="mobile phone", keywords="mHealth", keywords="prevention", keywords="risk", keywords="physical activity", keywords="sedentary behavior", keywords="young people", abstract="Background: Physical inactivity is a preventable risk factor for several chronic diseases and one of the driving forces behind the growing global burden of disease. Recent evidence has shown that interventions using mobile smartphone apps can promote a significant increase in physical activity (PA) levels. However, the accuracy and reliability of using apps is unknown. Objective: The aim of our review was to determine the accuracy and reliability of using mobile apps to measure PA levels in young people. We conducted a systematic review guided by PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Methods: Studies published from 2007 to 2020 were sourced from 8 databases---Ovid MEDLINE, Embase (Elsevier), Cochrane Library (Wiley), PsychINFO (EBSCOhost), CINAHL (EBSCOhost), Web of Science (Clarivate), SPORTDiscus (EBSCOhost), and IEEE Xplore Digital Library database. Studies were conducted in young people aged 10-24 years and without chronic illnesses, who evaluated a mobile app's ability to measure PA. Primary outcomes included validity, reliability, and responsiveness of the measurement approach. Duplicate screening was conducted for eligibility, data extraction, and assessing the risk of bias. Results were reported as a systematic review. The main physical activity measures evaluated for each study were the following: total PA time (min/day or min/week), total moderate to vigorous PA per week, daily step count, intensity measure (heart rate), and frequency measure (days per week). Results: Of the 149 identified studies, 5 met the inclusion criteria (322 participants, 176 female; mean age 14, SD 3 years). A total of 3 studies measured criterion validity and compared PA measured via apps against PA measured via an Actigraph accelerometer. The 2 studies that reported on construct validity identified a significant difference between self-reported PA and the objective measure. Only 1 of the 5 apps examined was available to the public, and although this app was highly accepted by young people, the app recorded PA to be significantly different to participants' self-reported PA. Conclusions: Overall, few studies assess the reliability, validity, and responsiveness of mobile apps to measure PA in healthy young people, with studies typically only reporting on one measurement property. Of the 3 studies that measured validity, all concluded that mobile phones were acceptable and valid tools. More research is needed into the validity and reliability of smartphone apps to measure PA levels in this population as well as in populations with other characteristics, including other age groups and those with chronic diseases. Trial Registration: PROSPERO CRD42019122242; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=122242 ", doi="10.2196/39085", url="https://mhealth.jmir.org/2022/10/e39085", url="http://www.ncbi.nlm.nih.gov/pubmed/36269659" } @Article{info:doi/10.2196/39532, author="Koch, Mara and Matzke, Ina and Huhn, Sophie and Gunga, Hanns-Christian and Maggioni, Anna Martina and Munga, Stephen and Obor, David and Si{\'e}, Ali and Boudo, Valentin and Bunker, Aditi and Dambach, Peter and B{\"a}rnighausen, Till and Barteit, Sandra", title="Wearables for Measuring Health Effects of Climate Change--Induced Weather Extremes: Scoping Review", journal="JMIR Mhealth Uhealth", year="2022", month="Sep", day="9", volume="10", number="9", pages="e39532", keywords="wearable", keywords="consumer-grade wearables", keywords="fitness trackers", keywords="climate change", keywords="heat", keywords="global health", keywords="public health", keywords="review", keywords="mobile phone", abstract="Background: Although climate change is one of the biggest global health threats, individual-level and short-term data on direct exposure and health impacts are still scarce. Wearable electronic devices (wearables) present a potential solution to this research gap. Wearables have become widely accepted in various areas of health research for ecological momentary assessment, and some studies have used wearables in the field of climate change and health. However, these studies vary in study design, demographics, and outcome variables, and existing research has not been mapped. Objective: In this review, we aimed to map existing research on wearables used to detect direct health impacts and individual exposure during climate change--induced weather extremes, such as heat waves or wildfires. Methods: We conducted a scoping review according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework and systematically searched 6 databases (PubMed [MEDLINE], IEEE Xplore, CINAHL [EBSCOhost], WoS, Scopus, Ovid [MEDLINE], and Google Scholar). The search yielded 1871 results. Abstracts and full texts were screened by 2 reviewers (MK and IM) independently using the inclusion and exclusion criteria. The inclusion criteria comprised studies published since 2010 that used off-the-shelf wearables that were neither invasive nor obtrusive to the user in the setting of climate change--related weather extremes. Data were charted using a structured form, and the study outcomes were narratively synthesized. Results: The review included 55,284 study participants using wearables in 53 studies. Most studies were conducted in upper--middle-income and high-income countries (50/53, 94\%) in urban environments (25/53, 47\%) or in a climatic chamber (19/53, 36\%) and assessed the health effects of heat exposure (52/53, 98\%). The majority reported adverse health effects of heat exposure on sleep, physical activity, and heart rate. The remaining studies assessed occupational heat stress or compared individual- and area-level heat exposure. In total, 26\% (14/53) of studies determined that all examined wearables were valid and reliable for measuring health parameters during heat exposure when compared with standard methods. Conclusions: Wearables have been used successfully in large-scale research to measure the health implications of climate change--related weather extremes. More research is needed in low-income countries and vulnerable populations with pre-existing conditions. In addition, further research could focus on the health impacts of other climate change--related conditions and the effectiveness of adaptation measures at the individual level to such weather extremes. ", doi="10.2196/39532", url="https://mhealth.jmir.org/2022/9/e39532", url="http://www.ncbi.nlm.nih.gov/pubmed/36083624" } @Article{info:doi/10.2196/33247, author="Aguiar, Maria and Trujillo, Maria and Chaves, Deisy and {\'A}lvarez, Roberto and Epelde, Gorka", title="mHealth Apps Using Behavior Change Techniques to Self-report Data: Systematic Review", journal="JMIR Mhealth Uhealth", year="2022", month="Sep", day="9", volume="10", number="9", pages="e33247", keywords="mobile health", keywords="mHealth", keywords="behavior change techniques", keywords="adherence", keywords="app", keywords="mobile health interventions", keywords="behavior", abstract="Background: The popularization of mobile health (mHealth) apps for public health or medical care purposes has transformed human life substantially, improving lifestyle behaviors and chronic condition management. Objective: This review aimed to identify behavior change techniques (BCTs) commonly used in mHealth, assess their effectiveness based on the evidence reported in interventions and reviews to highlight the most appropriate techniques to design an optimal strategy to improve adherence to data reporting, and provide recommendations for future interventions and research. Methods: We performed a systematic review of studies published between 2010 and 2021 in relevant scientific databases to identify and analyze mHealth interventions using BCTs that evaluated their effectiveness in terms of user adherence. Search terms included a mix of general (eg, data, information, and adherence), computer science (eg, mHealth and BCTs), and medicine (eg, personalized medicine) terms. Results: This systematic review included 24 studies and revealed that the most frequently used BCTs in the studies were feedback and monitoring (n=20), goals and planning (n=14), associations (n=14), shaping knowledge (n=12), and personalization (n=7). However, we found mixed effectiveness of the techniques in mHealth outcomes, having more effective than ineffective outcomes in the evaluation of apps implementing techniques from the feedback and monitoring, goals and planning, associations, and personalization categories, but we could not infer causality with the results and suggest that there is still a need to improve the use of these and many common BCTs for better outcomes. Conclusions: Personalization, associations, and goals and planning techniques were the most used BCTs in effective trials regarding adherence to mHealth apps. However, they are not necessarily the most effective since there are studies that use these techniques and do not report significant results in the proposed objectives; there is a notable overlap of BCTs within implemented app components, suggesting a need to better understand best practices for applying (a combination of) such techniques and to obtain details on the specific BCTs used in mHealth interventions. Future research should focus on studies with longer follow-up periods to determine the effectiveness of mHealth interventions on behavior change to overcome the limited evidence in the current literature, which has mostly small-sized and single-arm experiments with a short follow-up period. ", doi="10.2196/33247", url="https://mhealth.jmir.org/2022/9/e33247", url="http://www.ncbi.nlm.nih.gov/pubmed/36083606" } @Article{info:doi/10.2196/35727, author="Bube, Benjamin and Zan{\'o}n, Baruque Bruno and Lara Palma, Mar{\'i}a Ana and Klocke, Heinrich", title="Wearable Devices in Diving: Scoping Review", journal="JMIR Mhealth Uhealth", year="2022", month="Sep", day="6", volume="10", number="9", pages="e35727", keywords="wearable device", keywords="underwater communication", keywords="head-up display", keywords="safety device", keywords="scuba diving", keywords="free diving", abstract="Background: Wearables and their benefits for the safety and well-being of users have been widely studied and have had an enormous impact on the general development of these kinds of devices. Yet, the extent of research into the use and impact of wearable devices in the underwater environment is comparatively low. In the past 15 years, there has been an increased interest in research into wearables that are used underwater, as the use of such wearables has steadily grown over time. However, there has so far been no clear indication in the literature about the direction in which efforts for the design and construction of underwater wearable devices are developing. Therefore, the analysis presented in this scoping review establishes a good and powerful basis for the further development and orientation of current underwater wearables within the field. Objective: In this scoping review, we targeted wearable devices for underwater use to make a comprehensive map of their capabilities and features and discuss the general direction of the development of underwater wearables and the orientation of research into novel prototypes of these kinds of devices. Methods: In September 2021, we conducted an extensive search for existing literature on 4 databases and for grey literature to identify developed prototypes and early-stage products that were described and tested in water, could be worn and interacted with (eg, displays, buttons, etc), and were fully functional without external equipment. The studies were written in English, came from peer-reviewed academic sources, and were published between 2005 and 2021. We reviewed each title and abstract. The data extraction process was carried out by one author and verified by another author. Results: In total, 36 relevant studies were included. Among these, 4 different categories were identified; 18 studies dealt primarily with safety devices, 9 dealt with underwater communication devices, 7 dealt with head-up displays, and 2 dealt with underwater human-computer interaction approaches. Although the safety devices seemed to have gained the most interest at the time of this study, a clear trend toward underwater communication wearables was identified. Conclusions: This review sought to provide a first insight into the possibilities and challenges of the technologies that have been used in and for wearable devices that are meant for use in the underwater environment. Among these, underwater communication technologies have had the most significant influence on future developments. Moreover, a topic that has not received enough attention but should be further addressed is human-computer interaction. By developing underwater wearables that cover 2 or more of the technology categories that we identified, the extent of the benefits of such devices can be significantly increased in the future. ", doi="10.2196/35727", url="https://mhealth.jmir.org/2022/9/e35727", url="http://www.ncbi.nlm.nih.gov/pubmed/36066926" } @Article{info:doi/10.2196/39682, author="Rintala, Aki and Rantalainen, Roy and Kaksonen, Anu and Luomajoki, Hannu and Kauranen, Kari", title="mHealth Apps for Low Back Pain Self-management: Scoping Review", journal="JMIR Mhealth Uhealth", year="2022", month="Aug", day="26", volume="10", number="8", pages="e39682", keywords="low back pain", keywords="mobile health", keywords="mHealth", keywords="app", keywords="disability", keywords="self-management", keywords="mobile phone", abstract="Background: The role of self-management in health promotion, as well as prevention and rehabilitation, is increasing through the use of mobile health (mHealth) apps. Such mHealth apps are also increasingly being used for self-management of low back pain (LBP), but their effectiveness has not been sufficiently explored. Objective: The aim of this scoping review was to provide an overview of the literature on self-management mHealth apps and their effects on the levels of pain and disability in people with LBP. Methods: We applied the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) methodology, including a priori research questions. A literature search was conducted in 2 databases (PubMed and PEDro) for studies published between January 1, 2015, and June 17, 2021. Interventional, cohort, or case series studies with an interventional period were included if the mHealth app included built-in self-management content, the app was used for self-management for people with LBP, and the study reported outcomes regarding pain and disability in people with LBP. Results: In total, 7 studies were selected for the review with overall 2307 persons with LBP, of whom 1328 (57.56\%) were women. Among the studies (5/7, 71\%) that reported the type of pain, 85\% (390/459) of the participants were experiencing chronic LBP. A total of 5 different mHealth apps were identified, of which 4 contributed to a statistically significant reduction in LBP and clinically meaningful changes. Of the 7 studies, 4 (57\%) used 4 different assessments for disability, of which 3 (75\%) showed statistically significant improvements in the level of functional ability of participants in the experimental groups using an mHealth app with built-in self-management content for LBP. Conclusions: This scoping review supports the conclusion that people with LBP may benefit from mHealth apps that provide self-management content. However, the generalizability of the findings is limited because of heterogeneity in the pain characterization of the included participants and the intervention durations. More high-quality studies with longer follow-up periods to investigate personalized mHealth approaches are recommended for LBP self-management. ", doi="10.2196/39682", url="https://mhealth.jmir.org/2022/8/e39682", url="http://www.ncbi.nlm.nih.gov/pubmed/36018713" } @Article{info:doi/10.2196/35657, author="Madujibeya, Ifeanyi and Lennie, Terry and Aroh, Adaeze and Chung, L. Misook and Moser, Debra", title="Measures of Engagement With mHealth Interventions in Patients With Heart Failure: Scoping Review", journal="JMIR Mhealth Uhealth", year="2022", month="Aug", day="22", volume="10", number="8", pages="e35657", keywords="heart failure", keywords="mobile health interventions", keywords="mHealth interventions", keywords="patient engagement", keywords="system usage data", keywords="heart failure outcomes", keywords="mobile phone", abstract="Background: Despite the potential of mobile health (mHealth) interventions to facilitate the early detection of signs of heart failure (HF) decompensation and provide personalized management of symptoms, the outcomes of such interventions in patients with HF have been inconsistent. As engagement with mHealth is required for interventions to be effective, poor patient engagement with mHealth interventions may be associated with mixed evidence. It is crucial to understand how engagement with mHealth interventions is measured in patients with HF, and the effects of engagement on HF outcomes. Objective: In this review, we aimed to describe measures of patient engagement with mHealth interventions and the effects of engagement on HF outcomes. Methods: We conducted a systematic literature search in 7 databases for relevant studies published in the English language from 2009 to September 2021 and reported the descriptive characteristics of the studies. We used content analysis to identify themes that described patient engagement with mHealth interventions in the qualitative studies included in the review. Results: We synthesized 32 studies that operationalized engagement with mHealth interventions in 4771 patients with HF (3239/4771, 67.88\%, male), ranging from a sample of 7 to 1571 (median 53.3) patients, followed for a median duration of 90 (IQR 45-180) days. Patient engagement with mHealth interventions was measured only quantitatively based on system usage data in 72\% (23/32) of the studies, only qualitatively based on data from semistructured interviews and focus groups in 6\% (2/32) of studies, and by a combination of both quantitative and qualitative data in 22\% (7/32) of studies. System usage data were evaluated using 6 metrics of engagement: number of physiological parameters transmitted (19/30, 63\% studies), number of HF questionnaires completed (2/30, 7\% studies), number of log-ins (4/30, 13\% studies), number of SMS text message responses (1/30, 3\% studies), time spent (5/30, 17\% studies), and the number of features accessed and screen viewed (4/30, 13\% studies). There was a lack of consistency in how the system usage metrics were reported across studies. In total, 80\% of the studies reported only descriptive characteristics of system usage data. The emotional, cognitive, and behavioral domains of patient engagement were identified through qualitative studies. Patient engagement levels ranged from 45\% to 100\% and decreased over time. The effects of engagement on HF knowledge, self-care, exercise adherence, and HF hospitalization were inconclusive. Conclusions: The measures of patient engagement with mHealth interventions in patients with HF are underreported and lack consistency. The application of inferential analytical methods to engagement data is extremely limited. There is a need for a working group on mHealth that may consolidate the previous operational definitions of patient engagement into an optimal and standardized measure. ", doi="10.2196/35657", url="https://mhealth.jmir.org/2022/8/e35657", url="http://www.ncbi.nlm.nih.gov/pubmed/35994345" } @Article{info:doi/10.2196/34734, author="Soulard, Julie and Carlin, Thomas and Knitza, Johannes and Vuillerme, Nicolas", title="Wearables for Measuring the Physical Activity and Sedentary Behavior of Patients With Axial Spondyloarthritis: Systematic Review", journal="JMIR Mhealth Uhealth", year="2022", month="Aug", day="22", volume="10", number="8", pages="e34734", keywords="axial spondyloarthritis", keywords="rheumatology", keywords="physical activity", keywords="sedentary behavior", keywords="objective measures", keywords="wearable", keywords="mobile health", keywords="mHealth", keywords="eHealth", keywords="systematic review", keywords="mobile phone", abstract="Background: Axial spondyloarthritis (axSpA) is an inflammatory rheumatic disease associated with chronic back pain and restricted mobility and physical function. Increasing physical activity is a viable strategy for improving the health and quality of life of patients with axSpA. Thus, quantifying physical activity and sedentary behavior in this population is relevant to clinical outcomes and disease management. However, to the best of our knowledge, no systematic review to date has identified and synthesized the available evidence on the use of wearable devices to objectively measure the physical activity or sedentary behavior of patients with axSpA. Objective: This study aimed to review the literature on the use of wearable activity trackers as outcome measures for physical activity and sedentary behavior in patients with axSpA. Methods: PubMed, PEDro, and Cochrane electronic databases were searched in July 2021 for relevant original articles, with no limits on publication dates. Studies were included if they were original articles, targeted adults with a diagnosis of axSpA, and reported wearable device--measured physical activity or sedentary behavior among patients with axSpA. Data regarding the study's characteristics, the sample description, the methods used for measuring physical activity and sedentary behavior (eg, wearable devices, assessment methods, and outcomes), and the main results of the physical activity and sedentary behavior assessments were extracted. Results: A total of 31 studies were initially identified; 13 (13/31, 42\%) met the inclusion criteria, including 819 patients with axSpA. All the studies used accelerometer-based wearable devices to assess physical activity. Of the 13 studies, 4 (4/31, 31\%) studies also reported outcomes related to sedentary behavior. Wearable devices were secured on the wrists (3/13 studies, 23\%), lower back (3/13, 23\%), right hip (3/13, 23\%), waist (2/13, 15\%), anterior thigh (1/13, 8\%), or right arm (1/13, 8\%). The methods for reporting physical activity and sedentary behavior were heterogeneous. Approximately 77\% (10/13) of studies had a monitoring period of 1 week, including weekend days. Conclusions: To date, few studies have used wearable devices to quantify the physical activity and sedentary behavior of patients with axSpA. The methodologies and results were heterogeneous, and none of these studies assessed the psychometric properties of these wearables in this specific population. Further investigation in this direction is needed before using wearable device--measured physical activity and sedentary behavior as outcome measures in intervention studies in patients with axSpA. Trial Registration: PROSPERO CRD42020182398; https://tinyurl.com/ec22jzkt International Registered Report Identifier (IRRID): RR2-10.2196/23359 ", doi="10.2196/34734", url="https://mhealth.jmir.org/2022/8/e34734", url="http://www.ncbi.nlm.nih.gov/pubmed/35994315" } @Article{info:doi/10.2196/37547, author="Martinko, Antonio and Karuc, Josip and Juri{\'c}, Petra and Podnar, Hrvoje and Sori{\'c}, Maroje", title="Accuracy and Precision of Consumer-Grade Wearable Activity Monitors for Assessing Time Spent in Sedentary Behavior in Children and Adolescents: Systematic Review", journal="JMIR Mhealth Uhealth", year="2022", month="Aug", day="9", volume="10", number="8", pages="e37547", keywords="accuracy", keywords="precision", keywords="sedentary behavior", keywords="children", keywords="adolescents", keywords="wearable activity monitor", keywords="eHealth", keywords="digital health", keywords="mobile health", keywords="mHealth", keywords="mobile phone", abstract="Background: A large number of wearable activity monitor models are released and used each year by consumers and researchers. As more studies are being carried out on children and adolescents in terms of sedentary behavior (SB) assessment, knowledge about accurate and precise monitoring devices becomes increasingly important. Objective: The main aim of this systematic review was to investigate and communicate findings on the accuracy and precision of consumer-grade physical activity monitors in assessing the time spent in SB in children and adolescents. Methods: Searches of PubMed (MEDLINE), Scopus, SPORTDiscus (full text), ProQuest, Open Access Theses and Dissertations, DART Europe E-theses Portal, and Networked Digital Library of Theses and Dissertations electronic databases were performed. All relevant studies that compared different types of consumer-grade monitors using a comparison method in the assessment of SB, published in European languages from 2015 onward were considered for inclusion. The risk of bias was estimated using Consensus-Based Standards for the Selection of Health Status Measurement Instruments. For enabling comparisons of accuracy measures within the studied outcome domain, measurement accuracy interpretation was based on group mean or percentage error values and 90\% CI. Acceptable limits were predefined as --10\% to +10\% error in controlled and free-living settings. For determining the number of studies with group error percentages that fall within or outside one of the sides from previously defined acceptable limits, two 1-sided tests of equivalence were carried out, and the direction of measurement error was examined. Results: A total of 8 studies complied with the predefined inclusion criteria, and 3 studies provided acceptable data for quantitative analyses. In terms of the presented accuracy comparisons, 14 were subsequently identified, with 6 of these comparisons being acceptable in terms of quantitative analysis. The results of the Cochran Q test indicated that the included studies did not share a common effect size (Q5=82.86; P<.001). I2, which represents the percentage of total variation across studies due to heterogeneity, amounted to 94\%. The summary effect size based on the random effects model was not statistically significant (effect size=14.36, SE 12.04, 90\% CI ?5.45 to 34.17; P=.23). According to the equivalence test results, consumer-grade physical activity monitors did not generate equivalent estimates of SB in relation to the comparison methods. Majority of the studies (3/7, 43\%) that reported the mean absolute percentage errors have reported values of <30\%. Conclusions: This is the first study that has attempted to synthesize available evidence on the accuracy and precision of consumer-grade physical activity monitors in measuring SB in children and adolescents. We found very few studies on the accuracy and almost no evidence on the precision of wearable activity monitors. The presented results highlight the large heterogeneity in this area of research. Trial Registration: PROSPERO CRD42021251922; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=251922 ", doi="10.2196/37547", url="https://mhealth.jmir.org/2022/8/e37547", url="http://www.ncbi.nlm.nih.gov/pubmed/35943763" } @Article{info:doi/10.2196/28153, author="Alaslawi, Hessah and Berrou, Ilhem and Al Hamid, Abdullah and Alhuwail, Dari and Aslanpour, Zoe", title="Diabetes Self-management Apps: Systematic Review of Adoption Determinants and Future Research Agenda", journal="JMIR Diabetes", year="2022", month="Jul", day="28", volume="7", number="3", pages="e28153", keywords="diabetes self-management", keywords="mobile apps", keywords="mobile health", keywords="mHealth adoption", keywords="mobile phone", abstract="Background: Most diabetes management involves self-management. Effective self-management of the condition improves diabetes control, reduces the risk of complications, and improves patient outcomes. Mobile apps for diabetes self-management (DSM) can enhance patients' self-management activities. However, they are only effective if clinicians recommend them, and patients use them. Objective: This study aimed to explore the determinants of DSM apps' use by patients and their recommendations by health care professionals (HCPs). It also outlines the future research agenda for using DSM apps in diabetes care. Methods: We systematically reviewed the factors affecting the adoption of DSM apps by both patients and HCPs. Searches were performed using PubMed, Scopus, CINAHL, Cochrane Central, ACM, and Xplore digital libraries for articles published from 2008 to 2020. The search terms were diabetes, mobile apps, and self-management. Relevant data were extracted from the included studies and analyzed using a thematic synthesis approach. Results: A total of 28 studies met the inclusion criteria. We identified a range of determinants related to patients' and HCPs' characteristics, experiences, and preferences. Young female patients were more likely to adopt DSM apps. Patients' perceptions of the benefits of apps, ease of use, and recommendations by patients and other HCPs strongly affect their intention to use DSM apps. HCPs are less likely to recommend these apps if they do not perceive their benefits and may not recommend their use if they are unaware of their existence or credibility. Young and technology-savvy HCPs were more likely to recommend DSM apps. Conclusions: Despite the potential of DSM apps to improve patients' self-care activities and diabetes outcomes, HCPs and patients remain hesitant to use them. However, the COVID-19 pandemic may hasten the integration of technology into diabetes care. The use of DSM apps may become a part of the new normal. ", doi="10.2196/28153", url="https://diabetes.jmir.org/2022/3/e28153", url="http://www.ncbi.nlm.nih.gov/pubmed/35900826" } @Article{info:doi/10.2196/35684, author="Kang, Singh Harjeevan and Exworthy, Mark", title="Wearing the Future---Wearables to Empower Users to Take Greater Responsibility for Their Health and Care: Scoping Review", journal="JMIR Mhealth Uhealth", year="2022", month="Jul", day="13", volume="10", number="7", pages="e35684", keywords="wearable", keywords="device", keywords="tracker", keywords="activity tracker", keywords="fitness tracker", keywords="technology", keywords="MedTech", keywords="HealthTech", keywords="sensor", keywords="monitor", keywords="gadget", keywords="smartwatch", keywords="empowerment", keywords="self-care", keywords="management", keywords="behavior", keywords="responsibility", keywords="attitude", keywords="personalization", keywords="mobile phone", keywords="self-management", keywords="smartphone", keywords="wearable electronic devices", keywords="health promotion", keywords="health behavior", keywords="mHealth", keywords="digital health", keywords="health care wearables", keywords="scoping review", abstract="Background: Wearables refer to devices that are worn by individuals. In the health care field, wearables may assist with individual monitoring and diagnosis. In fact, the potential for wearable technology to assist with health care has received recognition from health systems around the world, including a place in the strategic Long Term Plan shared by the National Health Service in England. However, wearables are not limited to specialist medical devices used by patients. Leading technology companies, including Apple, have been exploring the capabilities of wearable health technology for health-conscious consumers. Despite advancements in wearable health technology, research is yet to be conducted on wearables and empowerment. Objective: This study aimed to identify, summarize, and synthesize knowledge on how wearable health technology can empower individuals to take greater responsibility for their health and care. Methods: This study was a scoping review with thematic analysis and narrative synthesis. Relevant guidance, such as the Arksey and O'Malley framework, was followed. In addition to searching gray literature, we searched MEDLINE, EMBASE, PsycINFO, HMIC, and Cochrane Library. Studies were included based on the following selection criteria: publication in English, publication in Europe or the United States, focus on wearables, relevance to the research, and the availability of the full text. Results: After identifying 1585 unique records and excluding papers based on the selection criteria, 20 studies were included in the review. On analysis of these 20 studies, 3 main themes emerged: the potential barriers to using wearables, the role of providers and the benefits to providers from promoting the use of wearables, and how wearables can drive behavior change. Conclusions: Considerable literature findings suggest that wearables can empower individuals by assisting with diagnosis, behavior change, and self-monitoring. However, greater adoption of wearables and engagement with wearable devices depend on various factors, including promotion and support from providers to encourage uptake; increased short-term investment to upskill staff, especially in the area of data analysis; and overcoming the barriers to use, particularly by improving device accuracy. Acting on these suggestions will require investment and constructive input from key stakeholders, namely users, health care professionals, and designers of the technology. As advancements in technology to make wearables viable health care devices have only come about recently, further studies will be important for measuring the effectiveness of wearables in empowering individuals. The investigation of user outcomes through large-scale studies would also be beneficial. Nevertheless, a significant challenge will be in the publication of research to keep pace with rapid developments related to wearable health technology. ", doi="10.2196/35684", url="https://mhealth.jmir.org/2022/7/e35684", url="http://www.ncbi.nlm.nih.gov/pubmed/35830222" } @Article{info:doi/10.2196/34767, author="Kassavou, Aikaterini and Wang, Michael and Mirzaei, Venus and Shpendi, Sonia and Hasan, Rana", title="The Association Between Smartphone App--Based Self-monitoring of Hypertension-Related Behaviors and Reductions in High Blood Pressure: Systematic Review and Meta-analysis", journal="JMIR Mhealth Uhealth", year="2022", month="Jul", day="12", volume="10", number="7", pages="e34767", keywords="self-monitoring", keywords="smartphone apps", keywords="behavior change", keywords="hypertension", keywords="blood pressure", keywords="mobile health", keywords="mHealth", keywords="mobile app", keywords="self-management", keywords="lifestyle", abstract="Background: Self-monitoring of behavior can support lifestyle modifications; however, we do not know whether such interventions are effective in supporting positive changes in hypertension-related health behaviors and thus in reducing blood pressure in patients treated for hypertension. Objective: This systematic literature review evaluates the extent to which smartphone app--based self-monitoring of health behavior supports reductions in blood pressure and changes in hypertension-related behaviors. It also explores the behavioral components that might explain intervention effectiveness. Methods: A systematic search of 7 databases was conducted in August 2021. Article screening, study and intervention coding, and data extraction were completed independently by reviewers. The search strategy was developed using keywords from previous reviews and relevant literature. Trials involving adults, published after the year 2000, and in the English language were considered for inclusion. The random-effects meta-analysis method was used to account for the distribution of the effect across the studies. Results: We identified 4638 articles, of which 227 were included for full-text screening. A total of 15 randomized controlled trials were included in the review. In total, 7415 patients with hypertension were included in the meta-analysis. The results indicate that app-based behavioral self-monitoring interventions had a small but significant effect in reducing systolic blood pressure (SBP), on average, by 1.64 mmHg (95\% CI 2.73-0.55, n=7301; odds ratio [OR] 1.60, 95\% CI 0.74-3.42, n=114) and in improving changes in medication adherence behavior (standardized mean difference [SMD] 0.78, 95\% CI 0.22-1.34) compared to usual care or minimal intervention. The review found the intervention had a small effect on supporting improvements in healthy diet by changing habits related to high sodium food (SMD --0.44, 95\% CI --0.79 to --0.08) and a trend, although insignificant, toward supporting smoking cessation, low alcohol consumption, and better physical activity behaviors. A subgroup analysis found that behavioral self-monitoring interventions combined with tailored advice resulted in higher and significant changes in both SBP and diastolic blood pressure (DBP) in comparison to those not providing tailored advice (SBP: --2.92 mmHg, 95\% CI --3.94 to --1.90, n=3102 vs --0.72 mmHg, 95\% CI --1.67 to 0.23, n=4199, $\chi$2=9.65, P=.002; DBP: --2.05 mmHg, 95\% CI --3.10 to --1.01, n=968 vs 1.54 mmHg, 95\% CI --0.53 to 3.61, n=400, $\chi$2=9.19, P=.002). Conclusions: Self-monitoring of hypertension-related behaviors via smartphone apps combined with tailored advice has a modest but potentially clinically significant effect on blood pressure reduction. Future studies could use rigorous methods to explore its effects on supporting changes in both blood pressure and hypertension-related health behaviors to inform recommendations for policy making and service provision. Trial Registration: PROSPERO CRD42019136158; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=136158 ", doi="10.2196/34767", url="https://mhealth.jmir.org/2022/7/e34767", url="http://www.ncbi.nlm.nih.gov/pubmed/35819830" } @Article{info:doi/10.2196/38614, author="Lee, Peter and Kim, Heepyung and Kim, Yongshin and Choi, Woohyeok and Zitouni, Sami M. and Khandoker, Ahsan and Jelinek, F. Herbert and Hadjileontiadis, Leontios and Lee, Uichin and Jeong, Yong", title="Beyond Pathogen Filtration: Possibility of Smart Masks as Wearable Devices for Personal and Group Health and Safety Management", journal="JMIR Mhealth Uhealth", year="2022", month="Jun", day="21", volume="10", number="6", pages="e38614", keywords="smart mask", keywords="pathogen filtration", keywords="COVID-19", keywords="protective equipment", keywords="digital health", keywords="wearable", keywords="smart device", keywords="wearable device", keywords="sensor", keywords="health monitoring", doi="10.2196/38614", url="https://mhealth.jmir.org/2022/6/e38614", url="http://www.ncbi.nlm.nih.gov/pubmed/35679029" } @Article{info:doi/10.2196/29481, author="Praus, Friederike and Krzowski, Bartosz and Walther, Tabea and Gratzke, Christian and Balsam, Pawe? and Miernik, Arkadiusz and Pohlmann, Fabian Philippe", title="Smartphone Apps for Managing Antithrombotic Therapy: Scoping Literature Review", journal="JMIR Cardio", year="2022", month="Jun", day="21", volume="6", number="1", pages="e29481", keywords="anticoagulation", keywords="mobile app", keywords="telehealth", keywords="telemedicine", keywords="mHealth", keywords="smartphone", keywords="educational apps", keywords="digital tools", keywords="physician support", abstract="Background: Antithrombotic therapy is complex and requires informed decisions and high therapy adherence. Several mobile phone apps exist to either support physicians in the management of antithrombotic therapies or to educate and support patients. For the majority of these apps, both their medical evidence and their development background are unknown. Objective: This review aims to investigate the available literature describing high-quality apps for managing antithrombotic therapy based on professional scientific information. Methods: Keywords and Medical Subject Heading terms were used to search MEDLINE via PubMed and Ovid between December 2019 and January 2022. Inclusion criteria were the availability of full text and publications in the English language. Apps that solely focused on atrial fibrillation were excluded. Qualitative findings were thematically synthesized and reported narratively. Results: Out of 149 identified records, 32 were classified as eligible. We identified four groups: (1) apps for patients supporting self-management of vitamin K antagonists, (2) apps for patients increasing therapy adherence, (3) educational apps for patients, and (4) apps for physicians in supporting guideline adherence. Conclusions: Throughout the evaluated data, patients from all age groups receiving antithrombotic drugs expressed the desire for a digital tool that could support their therapy management. In addition, physicians using mobile guideline-based apps may have contributed to decreased adverse event rates among their patients. In general, digital apps encompassing both user-friendly designs and scientific backgrounds may enhance the safety of antithrombotic therapies. However, our evaluation did not identify any apps that addressed all antithrombotic drugs in combination with perioperative stratification strategies. Currently, strict regulations for smartphone apps seem to negatively affect the development of new apps. Therefore, new legal policies for medical digital apps are urgently needed. ", doi="10.2196/29481", url="https://cardio.jmir.org/2022/1/e29481", url="http://www.ncbi.nlm.nih.gov/pubmed/35727608" } @Article{info:doi/10.2196/36377, author="Giurgiu, Marco and Timm, Irina and Becker, Marlissa and Schmidt, Steffen and Wunsch, Kathrin and Nissen, Rebecca and Davidovski, Denis and Bussmann, J. Johannes B. and Nigg, R. Claudio and Reichert, Markus and Ebner-Priemer, W. Ulrich and Woll, Alexander and von Haaren-Mack, Birte", title="Quality Evaluation of Free-living Validation Studies for the Assessment of 24-Hour Physical Behavior in Adults via Wearables: Systematic Review", journal="JMIR Mhealth Uhealth", year="2022", month="Jun", day="9", volume="10", number="6", pages="e36377", keywords="wearables", keywords="validation", keywords="sedentary behavior", keywords="physical activity", keywords="sleep", abstract="Background: Wearable technology is a leading fitness trend in the growing commercial industry and an established method for collecting 24-hour physical behavior data in research studies. High-quality free-living validation studies are required to enable both researchers and consumers to make guided decisions on which study to rely on and which device to use. However, reviews focusing on the quality of free-living validation studies in adults are lacking. Objective: This study aimed to raise researchers' and consumers' attention to the quality of published validation protocols while aiming to identify and compare specific consistencies or inconsistencies between protocols. We aimed to provide a comprehensive and historical overview of which wearable devices have been validated for which purpose and whether they show promise for use in further studies. Methods: Peer-reviewed validation studies from electronic databases, as well as backward and forward citation searches (1970 to July 2021), with the following, required indicators were included: protocol must include real-life conditions, outcome must belong to one dimension of the 24-hour physical behavior construct (intensity, posture or activity type, and biological state), the protocol must include a criterion measure, and study results must be published in English-language journals. The risk of bias was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool with 9 questions separated into 4 domains (patient selection or study design, index measure, criterion measure, and flow and time). Results: Of the 13,285 unique search results, 222 (1.67\%) articles were included. Most studies (153/237, 64.6\%) validated an intensity measure outcome such as energy expenditure. However, only 19.8\% (47/237) validated biological state and 15.6\% (37/237) validated posture or activity-type outcomes. Across all studies, 163 different wearables were identified. Of these, 58.9\% (96/163) were validated only once. ActiGraph GT3X/GT3X+ (36/163, 22.1\%), Fitbit Flex (20/163, 12.3\%), and ActivPAL (12/163, 7.4\%) were used most often in the included studies. The percentage of participants meeting the quality criteria ranged from 38.8\% (92/237) to 92.4\% (219/237). On the basis of our classification tree to evaluate the overall study quality, 4.6\% (11/237) of studies were classified as low risk. Furthermore, 16\% (38/237) of studies were classified as having some concerns, and 72.9\% (173/237) of studies were classified as high risk. Conclusions: Overall, free-living validation studies of wearables are characterized by low methodological quality, large variability in design, and focus on intensity. Future research should strongly aim at biological state and posture or activity outcomes and strive for standardized protocols embedded in a validation framework. Standardized protocols for free-living validation embedded in a framework are urgently needed to inform and guide stakeholders (eg, manufacturers, scientists, and consumers) in selecting wearables for self-tracking purposes, applying wearables in health studies, and fostering innovation to achieve improved validity. ", doi="10.2196/36377", url="https://mhealth.jmir.org/2022/6/e36377", url="http://www.ncbi.nlm.nih.gov/pubmed/35679106" } @Article{info:doi/10.2196/35053, author="Bhatt, Paras and Liu, Jia and Gong, Yanmin and Wang, Jing and Guo, Yuanxiong", title="Emerging Artificial Intelligence--Empowered mHealth: Scoping Review", journal="JMIR Mhealth Uhealth", year="2022", month="Jun", day="9", volume="10", number="6", pages="e35053", keywords="mobile health units", keywords="telemedicine", keywords="machine learning", keywords="artificial intelligence", keywords="review literature as topic", abstract="Background: Artificial intelligence (AI) has revolutionized health care delivery in recent years. There is an increase in research for advanced AI techniques, such as deep learning, to build predictive models for the early detection of diseases. Such predictive models leverage mobile health (mHealth) data from wearable sensors and smartphones to discover novel ways for detecting and managing chronic diseases and mental health conditions. Objective: Currently, little is known about the use of AI-powered mHealth (AIM) settings. Therefore, this scoping review aims to map current research on the emerging use of AIM for managing diseases and promoting health. Our objective is to synthesize research in AIM models that have increasingly been used for health care delivery in the last 2 years. Methods: Using Arksey and O'Malley's 5-point framework for conducting scoping reviews, we reviewed AIM literature from the past 2 years in the fields of biomedical technology, AI, and information systems. We searched 3 databases, PubsOnline at INFORMS, e-journal archive at MIS Quarterly, and Association for Computing Machinery (ACM) Digital Library using keywords such as ``mobile healthcare,'' ``wearable medical sensors,'' ``smartphones'', and ``AI.'' We included AIM articles and excluded technical articles focused only on AI models. We also used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) technique for identifying articles that represent a comprehensive view of current research in the AIM domain. Results: We screened 108 articles focusing on developing AIM models for ensuring better health care delivery, detecting diseases early, and diagnosing chronic health conditions, and 37 articles were eligible for inclusion, with 31 of the 37 articles being published last year (76\%). Of the included articles, 9 studied AI models to detect serious mental health issues, such as depression and suicidal tendencies, and chronic health conditions, such as sleep apnea and diabetes. Several articles discussed the application of AIM models for remote patient monitoring and disease management. The considered primary health concerns belonged to 3 categories: mental health, physical health, and health promotion and wellness. Moreover, 14 of the 37 articles used AIM applications to research physical health, representing 38\% of the total studies. Finally, 28 out of the 37 (76\%) studies used proprietary data sets rather than public data sets. We found a lack of research in addressing chronic mental health issues and a lack of publicly available data sets for AIM research. Conclusions: The application of AIM models for disease detection and management is a growing research domain. These models provide accurate predictions for enabling preventive care on a broader scale in the health care domain. Given the ever-increasing need for remote disease management during the pandemic, recent AI techniques, such as federated learning and explainable AI, can act as a catalyst for increasing the adoption of AIM and enabling secure data sharing across the health care industry. ", doi="10.2196/35053", url="https://mhealth.jmir.org/2022/6/e35053", url="http://www.ncbi.nlm.nih.gov/pubmed/35679107" } @Article{info:doi/10.2196/33489, author="Shah, Nirali and Costello, Kerry and Mehta, Akshat and Kumar, Deepak", title="Applications of Digital Health Technologies in Knee Osteoarthritis: Narrative Review", journal="JMIR Rehabil Assist Technol", year="2022", month="Jun", day="8", volume="9", number="2", pages="e33489", keywords="digital health", keywords="knee osteoarthritis", keywords="knee replacement", keywords="mobile health", keywords="telemedicine", keywords="mobile phone", abstract="Background: With the increasing adoption of high-speed internet and mobile technologies by older adults, digital health is a promising modality to enhance clinical care for people with knee osteoarthritis (KOA), including those with knee replacement (KR). Objective: This study aimed to summarize the current use, cost-effectiveness, and patient and clinician perspectives of digital health for intervention delivery in KOA and KR. Methods: In this narrative review, search terms such as mobile health, smartphone, mobile application, mobile technology, ehealth, text message, internet, knee osteoarthritis, total knee arthroplasty, and knee replacement were used in the PubMed and Embase databases between October 2018 and February 2021. The search was limited to original articles published in the English language within the past 10 years. In total, 91 studies were included. Results: Digital health technologies such as websites, mobile apps, telephone calls, SMS text messaging, social media, videoconferencing, and custom multi-technology systems have been used to deliver interventions in KOA and KR populations. Overall, there was significant heterogeneity in the types and applications of digital health used in these populations. Digital patient education improved disease-related knowledge, especially when used as an adjunct to traditional methods of patient education for both KOA and KR. Digital health that incorporated person-specific motivational messages, biofeedback, or patient monitoring was more successful at improving physical activity than self-directed digital interventions for both KOA and KR. Many digital exercise interventions were found to be as effective as in-person physical therapy for people with KOA. Many digital exercise interventions for KR incorporated both in-person and web-based treatments (blended format), communication with clinicians, and multi-technology systems and were successful in improving knee range of motion and self-reported symptoms and reducing the length of hospital stays. All digital interventions that incorporated cognitive behavioral therapy or similar psychological interventions showed significant improvements in knee pain, function, and psychological health when compared with no treatment or traditional treatments for both KOA and KR. Although limited in number, studies have indicated that digital health may be cost-effective for these populations, especially when travel costs are considered. Finally, although patients with KOA and KR and clinicians had positive views on digital health, concerns related to privacy and security and concerns related to logistics and training were raised by patients and clinicians, respectively. Conclusions: For people with KOA and KR, many studies found digital health to be as effective as traditional treatments for patient education, physical activity, and exercise interventions. All digital interventions that incorporated cognitive behavioral therapy or similar psychological treatments were reported to result in significant improvements in patients with KOA and KR when compared with no treatment or traditional treatments. Overall, technologies that were blended and incorporated communication with clinicians, as well as biofeedback or patient monitoring, showed favorable outcomes. ", doi="10.2196/33489", url="https://rehab.jmir.org/2022/2/e33489", url="http://www.ncbi.nlm.nih.gov/pubmed/35675102" } @Article{info:doi/10.2196/30960, author="Zhang, Zhenming and Xia, Enjun and Huang, Jieping", title="Impact of the Moderating Effect of National Culture on Adoption Intention in Wearable Health Care Devices: Meta-analysis", journal="JMIR Mhealth Uhealth", year="2022", month="Jun", day="3", volume="10", number="6", pages="e30960", keywords="wearable health care devices", keywords="national culture", keywords="moderating effect", keywords="meta-analysis", abstract="Background: Wearable health care devices have not yet been commercialized on a large scale. Additionally, people in different countries have different utilization rates. Therefore, more in-depth studies on the moderating effect of national culture on adoption intention in wearable health care devices are necessary. Objective: This study aims to explore the summary results of the relationships between perceived usefulness and perceived ease of use with adoption intention in wearable health care devices and the impact of the moderating effect of national culture on these two relationships. Methods: We searched for studies published before September 2021 in the Web of Science, EBSCO, Engineering Village, China National Knowledge Infrastructure, IEEE Xplore, and Wiley Online Library databases. CMA (version 2.0, Biostat Inc) software was used to perform the meta-analysis. We conducted publication bias and heterogeneity tests on the data. The random-effects model was used to estimate the main effect size, and a sensitivity analysis was conducted. A meta-regression analysis was used to test the moderating effect of national culture. Results: This meta-analysis included 20 publications with a total of 6128 participants. Perceived usefulness (r=0.612, P<.001) and perceived ease of use (r=0.462, P<.001) positively affect adoption intention. The relationship between perceived usefulness and adoption intention is positively moderated by individualism/collectivism ($\beta$=.003, P<.001), masculinity/femininity ($\beta$=.008, P<.001) and indulgence/restraint ($\beta$=.005, P<.001), and negatively moderated by uncertainty avoidance ($\beta$=-.005, P<.001). The relationship between perceived ease of use and adoption intention is positively moderated by individualism/collectivism ($\beta$=.003, P<.001), masculinity/femininity ($\beta$=.006, P<.001) and indulgence/restraint ($\beta$=.009, P<.001), and negatively moderated by uncertainty avoidance ($\beta$=-.004, P<.001). Conclusions: This meta-analysis provided comprehensive evidence on the positive relationship between perceived usefulness and perceived ease of use with adoption intention and the moderating effect of national culture on these two relationships. Regarding the moderating effect, perceived usefulness and perceived ease of use have a greater impact on adoption intention for people in individualistic, masculine, low uncertainty avoidance, and indulgence cultures, respectively. ", doi="10.2196/30960", url="https://mhealth.jmir.org/2022/6/e30960", url="http://www.ncbi.nlm.nih.gov/pubmed/35657654" } @Article{info:doi/10.2196/35920, author="Baumann, Hannes and Fiedler, Janis and Wunsch, Kathrin and Woll, Alexander and Wollesen, Bettina", title="mHealth Interventions to Reduce Physical Inactivity and Sedentary Behavior in Children and Adolescents: Systematic Review and Meta-analysis of Randomized Controlled Trials", journal="JMIR Mhealth Uhealth", year="2022", month="May", day="11", volume="10", number="5", pages="e35920", keywords="health behavior change", keywords="individualization", keywords="sedentary behavior", keywords="physical activity", keywords="tailored interventions", keywords="personalized medicine", keywords="health app", keywords="mobile phone", abstract="Background: Children and adolescents increasingly do not meet physical activity (PA) recommendations. Hence, insufficient PA (IPA) and sedentary behavior (SB) among children and adolescents are relevant behavior change domains for using individualized mobile health (mHealth) interventions. Objective: This review and meta-analysis investigated the effectiveness of mHealth interventions on IPA and SB, with a special focus on the age and level of individualization. Methods: PubMed, Scopus, Web of Science, SPORTDiscus, and Cochrane Library were searched for randomized controlled trials published between January 2000 and March 2021. mHealth interventions for primary prevention in children and adolescents addressing behavior change related to IPA and SB were included. Included studies were compared for content characteristics and methodological quality and summarized narratively. In addition, a meta-analysis with a subsequent exploratory meta-regression examining the moderating effects of age and individualization on overall effectiveness was performed. Results: On the basis of the inclusion criteria, 1.3\% (11/828) of the preliminary identified studies were included in the qualitative synthesis, and 1.2\% (10/828) were included in the meta-analysis. Trials included a total of 1515 participants (mean age (11.69, SD 0.788 years; 65\% male and 35\% female) self-reported (3/11, 27\%) or device-measured (8/11, 73\%) health data on the duration of SB and IPA for an average of 9.3 (SD 5.6) weeks. Studies with high levels of individualization significantly decreased insufficient PA levels (Cohen d=0.33; 95\% CI 0.08-0.58; Z=2.55; P=.01), whereas those with low levels of individualization (Cohen d=?0.06; 95\% CI ?0.32 to 0.20; Z=0.48; P=.63) or targeting SB (Cohen d=?0.11; 95\% CI ?0.01 to 0.23; Z=1.73; P=.08) indicated no overall significant effect. The heterogeneity of the studies was moderate to low, and significant subgroup differences were found between trials with high and low levels of individualization ($\chi$21=4.0; P=.04; I2=75.2\%). Age as a moderator variable showed a small effect; however, the results were not significant, which might have been because of being underpowered. Conclusions: Evidence suggests that mHealth interventions for children and adolescents can foster moderate reductions in IPA but not SB. Moreover, individualized mHealth interventions to reduce IPA seem to be more effective for adolescents than for children. Although, to date, only a few mHealth studies have addressed inactive and sedentary young people, and their quality of evidence is moderate, these findings indicate the relevance of individualization on the one hand and the difficulties in reducing SB using mHealth interventions on the other. Trial Registration: PROSPERO CRD42020209417; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=209417 ", doi="10.2196/35920", url="https://mhealth.jmir.org/2022/5/e35920", url="http://www.ncbi.nlm.nih.gov/pubmed/35544294" } @Article{info:doi/10.2196/36284, author="Jacob, Christine and Sezgin, Emre and Sanchez-Vazquez, Antonio and Ivory, Chris", title="Sociotechnical Factors Affecting Patients' Adoption of Mobile Health Tools: Systematic Literature Review and Narrative Synthesis", journal="JMIR Mhealth Uhealth", year="2022", month="May", day="5", volume="10", number="5", pages="e36284", keywords="telemedicine", keywords="smartphone", keywords="mobile phone", keywords="electronic health record", keywords="public health practice", keywords="technology", keywords="perception", keywords="health education", keywords="mHealth", keywords="mobile health", keywords="telehealth", keywords="eHealth", keywords="patients", abstract="Background: Mobile health (mHealth) tools have emerged as a promising health care technology that may contribute to cost savings, better access to care, and enhanced clinical outcomes; however, it is important to ensure their acceptance and adoption to harness this potential. Patient adoption has been recognized as a key challenge that requires further exploration. Objective: The aim of this review was to systematically investigate the literature to understand the factors affecting patients' adoption of mHealth tools by considering sociotechnical factors (from technical, social, and health perspectives). Methods: A structured search was completed following the participants, intervention, comparators, and outcomes framework. We searched the MEDLINE, PubMed, Cochrane Library, and SAGE databases for studies published between January 2011 and July 2021 in the English language, yielding 5873 results, of which 147 studies met the inclusion criteria. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and the Cochrane Handbook were followed to ensure a systematic process. Extracted data were analyzed using NVivo (QSR International), with thematic analysis and narrative synthesis of emergent themes. Results: The technical factors affecting patients' adoption of mHealth tools were categorized into six key themes, which in turn were divided into 20 subthemes: usefulness, ease of use, data-related, monetary factors, technical issues, and user experience. Health-related factors were categorized into six key themes: the disease or health condition, the care team's role, health consciousness and literacy, health behavior, relation to other therapies, integration into patient journey, and the patients' insurance status. Social and personal factors were divided into three key clusters: demographic factors, personal characteristics, and social and cultural aspects; these were divided into 19 subthemes, highlighting the importance of considering these factors when addressing potential barriers to mHealth adoption and how to overcome them. Conclusions: This review builds on the growing body of research that investigates patients' adoption of mHealth services and highlights the complexity of the factors affecting adoption, including personal, social, technical, organizational, and health care aspects. We recommend a more patient-centered approach by ensuring the tools' fit into the overall patient journey and treatment plan, emphasizing inclusive design, and warranting comprehensive patient education and support. Moreover, empowering and mobilizing clinicians and care teams, addressing ethical data management issues, and focusing on health care policies may facilitate adoption. ", doi="10.2196/36284", url="https://mhealth.jmir.org/2022/5/e36284", url="http://www.ncbi.nlm.nih.gov/pubmed/35318189" } @Article{info:doi/10.2196/33261, author="Treadwell, R. Jonathan and Rouse, Benjamin and Reston, James and Fontanarosa, Joann and Patel, Neha and Mull, K. Nikhil", title="Consumer Devices for Patient-Generated Health Data Using Blood Pressure Monitors for Managing Hypertension: Systematic Review", journal="JMIR Mhealth Uhealth", year="2022", month="May", day="2", volume="10", number="5", pages="e33261", keywords="patient-generated health data", keywords="consumer devices", keywords="hypertension", keywords="blood pressure monitors", keywords="digital health", keywords="cardiovascular diseases", keywords="wearable devices", keywords="health information", keywords="mobile phone", abstract="Background: In the era of digital health information technology, there has been a proliferation of devices that collect patient-generated health data (PGHD), including consumer blood pressure (BP) monitors. Despite their widespread use, it remains unclear whether such devices can improve health outcomes. Objective: We performed a systematic review of the literature on consumer BP monitors that collect PGHD for managing hypertension to summarize their clinical impact on health and surrogate outcomes. We focused particularly on studies designed to measure the specific effect of using a BP monitor independent of cointerventions. We have also summarized the process and consumer experience outcomes. Methods: An information specialist searched PubMed, MEDLINE, and Embase for controlled studies on consumer BP monitors published up to May 12, 2020. We assessed the risk of bias using an adapted 9-item appraisal tool and performed a narrative synthesis of the results. Results: We identified 41 different types of BP monitors used in 49 studies included for review. Device engineers judged that 38 (92\%) of those devices were similar to the currently available consumer BP monitors. The median sample size was 222 (IQR 101-416) participants, and the median length of follow-up was 6 (IQR 3-12) months. Of the included studies, 18 (36\%) were designed to isolate the clinical effects of BP monitors; 6 of the 18 (33\%) studies evaluated health outcomes (eg, mortality, hospitalizations, and quality of life), and data on those outcomes were unclear. The lack of clarity was due to low event rates, short follow-up duration, and risk of bias. All 18 studies that isolated the effect of BP monitors measured both systolic and diastolic BP and generally demonstrated a decrease of 2 to 4 mm Hg in systolic BP and 1 to 3 mm Hg in diastolic BP compared with non--BP monitor groups. Adherence to using consumer BP monitors ranged from 38\% to 89\%, and ease of use and satisfaction ratings were generally high. Adverse events were infrequent, but there were a few technical problems with devices (eg, incorrect device alerts). Conclusions: Overall, BP monitors offer small benefits in terms of BP reduction; however, the health impact of these devices continues to remain unclear. Future studies are needed to examine the effectiveness of BP monitors that transmit data to health care providers. Additional data from implementation studies may help determine which components are critical for sustained BP improvement, which in turn may improve prescription decisions by clinicians and coverage decisions by policy makers. ", doi="10.2196/33261", url="https://mhealth.jmir.org/2022/5/e33261", url="http://www.ncbi.nlm.nih.gov/pubmed/35499862" } @Article{info:doi/10.2196/30517, author="Ribeiro, Ricardo and Trifan, Alina and Neves, R. Ant{\'o}nio J.", title="Lifelog Retrieval From Daily Digital Data: Narrative Review", journal="JMIR Mhealth Uhealth", year="2022", month="May", day="2", volume="10", number="5", pages="e30517", keywords="lifelog", keywords="lifelogging", keywords="information retrieval", keywords="image retrieval", keywords="computer vision", keywords="signal processing", keywords="event segmentation", keywords="mobile phone", abstract="Background: Over the past decade, the wide availability and small size of different types of sensors, together with the decrease in pricing, have allowed the acquisition of a substantial amount of data about a person's life in real time. These sensors can be incorporated into personal electronic devices available at a reasonable cost, such as smartphones and small wearable devices. They allow the acquisition of images, audio, location, physical activity, and physiological signals among other data. With these data, usually denoted as lifelog data, we can then analyze and understand personal experiences and behaviors. This process is called lifelogging. Objective: The objective of this paper was to present a narrative review of the existing literature about lifelogging over the past decade. To achieve this goal, we analyzed lifelogging applications used to retrieve relevant information from daily digital data, some of them with the purpose of monitoring and assisting people with memory issues and others designed for memory augmentation. We aimed for this review to be used by researchers to obtain a broad idea of the type of data used, methodologies, and applications available in this research field. Methods: We followed a narrative review methodology to conduct a comprehensive search for relevant publications in Google Scholar and Scopus databases using lifelog topic--related keywords. A total of 411 publications were retrieved and screened. Of these 411 publications, 114 (27.7\%) publications were fully reviewed. In addition, 30 publications were manually included based on our bibliographical knowledge of this research field. Results: From the 144 reviewed publications, a total of 113 (78.5\%) were selected and included in this narrative review based on content analysis. The findings of this narrative review suggest that lifelogs are prone to become powerful tools to retrieve memories or increase knowledge about an individual's experiences or behaviors. Several computational tools are already available for a considerable range of applications. These tools use multimodal data of different natures, with visual lifelogs being one of the most used and rich sources of information. Different approaches and algorithms to process these data are currently in use, as this review will unravel. Moreover, we identified several open questions and possible lines of investigation in lifelogging. Conclusions: The use of personal lifelogs can be beneficial to improve the quality of our life, as they can serve as tools for memory augmentation or for providing support to people with memory issues. Through the acquisition and analysis of lifelog data, lifelogging systems can create digital memories that can be potentially used as surrogate memory. Through this narrative review, we understand that contextual information can be extracted from lifelogs, which provides an understanding of the daily life of a person based on events, experiences, and behaviors. ", doi="10.2196/30517", url="https://mhealth.jmir.org/2022/5/e30517", url="http://www.ncbi.nlm.nih.gov/pubmed/35499858" } @Article{info:doi/10.2196/32557, author="Alhussein, Ghada and Hadjileontiadis, Leontios", title="Digital Health Technologies for Long-term Self-management of Osteoporosis: Systematic Review and Meta-analysis", journal="JMIR Mhealth Uhealth", year="2022", month="Apr", day="21", volume="10", number="4", pages="e32557", keywords="mHealth", keywords="digital health", keywords="osteoporosis", keywords="self-management", keywords="systematic review", keywords="meta-analysis", keywords="chronic disease", keywords="bone health", keywords="nutrition", keywords="physical activity", keywords="risk assessment", keywords="mobile phone", abstract="Background: Osteoporosis is the fourth most common chronic disease worldwide. The adoption of preventative measures and effective self-management interventions can help improve bone health. Mobile health (mHealth) technologies can play a key role in the care and self-management of patients with osteoporosis. Objective: This study presents a systematic review and meta-analysis of the currently available mHealth apps targeting osteoporosis self-management, aiming to determine the current status, gaps, and challenges that future research could address, as well as propose appropriate recommendations. Methods: A systematic review of all English articles was conducted, in addition to a survey of all apps available in iOS and Android app stores as of May 2021. A comprehensive literature search (2010 to May 2021) of PubMed, Scopus, EBSCO, Web of Science, and IEEE Xplore was conducted. Articles were included if they described apps dedicated to or useful for osteoporosis (targeting self-management, nutrition, physical activity, and risk assessment) delivered on smartphone devices for adults aged ?18 years. Of the 32 articles, a random effects meta-analysis was performed on 13 (41\%) studies of randomized controlled trials, whereas the 19 (59\%) remaining studies were only included in the narrative synthesis as they did not provide enough data. Results: In total, 3906 unique articles were identified. Of these 3906 articles, 32 (0.81\%) articles met the inclusion criteria and were reviewed in depth. The 32 studies comprised 14,235 participants, of whom, on average, 69.5\% (n=9893) were female, with a mean age of 49.8 (SD 17.8) years. The app search identified 23 relevant apps for osteoporosis self-management. The meta-analysis revealed that mHealth-supported interventions resulted in a significant reduction in pain (Hedges g ?1.09, 95\% CI ?1.68 to ?0.45) and disability (Hedges g ?0.77, 95\% CI ?1.59 to 0.05). The posttreatment effect of the digital intervention was significant for physical function (Hedges g 2.54, 95\% CI ?4.08 to 4.08) but nonsignificant for well-being (Hedges g 0.17, 95\% CI ?1.84 to 2.17), physical activity (Hedges g 0.09, 95\% CI ?0.59 to 0.50), anxiety (Hedges g ?0.29, 95\% CI ?6.11 to 5.53), fatigue (Hedges g ?0.34, 95\% CI ?5.84 to 5.16), calcium (Hedges g ?0.05, 95\% CI ?0.59 to 0.50), vitamin D intake (Hedges g 0.10, 95\% CI ?4.05 to 4.26), and trabecular score (Hedges g 0.06, 95\% CI ?1.00 to 1.12). Conclusions: Osteoporosis apps have the potential to support and improve the management of the disease and its symptoms; they also appear to be valuable tools for patients and health professionals. However, most of the apps that are currently available lack clinically validated evidence of their efficacy and focus on a limited number of symptoms. A more holistic and personalized approach within a cocreation design ecosystem is needed. Trial Registration: PROSPERO 2021 CRD42021269399; https://tinyurl.com/2sw454a9 ", doi="10.2196/32557", url="https://mhealth.jmir.org/2022/4/e32557", url="http://www.ncbi.nlm.nih.gov/pubmed/35451968" } @Article{info:doi/10.2196/29985, author="Garc{\'i}a-S{\'a}nchez, Sebasti{\'a}n and Somoza-Fern{\'a}ndez, Beatriz and de Lorenzo-Pinto, Ana and Ortega-Navarro, Cristina and Herranz-Alonso, Ana and Sanjurjo, Mar{\'i}a", title="Mobile Health Apps Providing Information on Drugs for Adult Emergency Care: Systematic Search on App Stores and Content Analysis", journal="JMIR Mhealth Uhealth", year="2022", month="Apr", day="20", volume="10", number="4", pages="e29985", keywords="emergency drugs", keywords="emergency medicine", keywords="emergency departments", keywords="emergency professionals", keywords="medication errors", keywords="drug characteristics", keywords="drug management", keywords="apps", keywords="mHealth", keywords="mobile health", keywords="digital health", keywords="smartphone", keywords="mobile phone", abstract="Background: Drug-referencing apps are among the most frequently used by emergency health professionals. To date, no study has analyzed the quantity and quality of apps that provide information on emergency drugs. Objective: This study aimed to identify apps designed to assist emergency professionals in managing drugs and to describe and analyze their characteristics. Methods: We performed an observational, cross-sectional, descriptive study of apps that provide information on drugs for adult emergency care. The iOS and Android platforms were searched in February 2021. The apps were independently evaluated by 2 hospital clinical pharmacists. We analyzed developer affiliation, cost, updates, user ratings, and number of downloads. We also evaluated the main topic (emergency drugs or emergency medicine), the number of drugs described, the inclusion of bibliographic references, and the presence of the following drug information: commercial presentations, usual dosage, dose adjustment for renal failure, mechanism of action, therapeutic indications, contraindications, interactions with other medicinal products, use in pregnancy and breastfeeding, adverse reactions, method of preparation and administration, stability data, incompatibilities, identification of high-alert medications, positioning in treatment algorithms, information about medication reconciliation, and cost. Results: Overall, 49 apps were identified. Of these 49 apps, 32 (65\%) were found on both digital platforms; 11 (22\%) were available only for Android, and 6 (12\%) were available only for iOS. In total, 41\% (20/49) of the apps required payment (ranging from {\texteuro}0.59 [US \$0.64] to {\texteuro}179.99 [US \$196.10]) and 22\% (11/49) of the apps were developed by non--health care professionals. The mean weighted user rating was 4.023 of 5 (SD 0.71). Overall, 45\% (22/49) of the apps focused on emergency drugs, and 55\% (27/49) focused on emergency medicine. More than half (29/47, 62\%) did not include bibliographic references or had not been updated for more than a year (29/49, 59\%). The median number of drugs was 66 (range 4 to >5000). Contraindications (26/47, 55\%) and adverse reactions (24/47, 51\%) were found in only half of the apps. Less than half of the apps addressed dose adjustment for renal failure (15/47, 32\%), interactions (10/47, 21\%), and use during pregnancy and breastfeeding (15/47, 32\%). Only 6\% (3/47) identified high-alert medications, and 2\% (1/47) included information about medication reconciliation. Health-related developer, main topic, and greater amount of drug information were not statistically associated with higher user ratings (P=.99, P=.09, and P=.31, respectively). Conclusions: We provide a comprehensive review of apps with information on emergency drugs for adults. Information on authorship, drug characteristics, and bibliographic references is frequently scarce; therefore, we propose recommendations to consider when developing an app of these characteristics. Future efforts should be made to increase the regulation of drug-referencing apps and to conduct a more frequent and documented review of their clinical content. ", doi="10.2196/29985", url="https://mhealth.jmir.org/2022/4/e29985", url="http://www.ncbi.nlm.nih.gov/pubmed/35442212" } @Article{info:doi/10.2196/35626, author="Chevance, Guillaume and Golaszewski, M. Natalie and Tipton, Elizabeth and Hekler, B. Eric and Buman, Matthew and Welk, J. Gregory and Patrick, Kevin and Godino, G. Job", title="Accuracy and Precision of Energy Expenditure, Heart Rate, and Steps Measured by Combined-Sensing Fitbits Against Reference Measures: Systematic Review and Meta-analysis", journal="JMIR Mhealth Uhealth", year="2022", month="Apr", day="13", volume="10", number="4", pages="e35626", keywords="wearables", keywords="activity monitors", keywords="physical activity", keywords="validity", keywords="accelerometry", abstract="Background: Although it is widely recognized that physical activity is an important determinant of health, assessing this complex behavior is a considerable challenge. Objective: The purpose of this systematic review and meta-analysis is to examine, quantify, and report the current state of evidence for the validity of energy expenditure, heart rate, and steps measured by recent combined-sensing Fitbits. Methods: We conducted a systematic review and Bland-Altman meta-analysis of validation studies of combined-sensing Fitbits against reference measures of energy expenditure, heart rate, and steps. Results: A total of 52 studies were included in the systematic review. Among the 52 studies, 41 (79\%) were included in the meta-analysis, representing 203 individual comparisons between Fitbit devices and a criterion measure (ie, n=117, 57.6\% for heart rate; n=49, 24.1\% for energy expenditure; and n=37, 18.2\% for steps). Overall, most authors of the included studies concluded that recent Fitbit models underestimate heart rate, energy expenditure, and steps compared with criterion measures. These independent conclusions aligned with the results of the pooled meta-analyses showing an average underestimation of ?2.99 beats per minute (k comparison=74), ?2.77 kcal per minute (k comparison=29), and ?3.11 steps per minute (k comparison=19), respectively, of the Fitbit compared with the criterion measure (results obtained after removing the high risk of bias studies; population limit of agreements for heart rate, energy expenditure, and steps: ?23.99 to 18.01, ?12.75 to 7.41, and ?13.07 to 6.86, respectively). Conclusions: Fitbit devices are likely to underestimate heart rate, energy expenditure, and steps. The estimation of these measurements varied by the quality of the study, age of the participants, type of activities, and the model of Fitbit. The qualitative conclusions of most studies aligned with the results of the meta-analysis. Although the expected level of accuracy might vary from one context to another, this underestimation can be acceptable, on average, for steps and heart rate. However, the measurement of energy expenditure may be inaccurate for some research purposes. ", doi="10.2196/35626", url="https://mhealth.jmir.org/2022/4/e35626", url="http://www.ncbi.nlm.nih.gov/pubmed/35416777" } @Article{info:doi/10.2196/34638, author="Qirtas, Muhammad Malik and Zafeiridi, Evi and Pesch, Dirk and White, Bantry Eleanor", title="Loneliness and Social Isolation Detection Using Passive Sensing Techniques: Scoping Review", journal="JMIR Mhealth Uhealth", year="2022", month="Apr", day="12", volume="10", number="4", pages="e34638", keywords="passive sensing", keywords="loneliness", keywords="social isolation", keywords="smartphone", keywords="sensors", keywords="wearables", keywords="monitoring", keywords="scoping review", keywords="eHealth", keywords="mHealth", keywords="mobile phone", abstract="Background: Loneliness and social isolation are associated with multiple health problems, including depression, functional impairment, and death. Mobile sensing using smartphones and wearable devices, such as fitness trackers or smartwatches, as well as ambient sensors, can be used to acquire data remotely on individuals and their daily routines and behaviors in real time. This has opened new possibilities for the early detection of health and social problems, including loneliness and social isolation. Objective: This scoping review aimed to identify and synthesize recent scientific studies that used passive sensing techniques, such as the use of in-home ambient sensors, smartphones, and wearable device sensors, to collect data on device users' daily routines and behaviors to detect loneliness or social isolation. This review also aimed to examine various aspects of these studies, especially target populations, privacy, and validation issues. Methods: A scoping review was undertaken, following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). Studies on the topic under investigation were identified through 6 databases (IEEE Xplore, Scopus, ACM, PubMed, Web of Science, and Embase). The identified studies were screened for the type of passive sensing detection methods for loneliness and social isolation, targeted population, reliability of the detection systems, challenges, and limitations of these detection systems. Results: After conducting the initial search, a total of 40,071 papers were identified. After screening for inclusion and exclusion criteria, 29 (0.07\%) studies were included in this scoping review. Most studies (20/29, 69\%) used smartphone and wearable technology to detect loneliness or social isolation, and 72\% (21/29) of the studies used a validated reference standard to assess the accuracy of passively collected data for detecting loneliness or social isolation. Conclusions: Despite the growing use of passive sensing technologies for detecting loneliness and social isolation, some substantial gaps still remain in this domain. A population heterogeneity issue exists among several studies, indicating that different demographic characteristics, such as age and differences in participants' behaviors, can affect loneliness and social isolation. In addition, despite extensive personal data collection, relatively few studies have addressed privacy and ethical issues. This review provides uncertain evidence regarding the use of passive sensing to detect loneliness and social isolation. Future research is needed using robust study designs, measures, and examinations of privacy and ethical concerns. ", doi="10.2196/34638", url="https://mhealth.jmir.org/2022/4/e34638", url="http://www.ncbi.nlm.nih.gov/pubmed/35412465" } @Article{info:doi/10.2196/32435, author="Wang, Wentao and Cheng, Jing and Song, Weijun and Shen, Yi", title="The Effectiveness of Wearable Devices as Physical Activity Interventions for Preventing and Treating Obesity in Children and Adolescents: Systematic Review and Meta-analysis", journal="JMIR Mhealth Uhealth", year="2022", month="Apr", day="8", volume="10", number="4", pages="e32435", keywords="wearable devices", keywords="obesity", keywords="children", keywords="adolescents", keywords="meta-analysis", abstract="Background: The prevalence of obesity in children and adolescents remains a global public health issue. Wearable devices may offer new opportunities for prevention and intervention in obesity. Previous systematic reviews have only examined the effect of the wearable device interventions on preventing and treating obesity in adults. However, no systematic review has provided an evaluation of wearable devices as physical activity interventions for preventing and treating obesity in children and adolescents. Objective: The purpose of this review and meta-analysis was to evaluate the effectiveness of wearable devices as physical activity interventions on obesity-related anthropometric outcomes in children and adolescents. Methods: Research articles retrieved from PubMed, EMBASE, Cochrane Library, Scopus, and EBSCO from inception to February 1, 2021, were reviewed. The search was designed to identify studies utilizing wearable devices for preventing and treating obesity in children and adolescents. The included studies were evaluated for risk of bias following the Cochrane recommendation. Meta-analyses were conducted to evaluate the effectiveness of wearable devices as physical activity interventions on body weight, body fat, BMI z-score (BMI-Z), BMI, and waist circumference. Subgroup analyses were performed to determine whether the characteristics of the interventions had an impact on the effect size. Results: A total of 12 randomized controlled trials (3227 participants) were selected for meta-analysis. Compared with the control group, wearable device interventions had statistically significant beneficial effects on BMI (mean difference [MD] --0.23; 95\% CI --0.43 to --0.03; P=.03; I2=2\%), BMI-Z (MD --0.07; 95\% CI --0.13 to --0.01; P=.01; I2=81\%), body weight (MD --1.08; 95\% CI --2.16 to --0.00; P=.05; I2=58\%), and body fat (MD --0.72; 95\% CI --1.19 to --0.25; P=.003; I2=5\%). However, no statistically significant effect was found on waist circumference (MD 0.55; 95\% CI --0.21 to 1.32; P=.16; I2=0\%). The subgroup analysis showed that for participants with overweight or obesity (MD --0.75; 95\% CI --1.18 to --0.31; P<.01; I2=0\%), in the short-term (MD --0.62; 95\% CI --1.03 to --0.21; P<.01; I2=0\%), wearable-based interventions (MD --0.56; 95\% CI --0.95 to --0.18; P<.01; I2=0\%) generally resulted in greater intervention effect size on BMI. Conclusions: Evidence from this meta-analysis shows that wearable devices as physical activity interventions may be useful for preventing and treating obesity in children and adolescents. Future research is needed to identify the most effective physical activity indicators of wearable devices to prevent and treat obesity in children and adolescents. ", doi="10.2196/32435", url="https://mhealth.jmir.org/2022/4/e32435", url="http://www.ncbi.nlm.nih.gov/pubmed/35394447" } @Article{info:doi/10.2196/35479, author="Antoun, Jumana and Itani, Hala and Alarab, Natally and Elsehmawy, Amir", title="The Effectiveness of Combining Nonmobile Interventions With the Use of Smartphone Apps With Various Features for Weight Loss: Systematic Review and Meta-analysis", journal="JMIR Mhealth Uhealth", year="2022", month="Apr", day="8", volume="10", number="4", pages="e35479", keywords="obesity", keywords="weight loss", keywords="mobile app", keywords="self-monitoring", keywords="behavioral", keywords="tracker", keywords="behavioral coaching", keywords="coach", keywords="dietitian", keywords="mobile phone", abstract="Background: The effectiveness of smartphone apps for weight loss is limited by the diversity of interventions that accompany such apps. This research extends the scope of previous systematic reviews by including 2 subgroup analyses based on nonmobile interventions that accompanied smartphone use and human-based versus passive behavioral interventions. Objective: The primary objective of this study is to systematically review and perform a meta-analysis of studies that evaluated the effectiveness of smartphone apps on weight loss in the context of other interventions combined with app use. The secondary objective is to measure the impact of different mobile app features on weight loss and mobile app adherence. Methods: We conducted a systematic review and meta-analysis of relevant studies after an extensive search of the PubMed, MEDLINE, and EBSCO databases from inception to January 31, 2022. Gray literature, such as abstracts and conference proceedings, was included. Working independently, 2 investigators extracted the data from the articles, resolving disagreements by consensus. All randomized controlled trials that used smartphone apps in at least 1 arm for weight loss were included. The weight loss outcome was the change in weight from baseline to the 3- and 6-month periods for each arm. Net change estimates were pooled across the studies using random-effects models to compare the intervention group with the control group. The risk of bias was assessed independently by 2 authors using the Cochrane Collaboration tool for assessing the risk of bias in randomized trials. Results: Overall, 34 studies were included that evaluated the use of a smartphone app in at least 1 arm. Compared with controls, the use of a smartphone app--based intervention showed a significant weight loss of --1.99 kg (95\% CI --2.19 to --1.79 kg; I2=81\%) at 3 months and --2.80 kg (95\% CI --3.03 to --2.56 kg; I2=91\%) at 6 months. In the subgroup analysis, based on the various intervention components that were added to the mobile app, the combination of the mobile app, tracker, and behavioral interventions showed a statistically significant weight loss of --2.09 kg (95\% CI --2.32 to --1.86 kg; I2=91\%) and --3.77 kg (95\% CI --4.05 to --3.49 kg; I2=90\%) at 3 and 6 months, respectively. When a behavioral intervention was present, only the combination of the mobile app with intensive behavior coaching or feedback by a human coach showed a statistically significant weight loss of --2.03 kg (95\% CI --2.80 to --1.26 kg; I2=83\%) and --2.63 kg (95\% CI --2.97 to --2.29 kg; I2=91\%) at 3 and 6 months, respectively. Neither the type nor the number of mobile app features was associated with weight loss. Conclusions: Smartphone apps have a role in weight loss management. Nevertheless, the human-based behavioral component remained key to higher weight loss results. ", doi="10.2196/35479", url="https://mhealth.jmir.org/2022/4/e35479", url="http://www.ncbi.nlm.nih.gov/pubmed/35394443" } @Article{info:doi/10.2196/33527, author="Arroyo, Carmen Amber and Zawadzki, J. Matthew", title="The Implementation of Behavior Change Techniques in mHealth Apps for Sleep: Systematic Review", journal="JMIR Mhealth Uhealth", year="2022", month="Apr", day="4", volume="10", number="4", pages="e33527", keywords="behavior change techniques", keywords="sleep", keywords="mHealth", keywords="apps", keywords="digital health", keywords="mobile phone", abstract="Background: Mobile health (mHealth) apps targeting health behaviors using behavior change techniques (BCTs) have been successful in promoting healthy behaviors; however, their efficacy with sleep is unclear. Some work has shown success in promoting sleep through mHealth, whereas there have been reports that sleep apps can be adverse and lead to unhealthy obsessions with achieving perfect sleep. Objective: This study aims to report and describe the use of BCTs in mHealth apps for sleep with the following research questions: How many BCTs are used on average in sleep apps, and does this relate to their effectiveness on sleep outcomes? Are there specific BCTs used more or less often in sleep apps, and does this relate to their effectiveness on sleep outcomes? Does the effect of mHealth app interventions on sleep change when distinguishing between dimension and measurement of sleep? Methods: We conducted a systematic review following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to review articles on mHealth app interventions for sleep published between 2010 and 2020. Results: A total of 12 studies met the eligibility criteria. Most studies reported positive sleep outcomes, and there were no negative effects reported. Sleep quality was the most common dimension of sleep targeted. Subjective measures of sleep were used across all apps, whereas objective measures were often assessed but rarely reported as part of results. The average number of BCTs used was 7.67 (SD 2.32; range 3-11) of 16. Of the 12 studies, the most commonly used BCTs were feedback and monitoring (n=11, 92\%), shaping knowledge (n=11, 92\%), goals and planning (n=10, 83\%), and antecedents (n=10, 83\%), whereas the least common were scheduled consequences (n=0, 0\%), self-belief (n=0, 0\%), and covert learning (n=0, 0\%). Most apps used a similar set of BCTs that unfortunately did not allow us to distinguish which BCTs were present when studies reported more positive outcomes. Conclusions: Our study describes the peer-reviewed literature on sleep apps and provides a foundation for further examination and optimization of BCTs used in mHealth apps for sleep. We found strong evidence that mHealth apps are effective in improving sleep, and the potential reasons for the lack of adverse sleep outcome reporting are discussed. We found evidence that the type of BCTs used in mHealth apps for sleep differed from other health outcomes, although more research is needed to understand how BCTs can be implemented effectively to improve sleep using mHealth and the mechanisms of action through which they are effective (eg, self-efficacy, social norms, and attitudes). ", doi="10.2196/33527", url="https://mhealth.jmir.org/2022/4/e33527", url="http://www.ncbi.nlm.nih.gov/pubmed/35377327" } @Article{info:doi/10.2196/32344, author="Triantafyllidis, Andreas and Kondylakis, Haridimos and Katehakis, Dimitrios and Kouroubali, Angelina and Koumakis, Lefteris and Marias, Kostas and Alexiadis, Anastasios and Votis, Konstantinos and Tzovaras, Dimitrios", title="Deep Learning in mHealth for Cardiovascular Disease, Diabetes, and Cancer: Systematic Review", journal="JMIR Mhealth Uhealth", year="2022", month="Apr", day="4", volume="10", number="4", pages="e32344", keywords="mHealth", keywords="deep learning", keywords="chronic disease", keywords="review", keywords="mobile phone", abstract="Background: Major chronic diseases such as cardiovascular disease (CVD), diabetes, and cancer impose a significant burden on people and health care systems around the globe. Recently, deep learning (DL) has shown great potential for the development of intelligent mobile health (mHealth) interventions for chronic diseases that could revolutionize the delivery of health care anytime, anywhere. Objective: The aim of this study is to present a systematic review of studies that have used DL based on mHealth data for the diagnosis, prognosis, management, and treatment of major chronic diseases and advance our understanding of the progress made in this rapidly developing field. Methods: A search was conducted on the bibliographic databases Scopus and PubMed to identify papers with a focus on the deployment of DL algorithms that used data captured from mobile devices (eg, smartphones, smartwatches, and other wearable devices) targeting CVD, diabetes, or cancer. The identified studies were synthesized according to the target disease, the number of enrolled participants and their age, and the study period as well as the DL algorithm used, the main DL outcome, the data set used, the features selected, and the achieved performance. Results: In total, 20 studies were included in the review. A total of 35\% (7/20) of DL studies targeted CVD, 45\% (9/20) of studies targeted diabetes, and 20\% (4/20) of studies targeted cancer. The most common DL outcome was the diagnosis of the patient's condition for the CVD studies, prediction of blood glucose levels for the studies in diabetes, and early detection of cancer. Most of the DL algorithms used were convolutional neural networks in studies on CVD and cancer and recurrent neural networks in studies on diabetes. The performance of DL was found overall to be satisfactory, reaching >84\% accuracy in most studies. In comparison with classic machine learning approaches, DL was found to achieve better performance in almost all studies that reported such comparison outcomes. Most of the studies did not provide details on the explainability of DL outcomes. Conclusions: The use of DL can facilitate the diagnosis, management, and treatment of major chronic diseases by harnessing mHealth data. Prospective studies are now required to demonstrate the value of applied DL in real-life mHealth tools and interventions. ", doi="10.2196/32344", url="https://mhealth.jmir.org/2022/4/e32344", url="http://www.ncbi.nlm.nih.gov/pubmed/35377325" } @Article{info:doi/10.2196/35799, author="Voorheis, Paula and Zhao, Albert and Kuluski, Kerry and Pham, Quynh and Scott, Ted and Sztur, Peter and Khanna, Nityan and Ibrahim, Mohamed and Petch, Jeremy", title="Integrating Behavioral Science and Design Thinking to Develop Mobile Health Interventions: Systematic Scoping Review", journal="JMIR Mhealth Uhealth", year="2022", month="Mar", day="16", volume="10", number="3", pages="e35799", keywords="behavior change", keywords="design thinking", keywords="digital health", keywords="health behavior", keywords="mobile application", keywords="mobile health", keywords="mobile phone", keywords="product design", keywords="scoping review", keywords="systems design", keywords="telemedicine", keywords="user-centered design", abstract="Background: Mobile health (mHealth) interventions are increasingly being designed to facilitate health-related behavior change. Integrating insights from behavioral science and design science can help support the development of more effective mHealth interventions. Behavioral Design (BD) and Design Thinking (DT) have emerged as best practice approaches in their respective fields. Until now, little work has been done to examine how BD and DT can be integrated throughout the mHealth design process. Objective: The aim of this scoping review was to map the evidence on how insights from BD and DT can be integrated to guide the design of mHealth interventions. The following questions were addressed: (1) what are the main characteristics of studies that integrate BD and DT during the mHealth design process? (2) what theories, models, and frameworks do design teams use during the mHealth design process? (3) what methods do design teams use to integrate BD and DT during the mHealth design process? and (4) what are key design challenges, implementation considerations, and future directions for integrating BD and DT during mHealth design? Methods: This review followed the Joanna Briggs Institute reviewer manual and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. Studies were identified from MEDLINE, PsycINFO, Embase, CINAHL, and JMIR by using search terms related to mHealth, BD, and DT. Included studies had to clearly describe their mHealth design process and how behavior change theories, models, frameworks, or techniques were incorporated. Two independent reviewers screened the studies for inclusion and completed the data extraction. A descriptive analysis was conducted. Results: A total of 75 papers met the inclusion criteria. All studies were published between 2012 and 2021. Studies integrated BD and DT in notable ways, which can be referred to as ``Behavioral Design Thinking.'' Five steps were followed in Behavioral Design Thinking: (1) empathize with users and their behavior change needs, (2) define user and behavior change requirements, (3) ideate user-centered features and behavior change content, (4) prototype a user-centered solution that supports behavior change, and (5) test the solution against users' needs and for its behavior change potential. The key challenges experienced during mHealth design included meaningfully engaging patient and public partners in the design process, translating evidence-based behavior change techniques into actual mHealth features, and planning for how to integrate the mHealth intervention into existing clinical systems. Conclusions: Best practices from BD and DT can be integrated throughout the mHealth design process to ensure that mHealth interventions are purposefully developed to effectively engage users. Although this scoping review clarified how insights from BD and DT can be integrated during mHealth design, future research is needed to identify the most effective design approaches. ", doi="10.2196/35799", url="https://mhealth.jmir.org/2022/3/e35799", url="http://www.ncbi.nlm.nih.gov/pubmed/35293871" } @Article{info:doi/10.2196/35157, author="Mason, Madilyn and Cho, Youmin and Rayo, Jessica and Gong, Yang and Harris, Marcelline and Jiang, Yun", title="Technologies for Medication Adherence Monitoring and Technology Assessment Criteria: Narrative Review", journal="JMIR Mhealth Uhealth", year="2022", month="Mar", day="10", volume="10", number="3", pages="e35157", keywords="medication adherence", keywords="technology assessment", keywords="remote sensing technology", keywords="telemedicine", abstract="Background: Accurate measurement and monitoring of patient medication adherence is a global challenge because of the absence of gold standard methods for adherence measurement. Recent attention has been directed toward the adoption of technologies for medication adherence monitoring, as they provide the opportunity for continuous tracking of individual medication adherence behavior. However, current medication adherence monitoring technologies vary according to their technical features and data capture methods, leading to differences in their respective advantages and limitations. Overall, appropriate criteria to guide the assessment of medication adherence monitoring technologies for optimal adoption and use are lacking. Objective: This study aims to provide a narrative review of current medication adherence monitoring technologies and propose a set of technology assessment criteria to support technology development and adoption. Methods: A literature search was conducted on PubMed, Scopus, CINAHL, and ProQuest Technology Collection (2010-present) using the combination of keywords medication adherence, measurement technology, and monitoring technology. The selection focused on studies related to medication adherence monitoring technology and its development and use. The technological features, data capture methods, and potential advantages and limitations of the identified technology applications were extracted. Methods for using data for adherence monitoring were also identified. Common recurring elements were synthesized as potential technology assessment criteria. Results: Of the 3865 articles retrieved, 98 (2.54\%) were included in the final review, which reported a variety of technology applications for monitoring medication adherence, including electronic pill bottles or boxes, ingestible sensors, electronic medication management systems, blister pack technology, patient self-report technology, video-based technology, and motion sensor technology. Technical features varied by technology type, with common expectations for using these technologies to accurately monitor medication adherence and increase adoption in patients' daily lives owing to their unobtrusiveness and convenience of use. Most technologies were able to provide real-time monitoring of medication-taking behaviors but relied on proxy measures of medication adherence. Successful implementation of these technologies in clinical settings has rarely been reported. In all, 28 technology assessment criteria were identified and organized into the following five categories: development information, technology features, adherence to data collection and management, feasibility and implementation, and acceptability and usability. Conclusions: This narrative review summarizes the technical features, data capture methods, and various advantages and limitations of medication adherence monitoring technology reported in the literature and the proposed criteria for assessing medication adherence monitoring technologies. This collection of assessment criteria can be a useful tool to guide the development and selection of relevant technologies, facilitating the optimal adoption and effective use of technology to improve medication adherence outcomes. Future studies are needed to further validate the medication adherence monitoring technology assessment criteria and construct an appropriate technology assessment framework. ", doi="10.2196/35157", url="https://mhealth.jmir.org/2022/3/e35157", url="http://www.ncbi.nlm.nih.gov/pubmed/35266873" } @Article{info:doi/10.2196/29415, author="Cao, Weidan and Milks, Wesley M. and Liu, Xiaofu and Gregory, E. Megan and Addison, Daniel and Zhang, Ping and Li, Lang", title="mHealth Interventions for Self-management of Hypertension: Framework and Systematic Review on Engagement, Interactivity, and Tailoring", journal="JMIR Mhealth Uhealth", year="2022", month="Mar", day="2", volume="10", number="3", pages="e29415", keywords="mHealth", keywords="mobile app", keywords="digital behavior change", keywords="interventions", keywords="systematic review", keywords="hypertension", keywords="engagement", keywords="interactivity", keywords="tailoring", keywords="mobile phone", abstract="Background: Engagement is essential for the effectiveness of digital behavior change interventions. Existing systematic reviews examining hypertension self-management interventions via mobile apps have primarily focused on intervention efficacy and app usability. Engagement in the prevention or management of hypertension is largely unknown. Objective: This systematic review explores the definition and role of engagement in hypertension-focused mobile health (mHealth) interventions, as well as how determinants of engagement (ie, tailoring and interactivity) have been implemented. Methods: A systematic review of mobile app interventions for hypertension self-management targeting adults, published from 2013 to 2020, was conducted. A total of 21 studies were included in this systematic review. Results: The engagement was defined or operationalized as a microlevel concept, operationalized as interaction with the interventions (ie, frequency of engagement, time or duration of engagement with the program, and intensity of engagement). For all 3 studies that tested the relationship, increased engagement was associated with better biomedical outcomes (eg, blood pressure change). Interactivity was limited in digital behavior change interventions, as only 7 studies provided 2-way communication between users and a health care professional, and 9 studies provided 1-way communication in possible critical conditions; that is, when abnormal blood pressure values were recorded, users or health care professionals were notified. The tailoring of interventions varied at different aspects, from the tailoring of intervention content (including goals, patient education, advice and feedback from health professionals, reminders, and motivational messages) to the tailoring of intervention dose and communication mode. Tailoring was carried out in a number of ways, considering patient characteristics such as goals, preferences, disease characteristics (eg, hypertension stage and medication list), disease self-management experience levels, medication adherence rate, and values and beliefs. Conclusions: Available studies support the importance of engagement in intervention effectiveness as well as the essential roles of patient factors in tailoring, interactivity, and engagement. A patient-centered engagement framework for hypertension self-management using mHealth technology is proposed here, with the intent of facilitating intervention design and disease self-management using mHealth technology. ", doi="10.2196/29415", url="https://mhealth.jmir.org/2022/3/e29415", url="http://www.ncbi.nlm.nih.gov/pubmed/35234655" } @Article{info:doi/10.2196/31327, author="Chaudhari, Saurabh and Ghanvatkar, Suparna and Kankanhalli, Atreyi", title="Personalization of Intervention Timing for Physical Activity: Scoping Review", journal="JMIR Mhealth Uhealth", year="2022", month="Feb", day="28", volume="10", number="2", pages="e31327", keywords="review", keywords="physical activity", keywords="personalized intervention", keywords="intervention timing", keywords="mobile apps", keywords="fitness tracker", keywords="mobile phone", abstract="Background: The use of sensors in smartphones, smartwatches, and wearable devices has facilitated the personalization of interventions to increase users' physical activity (PA). Recent research has focused on evaluating the effects of personalized interventions in improving PA among users. However, it is critical to deliver the intervention at an appropriate time to each user to increase the likelihood of adoption of the intervention. Earlier review studies have not focused on the personalization of intervention timing for increasing PA. Objective: This review aims to examine studies of information technology--based PA interventions with personalized intervention timing (PIT); identify inputs (eg, user location) used by the system for generating the PIT, the techniques and methods used for generating the PIT, the content of the PA intervention, and delivery mode of the intervention; and identify gaps in existing literature and suggest future research directions. Methods: A scoping review was undertaken using PsycINFO, PubMed, Scopus, and Web of Science databases based on a structured search query. The main inclusion criteria were as follows: the study aimed to promote PA, included some form of PIT, and used some form of information technology for delivery of the intervention to the user. If deemed relevant, articles were included in this review after removing duplicates and examining the title, abstract, and full text of the shortlisted articles. Results: The literature search resulted in 18 eligible studies. In this review, 72\% (13/18) of the studies focused on increasing PA as the primary objective, whereas it was the secondary focus in the remaining studies. The inputs used to generate the PIT were categorized as user preference, activity level, schedule, location, and predicted patterns. On the basis of the intervention technique, studies were classified as manual, semiautomated, or automated. Of these, the automated interventions were either knowledge based (based on rules or guidelines) or data driven. Of the 18 studies, only 6 (33\%) evaluated the effectiveness of the intervention and reported positive outcomes. Conclusions: This work reviewed studies on PIT for PA interventions and identified several aspects of the interventions, that is, inputs, techniques, contents, and delivery mode. The reviewed studies evaluated PIT in conjunction with other personalization approaches such as activity recommendation, with no study evaluating the effectiveness of PIT alone. On the basis of the findings, several important directions for future research are also highlighted in this review. ", doi="10.2196/31327", url="https://mhealth.jmir.org/2022/2/e31327", url="http://www.ncbi.nlm.nih.gov/pubmed/35225811" } @Article{info:doi/10.2196/30671, author="Tran, Steven and Smith, Lorraine and El-Den, Sarira and Carter, Stephen", title="The Use of Gamification and Incentives in Mobile Health Apps to Improve Medication Adherence: Scoping Review", journal="JMIR Mhealth Uhealth", year="2022", month="Feb", day="21", volume="10", number="2", pages="e30671", keywords="gamification", keywords="incentives", keywords="mobile application", keywords="mHealth", keywords="medication adherence", keywords="mobile phone", abstract="Background: Emerging health care strategies addressing medication adherence include the use of direct-to-patient incentives or elements adapted from computer games. However, there is currently no published evidence synthesis on the use of gamification or financial incentives in mobile apps to improve medication adherence. Objective: The aim of this scoping review is to synthesize and appraise the literature pertaining to the use of mobile apps containing gamification or financial incentives for medication adherence. There were two objectives: to explore the reported effectiveness of these features and to describe and appraise the design and development process, including patient involvement. Methods: The following databases were searched for relevant articles published in English from database inception to September 24, 2020: Embase, MEDLINE, PsycINFO, CINAHL, and Web of Science. The framework by Arksey and O'Malley and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist guided this scoping review. Using a systematic screening process, studies were included if incentives or game features were used within mobile apps to specifically address medication adherence. An appraisal using risk of bias tools was also applied to their respective study design. Results: A total of 11 studies from the initial 691 retrieved articles were included in this review. Across the studies, gamification alone (9/11, 82\%) was used more than financial incentives (1/11, 9\%) alone or a combination of the two (1/11, 9\%). The studies generally reported improved or sustained optimal medication adherence outcomes; however, there was significant heterogeneity in the patient population, methodology such as outcome measures, and reporting of these studies. There was considerable variability in the development process and evaluation of the apps, with authors opting for either the waterfall or agile methodology. App development was often guided by a theory, but across the reviewed studies, there were no common theories used. Patient involvement was not commonly evident in predevelopment phases but were generally reserved for evaluations of feasibility, acceptance, and effectiveness. Patient perspectives on gamified app features indicated a potential to motivate positive health behaviors such as medication adherence along with critical themes of repetitiveness and irrelevance of certain features. The appraisal indicated a low risk of bias in most studies, although concerns were identified in potential confounding. Conclusions: To effectively address medication adherence via gamified and incentivized mobile apps, an evidence-based co-design approach and agile methodology should be used. This review indicates some adoption of an agile approach in app development; however, patient involvement is lacking in earlier stages. Further research in a generalized cohort of patients living with chronic conditions would facilitate the identification of barriers, potential opportunities, and the justification for the use of gamification and financial incentives in mobile apps for medication adherence. ", doi="10.2196/30671", url="https://mhealth.jmir.org/2022/2/e30671", url="http://www.ncbi.nlm.nih.gov/pubmed/35188475" } @Article{info:doi/10.2196/27337, author="Thornton, Louise and Osman, Bridie and Champion, Katrina and Green, Olivia and Wescott, B. Annie and Gardner, A. Lauren and Stewart, Courtney and Visontay, Rachel and Whife, Jesse and Parmenter, Belinda and Birrell, Louise and Bryant, Zachary and Chapman, Cath and Lubans, David and Slade, Tim and Torous, John and Teesson, Maree and Van de Ven, Pepijn", title="Measurement Properties of Smartphone Approaches to Assess Diet, Alcohol Use, and Tobacco Use: Systematic Review", journal="JMIR Mhealth Uhealth", year="2022", month="Feb", day="17", volume="10", number="2", pages="e27337", keywords="smartphone", keywords="app", keywords="alcohol", keywords="smoking", keywords="diet", keywords="measurement", keywords="mobile phone", abstract="Background: Poor diet, alcohol use, and tobacco smoking have been identified as strong determinants of chronic diseases, such as cardiovascular disease, diabetes, and cancer. Smartphones have the potential to provide a real-time, pervasive, unobtrusive, and cost-effective way to measure these health behaviors and deliver instant feedback to users. Despite this, the validity of using smartphones to measure these behaviors is largely unknown. Objective: The aim of our review is to identify existing smartphone-based approaches to measure these health behaviors and critically appraise the quality of their measurement properties. Methods: We conducted a systematic search of the Ovid MEDLINE, Embase (Elsevier), Cochrane Library (Wiley), PsycINFO (EBSCOhost), CINAHL (EBSCOHost), Web of Science (Clarivate), SPORTDiscus (EBSCOhost), and IEEE Xplore Digital Library databases in March 2020. Articles that were written in English; reported measuring diet, alcohol use, or tobacco use via a smartphone; and reported on at least one measurement property (eg, validity, reliability, and responsiveness) were eligible. The methodological quality of the included studies was assessed using the Consensus-Based Standards for the Selection of Health Measurement Instruments Risk of Bias checklist. Outcomes were summarized in a narrative synthesis. This systematic review was registered with PROSPERO, identifier CRD42019122242. Results: Of 12,261 records, 72 studies describing the measurement properties of smartphone-based approaches to measure diet (48/72, 67\%), alcohol use (16/72, 22\%), and tobacco use (8/72, 11\%) were identified and included in this review. Across the health behaviors, 18 different measurement techniques were used in smartphones. The measurement properties most commonly examined were construct validity, measurement error, and criterion validity. The results varied by behavior and measurement approach, and the methodological quality of the studies varied widely. Most studies investigating the measurement of diet and alcohol received very good or adequate methodological quality ratings, that is, 73\% (35/48) and 69\% (11/16), respectively, whereas only 13\% (1/8) investigating the measurement of tobacco use received a very good or adequate rating. Conclusions: This review is the first to provide evidence regarding the different types of smartphone-based approaches currently used to measure key behavioral risk factors for chronic diseases (diet, alcohol use, and tobacco use) and the quality of their measurement properties. A total of 19 measurement techniques were identified, most of which assessed dietary behaviors (48/72, 67\%). Some evidence exists to support the reliability and validity of using smartphones to assess these behaviors; however, the results varied by behavior and measurement approach. The methodological quality of the included studies also varied. Overall, more high-quality studies validating smartphone-based approaches against criterion measures are needed. Further research investigating the use of smartphones to assess alcohol and tobacco use and objective measurement approaches is also needed. International Registered Report Identifier (IRRID): RR2-10.1186/s13643-020-01375-w ", doi="10.2196/27337", url="https://mhealth.jmir.org/2022/2/e27337", url="http://www.ncbi.nlm.nih.gov/pubmed/35175212" } @Article{info:doi/10.2196/26275, author="Suo, Lingge and Ke, Xianghan and Zhang, Di and Qin, Xuejiao and Chen, Xuhao and Hong, Ying and Dai, Wanwei and Wu, Defu and Zhang, Chun and Zhang, Dongsong", title="Use of Mobile Apps for Visual Acuity Assessment: Systematic Review and Meta-analysis", journal="JMIR Mhealth Uhealth", year="2022", month="Feb", day="14", volume="10", number="2", pages="e26275", keywords="smartphone", keywords="iPad", keywords="eye screening", keywords="visual acuity", keywords="app", keywords="meta-analysis", abstract="Background: Vision impairments (VIs) and blindness are major global public health issues. A visual acuity (VA) test is one of the most crucial standard psychophysical tests of visual function and has been widely used in a broad range of health care domains, especially in many clinical settings. In recent years, there has been increasing research on mobile app--based VA assessment designed to allow people to test their VA at any time and any location. Objective: The goal of the review was to assess the accuracy and reliability of using mobile VA measurement apps. Methods: We searched PubMed, Embase, Cochrane Library, and Google Scholar for relevant articles on mobile apps for VA assessment published between January 1, 2008, and July 1, 2020. Two researchers independently inspected and selected relevant studies. Eventually, we included 22 studies that assessed tablet or smartphone apps for VA measurement. We then analyzed sensitivity, specificity, and accuracy in the 6 papers we found through a meta-analysis. Results: Most of the 22 selected studies can be considered of high quality based on the Quality Assessment of Diagnostic Accuracy Studies--2. In a meta-analysis of 6 studies involving 24,284 participants, we categorized the studies based on the age groups of the study participants (ie, aged 3-5 years, aged 6-22 years, and aged 55 years and older), examiner (ie, professional and nonprofessional examiners), and the type of mobile devices (ie, smartphone, iPad). In the group aged 3 to 5 years, the pooled sensitivity for VA app tests versus clinical VA tests was 0.87 (95\% CI 0.79-0.93; P=.39), and the pooled specificity was 0.78 (95\% CI 0.70-0.85; P=.37). In the group aged 6 to 22 years, the pooled sensitivity for VA app tests versus clinical VA tests was 0.86 (95\% CI 0.84-0.87; P<.001), and the pooled specificity for VA app tests versus clinical VA tests was 0.91 (95\% CI 0.90-0.91; P=.27). In the group aged 55 years and older, the pooled sensitivity for VA app tests versus clinical VA tests was 0.85 (95\% CI 0.55-0.98), and the pooled specificity for VA app tests versus clinical VA tests was 0.98 (95\% CI 0.95-0.99). We found that the nonprofessional examiner group (AUC 0.93) had higher accuracy than the professional examiner group (AUC 0.87). In the iPad-based group, the pooled sensitivity for VA app tests versus clinical VA tests was 0.86, and the pooled specificity was 0.79. In the smartphone-based group, the pooled sensitivity for VA app tests versus clinical VA tests was 0.86 (P<.001), and the pooled specificity for VA app tests versus clinical VA tests was 0.91 (P<.001). Conclusions: In this study, we conducted a comprehensive review of the research on existing mobile apps for VA tests to investigate their diagnostic value and limitations. Evidence gained from this study suggests that mobile app--based VA tests can be useful for on-demand VI detection. ", doi="10.2196/26275", url="https://mhealth.jmir.org/2022/2/e26275", url="http://www.ncbi.nlm.nih.gov/pubmed/35156935" } @Article{info:doi/10.2196/33413, author="Pit, Winona Sabrina and Tan, H. Aaron J. and Ramsden, Robyn and Payne, Kristy and Freihaut, Winona and Hayes, Oliver and Eames, Benjamin and Edwards, Mike and Colbran, Richard", title="Persuasive Design Solutions for a Sustainable Workforce: Review of Persuasive Apps for Real-Time Capability Support for Rural Health Care Professionals", journal="JMIR Mhealth Uhealth", year="2022", month="Feb", day="7", volume="10", number="2", pages="e33413", keywords="health", keywords="wellness", keywords="mobile apps", keywords="persuasive strategies", keywords="behavior change", keywords="review", keywords="health workforce", keywords="capability", keywords="career", keywords="employment", keywords="rural", keywords="workforce planning", abstract="Background: There is a need to further investigate how persuasive design principles can change rural health professionals' behaviors to look after their own health workforce capability. Several theories are used when developing apps to persuade people to change behavior, including the Persuasive System Design Model, consisting of primary task, dialogue, system credibility, and social support categories, and Cialdini's principles of persuasion. These have not been analyzed yet in the field of health workforce capability. Objective: This study aims to determine the persuasive design techniques used in capability building--related apps and to provide recommendations for designing a health workforce app to increase their persuasiveness. Methods: A Python script was used to extract a total of 3060 apps from Google Play. Keywords centered around health workforce capability elements. App inclusion criteria were as follows: been updated since 2019, rated by users on average 4 and above, and more than 100,000 downloads. Next, 2 experts reviewed whether 32 persuasive strategies were used in the selected apps, and these were further analyzed by capability categories: competencies and skills, health and personal qualities, values and attitudes, and work organization. Results: In all, 53 mobile apps were systematically reviewed to identify the persuasive design techniques. The most common were surface credibility (n=48, 90.6\%) and liking (n=48), followed by trustworthiness (n=43, 81.1\%), reminders (n=38, 71.7\%), and suggestion (n=30, 56.6\%). The techniques in the social support domain were the least used across the different apps analyzed for health workforce capability, whereas those in the primary task support domain were used most frequently. The recommendations reflect learnings from our analysis. These findings provided insight into mobile app design principles relevant to apps used in improving health workforce capability. Conclusions: Our review showed that there are many persuasive design techniques that can assist in building health workforce capability. Additionally, several apps are available in the market that can assist in improving health workforce capability. There is, however, a specific lack of digital, real-time support to improve health workforce capability. Social support strategies through using social support persuasive design techniques will need to be integrated more prominently into a health workforce capability app. An app to measure and monitor health workforce capability scores can be used in conjunction with direct real-world person and real-time support to discuss and identify solutions to improve health workforce capability for rural and remote health professionals who are at high risk of burnout or leaving the rural health workforce. ", doi="10.2196/33413", url="https://mhealth.jmir.org/2022/2/e33413", url="http://www.ncbi.nlm.nih.gov/pubmed/35129447" } @Article{info:doi/10.2196/33168, author="Bricca, Alessio and Pellegrini, Alessandro and Zangger, Graziella and Ahler, Jonas and J{\"a}ger, Madalina and Skou, T. S{\o}ren", title="The Quality of Health Apps and Their Potential to Promote Behavior Change in Patients With a Chronic Condition or Multimorbidity: Systematic Search in App Store and Google Play", journal="JMIR Mhealth Uhealth", year="2022", month="Feb", day="4", volume="10", number="2", pages="e33168", keywords="app", keywords="self-management", keywords="behavior change", keywords="multimorbidity", keywords="chronic conditions", keywords="health apps", keywords="mHealth", keywords="mobile health", keywords="mobile phone", abstract="Background: Mobile apps offer an opportunity to improve the lifestyle of patients with chronic conditions or multimorbidity. However, for apps to be recommended in clinical practice, their quality and potential for promoting behavior change must be considered. Objective: We aimed to investigate the quality of health apps for patients with a chronic condition or multimorbidity (defined as 2 or more chronic conditions) and their potential for promoting behavior change. Methods: We followed the Cochrane Handbook guidelines to conduct and report this study. A systematic search of apps available in English or Danish on App Store (Apple Inc) and Google Play (Google LLC) for patients with 1 or more of the following common and disabling conditions was conducted: osteoarthritis, heart conditions (heart failure and ischemic heart disease), hypertension, type 2 diabetes mellitus, depression, and chronic obstructive pulmonary disease. For the search strategy, keywords related to these conditions were combined. One author screened the titles and content of the identified apps. Subsequently, 3 authors independently downloaded the apps onto a smartphone and assessed the quality of the apps and their potential for promoting behavior change by using the Mobile App Rating Scale (MARS; number of items: 23; score: range 0-5 [higher is better]) and the App Behavior Change Scale (ABACUS; number of items: 21; score: range 0-21 [higher is better]), respectively. We included the five highest-rated apps and the five most downloaded apps but only assessed free content for their quality and potential for promoting behavior change. Results: We screened 453 apps and ultimately included 60. Of the 60 apps, 35 (58\%) were available in both App Store and Google Play. The overall average quality score of the apps was 3.48 (SD 0.28) on the MARS, and their overall average score for their potential to promote behavior change was 8.07 (SD 2.30) on the ABACUS. Apps for depression and apps for patients with multimorbidity tended to have higher overall MARS and ABACUS scores, respectively. The most common app features for supporting behavior change were the self-monitoring of physiological parameters (eg, blood pressure monitoring; apps: 38/60, 63\%), weight and diet (apps: 25/60, 42\%), or physical activity (apps: 22/60, 37\%) and stress management (apps: 22/60, 37\%). Only 8 out of the 60 apps (13\%) were completely free. Conclusions: Apps for patients with a chronic condition or multimorbidity appear to be of acceptable quality but have low to moderate potential for promoting behavior change. Our results provide a useful overview for patients and clinicians who would like to use apps for managing chronic conditions and indicate the need to improve health apps in terms of their quality and potential for promoting behavior change. ", doi="10.2196/33168", url="https://mhealth.jmir.org/2022/2/e33168", url="http://www.ncbi.nlm.nih.gov/pubmed/35119367" } @Article{info:doi/10.2196/27794, author="Xu, Linqi and Shi, Hongyu and Shen, Meidi and Ni, Yuanyuan and Zhang, Xin and Pang, Yue and Yu, Tianzhuo and Lian, Xiaoqian and Yu, Tianyue and Yang, Xige and Li, Feng", title="The Effects of mHealth-Based Gamification Interventions on Participation in Physical Activity: Systematic Review", journal="JMIR Mhealth Uhealth", year="2022", month="Feb", day="3", volume="10", number="2", pages="e27794", keywords="mobile health", keywords="gamification", keywords="physical activity", keywords="systematic review", keywords="mobile phone", abstract="Background: It is well known that regular physical exercise has associated benefits; yet, participation remains suboptimal. Mobile health (mHealth) has become an indispensable medium to deliver behavior change interventions, and there is a growing interest in the gamification apps in mHealth to promote physical activity (PA) participation. Gamification could use game design elements (such as points, leaderboards, and progress bars), and it has the potential to increase motivation for PA and engagement. However, mHealth-based gamification interventions are still emerging, and little is known about the application status and efficacy of such interventions. Objective: This systematic review aims to investigate gamification apps in mHealth for improving PA levels and simultaneously summarize the impact of gamification interventions on PA participation. Methods: We searched PubMed, Scopus, Web of Science, Embase, CINAHL (EBSCO host), and IEEE Xplore from inception to December 20, 2020. Original empirical research exploring the effects of gamification interventions on PA participation was included. The papers described at least one outcome regarding exercise or PA participation, which could be subjective self-report or objective indicator measurement. Of note, we excluded studies about serious games or full-fledged games. Results: Of 2944 studies identified from the database search, 50 (1.69\%) were included, and the information was synthesized. The review revealed that gamification of PA had been applied to various population groups and broadly distributed among young people but less distributed among older adults and patients with a disease. Most of the studies (30/50, 60\%) combined gamification with wearable devices to improve PA behavior change, and 50\% (25/50) of the studies used theories or principles for designing gamified PA interventions. The most frequently used game elements were goal-setting, followed by progress bars, rewards, points, and feedback. This review demonstrated that gamification interventions could increase PA participation; however, the results were mixed, and modest changes were attained, which could be attributed to the heterogeneity across studies. Conclusions: Overall, this study provides an overview of the existing empirical research in PA gamification interventions and provides evidence for the efficacy of gamification in enhancing PA participation. High-quality empirical studies are needed in the future to assess the efficacy of a combination of gamification and wearable activity devices to promote PA, and further exploration is needed to investigate the optimal implementation of these features of game elements and theories to enhance PA participation. ", doi="10.2196/27794", url="https://mhealth.jmir.org/2022/2/e27794", url="http://www.ncbi.nlm.nih.gov/pubmed/35113034" } @Article{info:doi/10.2196/29621, author="Serrano-Ripoll, J. Maria and Zamanillo-Campos, Roc{\'i}o and Fiol-DeRoque, A. Maria and Castro, Adoraci{\'o}n and Ricci-Cabello, Ignacio", title="Impact of Smartphone App--Based Psychological Interventions for Reducing Depressive Symptoms in People With Depression: Systematic Literature Review and Meta-analysis of Randomized Controlled Trials", journal="JMIR Mhealth Uhealth", year="2022", month="Jan", day="27", volume="10", number="1", pages="e29621", keywords="smartphone technology", keywords="mental health interventions", keywords="depression", keywords="eHealth", keywords="mHealth", keywords="apps", keywords="systematic review", keywords="meta-analysis", keywords="mobile phone", abstract="Background: Depression is a serious, disabling mental disorder that severely affects quality of life. Patients with depression often do not receive adequate treatment. App-based psychotherapy is considered to have great potential to treat depression owing to its reach and easy accessibility. Objective: We aim to analyze the impact of app-based psychological interventions for reducing depressive symptoms in people with depression. Methods: We conducted a systematic literature review and meta-analysis. We searched Medline, Embase, PsycINFO, Web of Science, and Cochrane Central Register of Controlled Trials from inception to December 23, 2020. We selected randomized controlled trials to examine the impact of app-based psychological interventions for reducing depressive symptoms in people with depression. Study selection, data extraction, and critical appraisal (using the Cochrane Risk of Bias tool for randomized studies and the ROBINS-I tool for nonrandomized studies) were conducted independently by 2 reviewers. Where possible, we pooled data using random effects meta-analyses to obtain estimates of the effect size of the intervention. We conducted post hoc meta-regression analyses to explore the factors associated with intervention success. Results: After screening 3468 unique references retrieved from bibliographic searches and assessing the eligibility of 79 full texts, we identified 12 trials (2859 participants) evaluating 14 different interventions. Of 14 trials, 7 (58\%) were conducted in the United States; 3 (25\%) trials, in Asia (Japan, South Korea, and China); 1 (8\%) trial, in Australia; and 1 (8\%) trial, in Germany. Of the 12 trials, 5 (42\%) trials presented a low risk of bias. The mean duration of the interventions was 6.6 (SD 2.8) weeks. Two-thirds of the interventions were based on cognitive behavioral therapy alone or included it in combination with cognitive control therapy, positive psychology, brief behavioral activation, or mindfulness- and acceptance-based therapy. With no evidence of publication bias, a pooled analysis of 83\% (10/12) of the trials and 86\% (12/14) of the interventions showed that app-based interventions, compared with a control group receiving usual care or minimal intervention, produced a moderate reduction in depressive symptoms (standardized mean difference [SMD] ?0.51, 95\% CI ?0.69 to ?0.33; 2018/2859, 70.58\% of the participants; I2=70\%). Our meta-regression analyses indicated that there was a greater reduction in symptoms of depression (P=.04) in trials that included participants with moderate to severe depression (SMD ?0.67, 95\% CI ?0.79 to ?0.55), compared with trials with participants exhibiting mild to moderate depression (SMD ?0.15, 95\% CI ?0.43 to ?0.12). Conclusions: App-based interventions targeted at people with depression produce moderate reductions in the symptoms of depression. More methodologically robust trials are needed to confirm our findings, determine which intervention features are associated with greater improvements, and identify those populations most likely to benefit from this type of intervention. Trial Registration: PROSPERO CRD42019145689; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=145689 ", doi="10.2196/29621", url="https://mhealth.jmir.org/2022/1/e29621", url="http://www.ncbi.nlm.nih.gov/pubmed/35084346" } @Article{info:doi/10.2196/22093, author="Sowon, Karen and Maliwichi, Priscilla and Chigona, Wallace", title="The Influence of Design and Implementation Characteristics on the Use of Maternal Mobile Health Interventions in Kenya: Systematic Literature Review", journal="JMIR Mhealth Uhealth", year="2022", month="Jan", day="27", volume="10", number="1", pages="e22093", keywords="human-technology interaction", keywords="maternal health", keywords="mHealth", keywords="mobile phone", keywords="utilization", keywords="Kenya", abstract="Background: The growth of mobile technology in developing countries, coupled with pressing maternal health care challenges, has led to a widespread implementation of maternal mobile health (mHealth) innovations. However, reviews generating insights on how the characteristics of the interventions influence use are scarce. Objective: This study aims to review maternal mHealth interventions in Kenya to explore the influence of intervention design and implementation characteristics on use by maternal health clients. We also provide a starting inventory for maternal mHealth interventions in the country. Methods: Using a systematic approach, we retrieved a total of 1100 citations from both peer-reviewed and gray sources. Articles were screened on the basis of an inclusion and exclusion criterion, and the results synthesized by categorizing and characterizing the interventions presented in the articles. The first phase of the literature search was conducted between January and April 2019, and the second phase was conducted between April and June 2021. Results: A total of 16 articles were retrieved, comprising 13 maternal mHealth interventions. The study highlighted various mHealth design and implementation characteristics that may influence the use of these interventions. Conclusions: In addition to elaborating on insights that would be useful in the design and implementation of future interventions, this study contributes to a local inventory of maternal mHealth interventions that may be useful to researchers and implementers in mHealth. This study highlights the need for explanatory studies to elucidate maternal mHealth use, while complementing existing evidence on mHealth effectiveness. ", doi="10.2196/22093", url="https://mhealth.jmir.org/2022/1/e22093", url="http://www.ncbi.nlm.nih.gov/pubmed/35084356" } @Article{info:doi/10.2196/34384, author="Huhn, Sophie and Axt, Miriam and Gunga, Hanns-Christian and Maggioni, Anna Martina and Munga, Stephen and Obor, David and Si{\'e}, Ali and Boudo, Valentin and Bunker, Aditi and Sauerborn, Rainer and B{\"a}rnighausen, Till and Barteit, Sandra", title="The Impact of Wearable Technologies in Health Research: Scoping Review", journal="JMIR Mhealth Uhealth", year="2022", month="Jan", day="25", volume="10", number="1", pages="e34384", keywords="wearable", keywords="consumer-grade wearables", keywords="commercially available wearables", keywords="public health", keywords="global health", keywords="population health", keywords="fitness trackers", keywords="big data", keywords="low-resource setting", keywords="tracker", keywords="review", keywords="mHealth", keywords="research", keywords="mobile phone", abstract="Background: Wearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen substantially in recent years. However, there is a shortage of aggregated insights into how wearables have been used in health research. Objective: In this review, we aim to broadly overview and categorize the current research conducted with affordable wearable devices for health research. Methods: We performed a scoping review to understand the use of affordable, consumer-grade wearables for health research from a population health perspective using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. A total of 7499 articles were found in 4 medical databases (PubMed, Ovid, Web of Science, and CINAHL). Studies were eligible if they used noninvasive wearables: worn on the wrist, arm, hip, and chest; measured vital signs; and analyzed the collected data quantitatively. We excluded studies that did not use wearables for outcome assessment and prototype studies, devices that cost >{\texteuro}500 (US \$570), or obtrusive smart clothing. Results: We included 179 studies using 189 wearable devices covering 10,835,733 participants. Most studies were observational (128/179, 71.5\%), conducted in 2020 (56/179, 31.3\%) and in North America (94/179, 52.5\%), and 93\% (10,104,217/10,835,733) of the participants were part of global health studies. The most popular wearables were fitness trackers (86/189, 45.5\%) and accelerometer wearables, which primarily measure movement (49/189, 25.9\%). Typical measurements included steps (95/179, 53.1\%), heart rate (HR; 55/179, 30.7\%), and sleep duration (51/179, 28.5\%). Other devices measured blood pressure (3/179, 1.7\%), skin temperature (3/179, 1.7\%), oximetry (3/179, 1.7\%), or respiratory rate (2/179, 1.1\%). The wearables were mostly worn on the wrist (138/189, 73\%) and cost <{\texteuro}200 (US \$228; 120/189, 63.5\%). The aims and approaches of all 179 studies revealed six prominent uses for wearables, comprising correlations---wearable and other physiological data (40/179, 22.3\%), method evaluations (with subgroups; 40/179, 22.3\%), population-based research (31/179, 17.3\%), experimental outcome assessment (30/179, 16.8\%), prognostic forecasting (28/179, 15.6\%), and explorative analysis of big data sets (10/179, 5.6\%). The most frequent strengths of affordable wearables were validation, accuracy, and clinical certification (104/179, 58.1\%). Conclusions: Wearables showed an increasingly diverse field of application such as COVID-19 prediction, fertility tracking, heat-related illness, drug effects, and psychological interventions; they also included underrepresented populations, such as individuals with rare diseases. There is a lack of research on wearable devices in low-resource contexts. Fueled by the COVID-19 pandemic, we see a shift toward more large-sized, web-based studies where wearables increased insights into the developing pandemic, including forecasting models and the effects of the pandemic. Some studies have indicated that big data extracted from wearables may potentially transform the understanding of population health dynamics and the ability to forecast health trends. ", doi="10.2196/34384", url="https://mhealth.jmir.org/2022/1/e34384", url="http://www.ncbi.nlm.nih.gov/pubmed/35076409" } @Article{info:doi/10.2196/33944, author="Lee, JuHee and Yeom, Insun and Chung, L. Misook and Kim, Yielin and Yoo, Subin and Kim, Eunyoung", title="Use of Mobile Apps for Self-care in People With Parkinson Disease: Systematic Review", journal="JMIR Mhealth Uhealth", year="2022", month="Jan", day="21", volume="10", number="1", pages="e33944", keywords="systematic review", keywords="Parkinson disease", keywords="motor symptoms", keywords="nonmotor symptoms", keywords="smartphone", keywords="mobile phone", keywords="mobile health", keywords="mobile apps", keywords="self-care", keywords="symptom", keywords="monitoring", keywords="review", keywords="disability", keywords="app", keywords="care", keywords="quality of life", keywords="self-management", abstract="Background: Self-care is essential for people with Parkinson disease (PD) to minimize their disability and adapt to alterations in physical abilities due to this progressive neurodegenerative disorder. With rapid developments in mobile technology, many health-related mobile apps for PD have been developed and used. However, research on mobile app--based self-care in PD is insufficient. Objective: This study aimed to explore the features and characteristics of mobile apps for self-care in people with PD. Methods: This study was performed sequentially according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature, Cochrane Library, Web of Science, and PsycINFO were searched in consultation with a librarian on June 8, 2021. We used keywords including ''Parkinson disease'' and ''mobile.'' Results: A total of 17 studies were selected based on the inclusion criteria, including 3 randomized controlled trials and 14 observational studies or quasi-experimental studies. The use of mobile apps for self-care in people with PD focused on symptom monitoring, especially motor symptoms. Motor symptoms were objectively measured mainly through the sensors of smartphones or wearable devices and task performance. Nonmotor symptoms were monitored through task performance or self-reported questionnaires in mobile apps. Most existing studies have focused on clinical symptom assessment in people with PD, and there is a lack of studies focusing on symptom management. Conclusions: Mobile apps for people with PD have been developed and used, but strategies for self-management are insufficient. We recommend the development of mobile apps focused on self-care that can enhance symptom management and health promotion practices. Studies should also evaluate the effects of mobile apps on symptom improvement and quality of life in people with PD. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42021267374; https://www.crd.york.ac.uk/prospero/display\_record.php?ID=CRD42021267374. ", doi="10.2196/33944", url="https://mhealth.jmir.org/2022/1/e33944", url="http://www.ncbi.nlm.nih.gov/pubmed/35060910" } @Article{info:doi/10.2196/30791, author="Germini, Federico and Noronha, Noella and Borg Debono, Victoria and Abraham Philip, Binu and Pete, Drashti and Navarro, Tamara and Keepanasseril, Arun and Parpia, Sameer and de Wit, Kerstin and Iorio, Alfonso", title="Accuracy and Acceptability of Wrist-Wearable Activity-Tracking Devices: Systematic Review of the Literature", journal="J Med Internet Res", year="2022", month="Jan", day="21", volume="24", number="1", pages="e30791", keywords="diagnosis", keywords="measurement", keywords="wrist-wearable devices", keywords="mobile phone", abstract="Background: Numerous wrist-wearable devices to measure physical activity are currently available, but there is a need to unify the evidence on how they compare in terms of acceptability and accuracy. Objective: The aim of this study is to perform a systematic review of the literature to assess the accuracy and acceptability (willingness to use the device for the task it is designed to support) of wrist-wearable activity trackers. Methods: We searched MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, and SPORTDiscus for studies measuring physical activity in the general population using wrist-wearable activity trackers. We screened articles for inclusion and, for the included studies, reported data on the studies' setting and population, outcome measured, and risk of bias. Results: A total of 65 articles were included in our review. Accuracy was assessed for 14 different outcomes, which can be classified in the following categories: count of specific activities (including step counts), time spent being active, intensity of physical activity (including energy expenditure), heart rate, distance, and speed. Substantial clinical heterogeneity did not allow us to perform a meta-analysis of the results. The outcomes assessed most frequently were step counts, heart rate, and energy expenditure. For step counts, the Fitbit Charge (or the Fitbit Charge HR) had a mean absolute percentage error (MAPE) <25\% across 20 studies. For heart rate, the Apple Watch had a MAPE <10\% in 2 studies. For energy expenditure, the MAPE was >30\% for all the brands, showing poor accuracy across devices. Acceptability was most frequently measured through data availability and wearing time. Data availability was ?75\% for the Fitbit Charge HR, Fitbit Flex 2, and Garmin Vivofit. The wearing time was 89\% for both the GENEActiv and Nike FuelBand. Conclusions: The Fitbit Charge and Fitbit Charge HR were consistently shown to have a good accuracy for step counts and the Apple Watch for measuring heart rate. None of the tested devices proved to be accurate in measuring energy expenditure. Efforts should be made to reduce the heterogeneity among studies. ", doi="10.2196/30791", url="https://www.jmir.org/2022/1/e30791", url="http://www.ncbi.nlm.nih.gov/pubmed/35060915" } @Article{info:doi/10.2196/30682, author="Jung, Jiyeon and Cho, Inhae", title="Promoting Physical Activity and Weight Loss With mHealth Interventions Among Workers: Systematic Review and Meta-analysis of Randomized Controlled Trials", journal="JMIR Mhealth Uhealth", year="2022", month="Jan", day="21", volume="10", number="1", pages="e30682", keywords="mHealth", keywords="physical activity", keywords="obesity", keywords="weight loss", keywords="workforce", keywords="workplace health promotion", keywords="mobile phone", abstract="Background: Physical activity (PA) is a vital factor in promoting health in the workforce. Mobile health (mHealth) interventions have recently emerged in workplace health promotion as an effective strategy for inducing changes in health behaviors among workers; however, the effectiveness of mHealth interventions in promoting PA and weight loss for workers is unclear. Objective: This study aims to provide a comprehensive analysis of current evidence on the effectiveness of mHealth interventions in promoting PA and weight loss among workers. Methods: We searched relevant databases, including PubMed, Embase, CINAHL Complete, and the Cochrane Library, for publications on mHealth interventions in the English or Korean language from inception to December 2020. Randomized controlled trials that evaluated the effectiveness of mHealth in improving PA and weight loss were retrieved. A meta-analysis with a random effects model and subgroup analyses was performed on PA types and mHealth intervention characteristics. Results: A total of 8 studies were included in this analysis. More than half of the studies (5/8, 63\%) were identified as having a high risk of bias. The mHealth intervention group showed a significant improvement in PA (standardized mean difference [SMD] 0.22, 95\% CI 0.03-0.41; P<.001; I2=78\%). No significant difference in weight loss was observed when comparing the intervention group with the control groups (SMD 0.02, 95\% CI --0.07 to 0.10; P=.48; I2=0\%). A subgroup analysis was also performed; walking activity (SMD 0.70, 95\% CI 0.21-1.19; P<.001; I2=83.3\%), a multicomponent program (SMD 0.19, 95\% CI 0.05-0.33; P=.03; I2=57.4\%), objective measurement (SMD 0.58, 95\% CI 0.05-1.10; P<.001; I2=87.3\%), and 2 or more delivery modes (SMD 0.44, 95\% CI 0.01-0.87; P<.001; I2=85.1\%) were significantly associated with an enhancement in PA. Conclusions: This study suggests that mHealth interventions are effective for improving PA among workers. Future studies that assess long-term efficacy with a larger population are recommended. ", doi="10.2196/30682", url="https://mhealth.jmir.org/2022/1/e30682", url="http://www.ncbi.nlm.nih.gov/pubmed/35060913" } @Article{info:doi/10.2196/31607, author="Hayman, J. Melanie and Alfrey, Kristie-Lee and Waters, Kim and Cannon, Summer and Mielke, I. Gregore and Keating, E. Shelley and Mena, P. Gabriela and Mottola, F. Michelle and Evenson, R. Kelly and Davenport, H. Margie and Barlow, Ariel S. and Budzynski-Seymour, Emily and Comardelle, Natalie and Dickey, Madison and Harrison, L. Cheryce and Kebbe, Maryam and Moholdt, Trine and Moran, J. Lisa and Nagpal, S. Taniya and Schoeppe, Stephanie and Alley, Stephanie and Brown, J. Wendy and Williams, Susan and Vincze, Lisa", title="Evaluating Evidence-Based Content, Features of Exercise Instruction, and Expert Involvement in Physical Activity Apps for Pregnant Women: Systematic Search and Content Analysis", journal="JMIR Mhealth Uhealth", year="2022", month="Jan", day="19", volume="10", number="1", pages="e31607", keywords="apps", keywords="exercise", keywords="mobile health", keywords="mHealth", keywords="mobile phone", keywords="physical activity", keywords="pregnancy", keywords="exercise prescription", keywords="evidence-based guidelines", keywords="app development", keywords="systematic review", abstract="Background: Guidelines for physical activity and exercise during pregnancy recommend that all women without contraindications engage in regular physical activity to improve both their own health and the health of their baby. Many women are uncertain how to safely engage in physical activity and exercise during this life stage and are increasingly using mobile apps to access health-related information. However, the extent to which apps that provide physical activity and exercise advice align with current evidence-based pregnancy recommendations is unclear. Objective: This study aims to conduct a systematic search and content analysis of apps that promote physical activity and exercise in pregnancy to examine the alignment of the content with current evidence-based recommendations; delivery, format, and features of physical activity and exercise instruction; and credentials of the app developers. Methods: Systematic searches were conducted in the Australian App Store and Google Play Store in October 2020. Apps were identified using combinations of search terms relevant to pregnancy and exercise or physical activity and screened for inclusion (with a primary focus on physical activity and exercise during pregnancy, free to download or did not require immediate paid subscription, and an average user rating of ?4 out of 5). Apps were then independently reviewed using an author-designed extraction tool. Results: Overall, 27 apps were included in this review (Google Play Store: 16/27, 59\%, and App Store: 11/27, 41\%). Two-thirds of the apps provided some information relating to the frequency, intensity, time, and type principles of exercise; only 11\% (3/27) provided this information in line with current evidence-based guidelines. Approximately one-third of the apps provided information about contraindications to exercise during pregnancy and referenced the supporting evidence. None of the apps actively engaged in screening for potential contraindications. Only 15\% (4/27) of the apps collected information about the user's current exercise behaviors, 11\% (3/27) allowed users to personalize features relating to their exercise preferences, and a little more than one-third provided information about developer credentials. Conclusions: Few exercise apps designed for pregnancy aligned with current evidence-based physical activity guidelines. None of the apps screened users for contraindications to physical activity and exercise during pregnancy, and most lacked appropriate personalization features to account for an individual's characteristics. Few involved qualified experts during the development of the app. There is a need to improve the quality of apps that promote exercise in pregnancy to ensure that women are appropriately supported to engage in exercise and the potential risk of injury, complications, and adverse pregnancy outcomes for both mother and child is minimized. This could be done by providing expert guidance that aligns with current recommendations, introducing screening measures and features that enable personalization and tailoring to individual users, or by developing a recognized system for regulating apps. ", doi="10.2196/31607", url="https://mhealth.jmir.org/2022/1/e31607", url="http://www.ncbi.nlm.nih.gov/pubmed/35044318" } @Article{info:doi/10.2196/26453, author="Voth, Melissa and Chisholm, Shannon and Sollid, Hannah and Jones, Chelsea and Smith-MacDonald, Lorraine and Br{\'e}mault-Phillips, Suzette", title="Efficacy, Effectiveness, and Quality of Resilience-Building Mobile Health Apps for Military, Veteran, and Public Safety Personnel Populations: Scoping Literature Review and App Evaluation", journal="JMIR Mhealth Uhealth", year="2022", month="Jan", day="19", volume="10", number="1", pages="e26453", keywords="occupational stress injury", keywords="trauma", keywords="mHealth", keywords="resilience", keywords="mental health", keywords="military", keywords="veteran", keywords="public safety personnel", keywords="OSI", keywords="PTSD", keywords="mental health intervention", keywords="mobile phone", abstract="Background: Military members (MMs) and public safety personnel (PSP) are vulnerable to occupational stress injuries because of their job demands. When MMs and PSP transition out of these professions, they may continue to experience mental health challenges. The development and implementation of resilience-building mobile health (mHealth) apps as an emergent mental health intervention platform has allowed for targeted, cost-effective, and easily accessible treatment when in-person therapy may be limited or unavailable. However, current mHealth app development is not regulated, and often lacks both clear evidence-based research and the input of health care professionals. Objective: This study aims to evaluate the evidence-based quality, efficacy, and effectiveness of resilience-building mobile apps targeted toward the MMs, PSP, and veteran populations via a scoping literature review of the current evidence base regarding resilience apps for these populations and an evaluation of free resilience apps designed for use among these populations. Methods: The studies were selected using a comprehensive search of MEDLINE, CINAHL Plus, PsycINFO, SocINDEX, Academic Search Complete, Embase, and Google and were guided by PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). A narrative synthesis of the resulting papers was performed. The Alberta Rating Index for Apps was used to conduct a review of each of the identified apps. The inclusion criteria consisted of apps that were free to download in either the Google Play Store or the Apple App Store; updated within the last 3 years; available in English and in Canada; and intended for use by MMs, veterans, and PSP. Results: In total, 22 apps met the inclusion criteria for evaluation. The resilience strategies offered by most apps included psychoeducation, mindfulness, cognitive behavioral therapy, and acceptance and commitment therapy. Overall, 50\% (11/22) of apps had been tested in randomized controlled trials, 7 (32\%) apps had been evaluated using other research methods, and 5 (23\%) apps had not been studied. Using the Alberta Rating Index for Apps, the app scores ranged from 37 to 56 out of 72, with higher rated apps demonstrating increased usability and security features. Conclusions: The mHealth apps reviewed are well-suited to providing resilience strategies for MMs, PSP, and veterans. They offer easy accessibility to evidence-based tools while working to encourage the use of emotional and professional support with safety in mind. Although not intended to function as a substitute for professional services, research has demonstrated that mHealth apps have the potential to foster a significant reduction in symptom severity for posttraumatic stress disorder, depression, anxiety, and other mental health conditions. In clinical practice, apps can be used to supplement treatment and provide clients with population-specific confidential tools to increase engagement in the treatment process. ", doi="10.2196/26453", url="https://mhealth.jmir.org/2022/1/e26453", url="http://www.ncbi.nlm.nih.gov/pubmed/35044307" } @Article{info:doi/10.2196/30724, author="Spadaro, Benedetta and Martin-Key, A. Nayra and Funnell, Erin and Bahn, Sabine", title="mHealth Solutions for Perinatal Mental Health: Scoping Review and Appraisal Following the mHealth Index and Navigation Database Framework", journal="JMIR Mhealth Uhealth", year="2022", month="Jan", day="17", volume="10", number="1", pages="e30724", keywords="digital mental health", keywords="perinatal mental health", keywords="pregnancy", keywords="MIND", keywords="mobile phone", abstract="Background: The ever-increasing pressure on health care systems has resulted in the underrecognition of perinatal mental disorders. Digital mental health tools such as apps could provide an option for accessible perinatal mental health screening and assessment. However, there is a lack of information regarding the availability and features of perinatal app options. Objective: This study aims to evaluate the current state of diagnostic and screening apps for perinatal mental health available on the Google Play Store (Android) and Apple App Store (iOS) and to review their features following the mHealth Index and Navigation Database framework. Methods: Following a scoping review approach, the Apple App Store and Google Play Store were systematically searched to identify perinatal mental health assessment apps. A total of 14 apps that met the inclusion criteria were downloaded and reviewed in a standardized manner using the mHealth Index and Navigation Database framework. The framework comprised 107 questions, allowing for a comprehensive assessment of app origin, functionality, engagement features, security, and clinical use. Results: Most apps were developed by for-profit companies (n=10), followed by private individuals (n=2) and trusted health care companies (n=2). Out of the 14 apps, 3 were available only on Android devices, 4 were available only on iOS devices, and 7 were available on both platforms. Approximately one-third of the apps (n=5) had been updated within the last 180 days. A total of 12 apps offered the Edinburgh Postnatal Depression Scale in its original version or in rephrased versions. Engagement, input, and output features included reminder notifications, connections to therapists, and free writing features. A total of 6 apps offered psychoeducational information and references. Privacy policies were available for 11 of the 14 apps, with a median Flesch-Kincaid reading grade level of 12.3. One app claimed to be compliant with the Health Insurance Portability and Accountability Act standards and 2 apps claimed to be compliant with General Data Protection Regulation. Of the apps that could be accessed in full (n=10), all appeared to fulfill the claims stated in their description. Only 1 app referenced a relevant peer-reviewed study. All the apps provided a warning for use, highlighting that the mental health assessment result should not be interpreted as a diagnosis or as a substitute for medical care. Only 3 apps allowed users to export or email their mental health test results. Conclusions: These results indicate that there are opportunities to improve perinatal mental health assessment apps. To this end, we recommend focusing on the development and validation of more comprehensive assessment tools, ensuring data protection and safety features are adequate for the intended app use, and improving data sharing features between users and health care professionals for timely support. ", doi="10.2196/30724", url="https://mhealth.jmir.org/2022/1/e30724", url="http://www.ncbi.nlm.nih.gov/pubmed/35037894" } @Article{info:doi/10.2196/29512, author="Nimmanterdwong, Zethapong and Boonviriya, Suchaya and Tangkijvanich, Pisit", title="Human-Centered Design of Mobile Health Apps for Older Adults: Systematic Review and Narrative Synthesis", journal="JMIR Mhealth Uhealth", year="2022", month="Jan", day="14", volume="10", number="1", pages="e29512", keywords="connected health", keywords="development", keywords="elderly", keywords="HCD", keywords="mHealth", keywords="older adults", keywords="review", keywords="telehealth", keywords="UCD", keywords="usability", keywords="design", keywords="human-centered", keywords="app", abstract="Background: The world is aging. The number of older patients is on the rise, and along with it comes the burden of noncommunicable diseases, both clinical and economic. Attempts with mobile health (mHealth) have been made to remedy the situation with promising outcomes. Researchers have adopted human-centered design (HCD) in mHealth creation to ensure those promises become a reality. Objective: This systematic review aims to explore existing literature on relevant primary research and case studies to (1) illustrate how HCD can be used to create mHealth solutions for older adults and (2) summarize the overall process with recommendations specific to the older population. Methods: We conducted a systematic review to address the study objectives. IEEE Xplore, Medline via Ovid, PubMed, and Scopus were searched for HCD research of mHealth solutions for older adults. Two independent reviewers then included the papers if they (1) were written in English, (2) included participants equal to or older than 60 years old, (3) were primary research, and (4) reported about mHealth apps and their HCD developments from start to finish. The 2 reviewers continued to assess the included studies' qualities using the Mixed Methods Appraisal Tool (MMAT). A narrative synthesis was then carried out and completed. Results: Eight studies passed the eligibility criteria: 5 were mixed methods studies and 3 were case studies. Some studies were about the same mHealth projects with a total of 5 mHealth apps. The included studies differed in HCD goals, target groups, and details of their HCD methodologies. The HCD process was explored through narrative synthesis in 4 steps according to the International Standardization Organization (ISO) standard 9241-210: (1) understand and specify the context of use, (2) specify the user requirements, (3) produce design solutions to meet these requirements, and (4) evaluate the designs against requirements. The overall process and recommendations unique to older adults are summarized logically with structural order and time order based on the Minto pyramid principle and ISO 9241-210. Conclusions: Findings show that HCD can be used to create mHealth solutions for older adults with positive outcomes. This review has also summarized practical HCD steps and additional suggestions based on existing literature in the subfield. However, evidence-based results are still limited because most included studies lacked details about their sampling methods and did not set objective and quantifiable goals, leading to failure to draw significant conclusions. More studies of HCD application on mHealth for older adults with measurable design goals and rigorous research strategy are warranted. ", doi="10.2196/29512", url="https://mhealth.jmir.org/2022/1/e29512", url="http://www.ncbi.nlm.nih.gov/pubmed/35029535" } @Article{info:doi/10.2196/28285, author="Peyroteo, Mariana and Ferreira, Augusto In{\^e}s and Elvas, Brito Lu{\'i}s and Ferreira, Carlos Jo{\~a}o and Lap{\~a}o, Velez Lu{\'i}s", title="Remote Monitoring Systems for Patients With Chronic Diseases in Primary Health Care: Systematic Review", journal="JMIR Mhealth Uhealth", year="2021", month="Dec", day="21", volume="9", number="12", pages="e28285", keywords="sensors", keywords="wearables", keywords="remote monitoring", keywords="digital health", keywords="primary health care", keywords="chronic diseases", abstract="Background: The digital age, with digital sensors, the Internet of Things (IoT), and big data tools, has opened new opportunities for improving the delivery of health care services, with remote monitoring systems playing a crucial role and improving access to patients. The versatility of these systems has been demonstrated during the current COVID-19 pandemic. Health remote monitoring systems (HRMS) present various advantages such as the reduction in patient load at hospitals and health centers. Patients that would most benefit from HRMS are those with chronic diseases, older adults, and patients that experience less severe symptoms recovering from SARS-CoV-2 viral infection. Objective: This paper aimed to perform a systematic review of the literature of HRMS in primary health care (PHC) settings, identifying the current status of the digitalization of health processes, remote data acquisition, and interactions between health care personnel and patients. Methods: A systematic literature review was conducted using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines to identify articles that explored interventions with HRMS in patients with chronic diseases in the PHC setting. Results: The literature review yielded 123 publications, 18 of which met the predefined inclusion criteria. The selected articles highlighted that sensors and wearables are already being used in multiple scenarios related to chronic disease management at the PHC level. The studies focused mostly on patients with diabetes (9/26, 35\%) and cardiovascular diseases (7/26, 27\%). During the evaluation of the implementation of these interventions, the major difficulty that stood out was the integration of information into already existing systems in the PHC infrastructure and in changing working processes of PHC professionals (83\%). Conclusions: The PHC context integrates multidisciplinary teams and patients with often complex, chronic pathologies. Despite the theoretical framework, objective identification of problems, and involvement of stakeholders in the design and implementation processes, these interventions mostly fail to scale up. Despite the inherent limitations of conducting a systematic literature review, the small number of studies in the PHC context is a relevant limitation. This study aimed to demonstrate the importance of matching technological development to the working PHC processes in interventions regarding the use of sensors and wearables for remote monitoring as a source of information for chronic disease management, so that information with clinical value is not lost along the way. ", doi="10.2196/28285", url="https://mhealth.jmir.org/2021/12/e28285", url="http://www.ncbi.nlm.nih.gov/pubmed/34932000" } @Article{info:doi/10.2196/25129, author="Bezabih, Mequanint Alemitu and Gerling, Kathrin and Abebe, Workeabeba and Abeele, Vanden Vero", title="Behavioral Theories and Motivational Features Underlying eHealth Interventions for Adolescent Antiretroviral Adherence: Systematic Review", journal="JMIR Mhealth Uhealth", year="2021", month="Dec", day="10", volume="9", number="12", pages="e25129", keywords="HIV", keywords="adolescents", keywords="ART adherence", keywords="eHealth", keywords="health theories", keywords="behavior change techniques", keywords="motivational design principles", abstract="Background: eHealth systems provide new opportunities for the delivery of antiretroviral therapy (ART) adherence interventions for adolescents. They may be more effective if grounded in health behavior theories and behavior change techniques (BCTs). Prior reviews have examined the effectiveness, feasibility, and acceptability of these eHealth systems. However, studies have not systematically explored the use of health behavior theories and BCTs in the design of these applications. Objective: The purpose of this review was to explore whether health behavior theories and BCTs were considered to ground designs of eHealth systems supporting adolescents' (10-24 years) ART adherence. More specifically, we examined which specific theories and BCTs were applied, and how these BCTs were implemented as design features. Additionally, we investigated the quality and effect of eHealth systems. Methods: A systematic search was performed on IEEE Xplore, ACM, ScienceDirect, PubMed, Scopus, and Web of Science databases from 2000 to 2020. Theory use and BCTs were coded using the Theory Coding Scheme and the Behavior Change Technique Taxonomy version 1 (BCTTv1), respectively. Design features were identified using the lenses of motivational design for mobile health (mHealth). The number of BCTs and design features for each eHealth system and their prevalence across all systems were assessed. Results: This review identified 16 eHealth systems aiming to support ART adherence among adolescents. System types include SMS text message reminders (n=6), phone call reminders (n=3), combined SMS text message and phone call reminders (n=1), electronic adherence monitoring devices (n=3), smartphone apps (n=1), smartphone serious games (n=1), gamified smartphone apps (n=1), leveraging existing social media (n=2), web-based applications (n=1), videoconferencing (n=1), and desktop applications (n=1). Nine were grounded in theory, of which 3 used theories extensively. The impact of adolescent developmental changes on ART adherence was not made explicit. A total of 42 different BCTs and 24 motivational design features were used across systems. Ten systems reported positive effects on 1 or more outcomes; however, of these ten systems, only 3 reported exclusively positive effects on all the outcomes they measured. As much as 6 out of 16 reported purely no effect in all the outcomes measured. Conclusions: Basic applications (SMS text messaging and phone calls) were most frequent, although more advanced systems such as mobile apps and games are also emerging. This review indicated gaps in the use of theory and BCTs, and particularly the impact of developmental changes on ART adherence was not adequately considered. Together with adopting a developmental orientation, future eHealth systems should effectively leverage health theories and consider developing more advanced systems that open the door to using BCTs more comprehensively. Overall, the impact of eHealth systems on adolescent ART adherence and its mediators is promising, but conclusive evidence on effect still needs to be provided. ", doi="10.2196/25129", url="https://mhealth.jmir.org/2021/12/e25129", url="http://www.ncbi.nlm.nih.gov/pubmed/34890353" } @Article{info:doi/10.2196/28102, author="G{\"o}ttgens, Irene and Oertelt-Prigione, Sabine", title="The Application of Human-Centered Design Approaches in Health Research and Innovation: A Narrative Review of Current Practices", journal="JMIR Mhealth Uhealth", year="2021", month="Dec", day="6", volume="9", number="12", pages="e28102", keywords="human-centered design", keywords="design thinking", keywords="user-centered design", keywords="design-based research", keywords="methodology", keywords="review", keywords="mobile phone", abstract="Background: Human-centered design (HCD) approaches to health care strive to support the development of innovative, effective, and person-centered solutions for health care. Although their use is increasing, there is no integral overview describing the details of HCD methods in health innovations. Objective: This review aims to explore the current practices of HCD approaches for the development of health innovations, with the aim of providing an overview of the applied methods for participatory and HCD processes and highlighting their shortcomings for further research. Methods: A narrative review of health research was conducted based on systematic electronic searches in the PubMed, CINAHL, Embase, Cochrane Library, Web of Science, PsycINFO, and Sociological Abstracts (2000-2020) databases using keywords related to human-centered design, design thinking (DT), and user-centered design (UCD). Abstracts and full-text articles were screened by 2 reviewers independently based on predefined inclusion criteria. Data extraction focused on the methodology used throughout the research process, the choice of methods in different phases of the innovation cycle, and the level of engagement of end users. Results: This review summarizes the application of HCD practices across various areas of health innovation. All approaches prioritized the user's needs and the participatory and iterative nature of the design process. The design processes comprised several design cycles during which multiple qualitative and quantitative methods were used in combination with specific design methods. HCD- and DT-based research primarily targeted understanding the research context and defining the problem, whereas UCD-based work focused mainly on the direct generation of solutions. Although UCD approaches involved end users primarily as testers and informants, HCD and DT approaches involved end users most often as design partners. Conclusions: We have provided an overview of the currently applied methodologies and HCD guidelines to assist health care professionals and design researchers in their methodological choices. HCD-based techniques are challenging to evaluate using traditional biomedical research methods. Previously proposed reporting guidelines are a step forward but would require a level of detail that is incompatible with the current publishing landscape. Hence, further development is needed in this area. Special focus should be placed on the congruence between the chosen methods, design strategy, and achievable outcomes. Furthermore, power dimensions, agency, and intersectionality need to be considered in co-design sessions with multiple stakeholders, especially when including vulnerable groups. ", doi="10.2196/28102", url="https://mhealth.jmir.org/2021/12/e28102", url="http://www.ncbi.nlm.nih.gov/pubmed/34874893" } @Article{info:doi/10.2196/15433, author="Muro-Culebras, Antonio and Escriche-Escuder, Adrian and Martin-Martin, Jaime and Rold{\'a}n-Jim{\'e}nez, Cristina and De-Torres, Irene and Ruiz-Mu{\~n}oz, Maria and Gonzalez-Sanchez, Manuel and Mayoral-Cleries, Fermin and Bir{\'o}, Attila and Tang, Wen and Nikolova, Borjanka and Salvatore, Alfredo and Cuesta-Vargas, Ignacio Antonio", title="Tools for Evaluating the Content, Efficacy, and Usability of Mobile Health Apps According to the Consensus-Based Standards for the Selection of Health Measurement Instruments: Systematic Review", journal="JMIR Mhealth Uhealth", year="2021", month="Dec", day="1", volume="9", number="12", pages="e15433", keywords="mobile health", keywords="mHealth", keywords="eHealth", keywords="mobile apps", keywords="assessment", keywords="rating", keywords="smartphone", keywords="questionnaire design", keywords="mobile phone", abstract="Background: There are several mobile health (mHealth) apps in mobile app stores. These apps enter the business-to-customer market with limited controls. Both, apps that users use autonomously and those designed to be recommended by practitioners require an end-user validation to minimize the risk of using apps that are ineffective or harmful. Prior studies have reviewed the most relevant aspects in a tool designed for assessing mHealth app quality, and different options have been developed for this purpose. However, the psychometric properties of the mHealth quality measurement tools, that is, the validity and reliability of the tools for their purpose, also need to be studied. The Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) initiative has developed tools for selecting the most suitable measurement instrument for health outcomes, and one of the main fields of study was their psychometric properties. Objective: This study aims to address and psychometrically analyze, following the COSMIN guideline, the quality of the tools that are used to measure the quality of mHealth apps. Methods: From February 1, 2019, to December 31, 2019, 2 reviewers searched PubMed and Embase databases, identifying mHealth app quality measurement tools and all the validation studies associated with each of them. For inclusion, the studies had to be meant to validate a tool designed to assess mHealth apps. Studies that used these tools for the assessment of mHealth apps but did not include any psychometric validation were excluded. The measurement tools were analyzed according to the 10 psychometric properties described in the COSMIN guideline. The dimensions and items analyzed in each tool were also analyzed. Results: The initial search showed 3372 articles. Only 10 finally met the inclusion criteria and were chosen for analysis in this review, analyzing 8 measurement tools. Of these tools, 4 validated ?5 psychometric properties defined in the COSMIN guideline. Although some of the tools only measure the usability dimension, other tools provide information such as engagement, esthetics, or functionality. Furthermore, 2 measurement tools, Mobile App Rating Scale and mHealth Apps Usability Questionnaire, have a user version, as well as a professional version. Conclusions: The Health Information Technology Usability Evaluation Scale and the Measurement Scales for Perceived Usefulness and Perceived Ease of Use were the most validated tools, but they were very focused on usability. The Mobile App Rating Scale showed a moderate number of validated psychometric properties, measures a significant number of quality dimensions, and has been validated in a large number of mHealth apps, and its use is widespread. It is suggested that the continuation of the validation of this tool in other psychometric properties could provide an appropriate option for evaluating the quality of mHealth apps. ", doi="10.2196/15433", url="https://mhealth.jmir.org/2021/12/e15433", url="http://www.ncbi.nlm.nih.gov/pubmed/34855618" } @Article{info:doi/10.2196/28204, author="Motahari-Nezhad, Hossein and P{\'e}ntek, M{\'a}rta and Gul{\'a}csi, L{\'a}szl{\'o} and Zrubka, Zsombor", title="Outcomes of Digital Biomarker--Based Interventions: Protocol for a Systematic Review of Systematic Reviews", journal="JMIR Res Protoc", year="2021", month="Nov", day="24", volume="10", number="11", pages="e28204", keywords="digital biomarker", keywords="outcome", keywords="systematic review", keywords="meta-analysis", keywords="digital health", keywords="mobile health", keywords="Grading of Recommendations, Assessment, Development and Evaluation", keywords="AMSTAR-2", keywords="review", keywords="biomarkers", keywords="clinical outcome", keywords="interventions", keywords="wearables", keywords="portables", keywords="digestables", keywords="implants", abstract="Background: Digital biomarkers?are?defined?as objective, quantifiable, physiological, and behavioral data that are collected and measured using?digital?devices such as portables, wearables, implantables, or digestibles. For their widespread adoption in publicly financed health care systems, it is important to understand how their benefits translate into improved patient outcomes, which is essential for demonstrating their value. Objective: The paper presents the protocol for a systematic review that aims to assess the quality and strength of the evidence reported in systematic reviews regarding the impact of digital biomarkers on clinical outcomes compared to interventions without digital biomarkers. Methods: A comprehensive search for reviews from 2019 to 2020 will be conducted in PubMed and the Cochrane Library using keywords related to digital biomarkers and a filter for systematic reviews. Original full-text English publications of systematic reviews comparing clinical outcomes of interventions with and without digital biomarkers via meta-analysis will be included. The AMSTAR-2 tool will be used to assess the methodological quality of these reviews. To assess the quality of evidence, we will evaluate the systematic reviews using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) tool. To detect the possible presence of reporting bias, we will determine whether a protocol was published prior to the start of the studies. A qualitative summary of the results by digital biomarker technology and outcomes will be provided. Results: This protocol was submitted before data collection. Search, screening, and data extraction will commence in December 2021 in accordance with the published protocol. Conclusions: Our study will provide a comprehensive summary of the highest level of evidence available on digital biomarker interventions, providing practical guidance for health care providers. Our results will help identify clinical areas in which the use of digital biomarkers has led to favorable clinical outcomes. In addition, our findings will highlight areas of evidence gaps where the clinical benefits of digital biomarkers have not yet been demonstrated. International Registered Report Identifier (IRRID): PRR1-10.2196/28204 ", doi="10.2196/28204", url="https://www.researchprotocols.org/2021/11/e28204", url="http://www.ncbi.nlm.nih.gov/pubmed/34821568" } @Article{info:doi/10.2196/28384, author="Woulfe, Fionn and Fadahunsi, Philip Kayode and Smith, Simon and Chirambo, Baxter Griphin and Larsson, Emma and Henn, Patrick and Mawkin, Mala and O' Donoghue, John", title="Identification and Evaluation of Methodologies to Assess the Quality of Mobile Health Apps in High-, Low-, and Middle-Income Countries: Rapid Review", journal="JMIR Mhealth Uhealth", year="2021", month="Oct", day="12", volume="9", number="10", pages="e28384", keywords="mHealth app", keywords="health app", keywords="mobile health", keywords="health website", keywords="quality", keywords="quality assessment", keywords="methodology", keywords="high-income country", keywords="low-income country", keywords="middle-income country", keywords="LMIC", keywords="mobile phone", abstract="Background: In recent years, there has been rapid growth in the availability and use of mobile health (mHealth) apps around the world. A consensus regarding an accepted standard to assess the quality of such apps has yet to be reached. A factor that exacerbates the challenge of mHealth app quality assessment is variations in the interpretation of quality and its subdimensions. Consequently, it has become increasingly difficult for health care professionals worldwide to distinguish apps of high quality from those of lower quality. This exposes both patients and health care professionals to unnecessary risks. Despite progress, limited understanding of the contributions of researchers in low- and middle-income countries (LMICs) exists on this topic. Furthermore, the applicability of quality assessment methodologies in LMIC settings remains relatively unexplored. Objective: This rapid review aims to identify current methodologies in the literature to assess the quality of mHealth apps, understand what aspects of quality these methodologies address, determine what input has been made by authors from LMICs, and examine the applicability of such methodologies in LMICs. Methods: This review was registered with PROSPERO (International Prospective Register of Systematic Reviews). A search of PubMed, EMBASE, Web of Science, and Scopus was performed for papers related to mHealth app quality assessment methodologies, which were published in English between 2005 and 2020. By taking a rapid review approach, a thematic and descriptive analysis of the papers was performed. Results: Electronic database searches identified 841 papers. After the screening process, 52 papers remained for inclusion. Of the 52 papers, 5 (10\%) proposed novel methodologies that could be used to evaluate mHealth apps of diverse medical areas of interest, 8 (15\%) proposed methodologies that could be used to assess apps concerned with a specific medical focus, and 39 (75\%) used methodologies developed by other published authors to evaluate the quality of various groups of mHealth apps. The authors in 6\% (3/52) of papers were solely affiliated to institutes in LMICs. A further 15\% (8/52) of papers had at least one coauthor affiliated to an institute in an LMIC. Conclusions: Quality assessment of mHealth apps is complex in nature and at times subjective. Despite growing research on this topic, to date, an all-encompassing appropriate means for evaluating the quality of mHealth apps does not exist. There has been engagement with authors affiliated to institutes across LMICs; however, limited consideration of current generic methodologies for application in LMIC settings has been identified. Trial Registration: PROSPERO CRD42020205149; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=205149 ", doi="10.2196/28384", url="https://mhealth.jmir.org/2021/10/e28384", url="http://www.ncbi.nlm.nih.gov/pubmed/34636737" } @Article{info:doi/10.2196/32544, author="Zhao, Liuhong and Chen, Jingfen and Lan, Liuying and Deng, Ni and Liao, Yan and Yue, Liqun and Chen, Innie and Wen, Wu Shi and Xie, Ri-hua", title="Effectiveness of Telehealth Interventions for Women With Postpartum Depression: Systematic Review and Meta-analysis", journal="JMIR Mhealth Uhealth", year="2021", month="Oct", day="7", volume="9", number="10", pages="e32544", keywords="telehealth", keywords="postpartum depression", keywords="anxiety", keywords="meta-analysis", abstract="Background: Postpartum depression (PPD) is a prevalent mental health problem with serious adverse consequences for affected women and their infants. Clinical trials have found that telehealth interventions for women with PPD result in increased accessibility and improved treatment effectiveness. However, no comprehensive synthesis of evidence from clinical trials by systematic review has been conducted. Objective: The aim of this study is to evaluate the effectiveness of telehealth interventions in reducing depressive symptoms and anxiety in women with PPD. To enhance the homogeneity and interpretability of the findings, this systematic review focuses on PPD measured by the Edinburgh Postnatal Depression Scale (EPDS). Methods: PubMed, The Cochrane Library, CINAHL, PsycINFO, CNKI, and Wanfang were electronically searched to identify randomized controlled trials (RCTs) on the effectiveness of telehealth interventions for women with PPD from inception to February 28, 2021. Data extraction and quality assessment were performed independently by two researchers. The quality of included studies was assessed using the Cochrane risk-of-bias tool, and meta-analysis was performed using RevMan 5.4 software. Results: Following the search, 9 RCTs with a total of 1958 women with PPD were included. The EPDS (mean difference=--2.99, 95\% CI --4.52 to --1.46; P<.001) and anxiety (standardized mean difference=--0.39, 95\% CI --0.67 to --0.12; P=.005) scores were significantly lower in the telehealth group compared with the control group. Significant subgroup differences were found in depressive symptoms according to the severity of PPD, telehealth technology, specific therapy, and follow-up time (P<.001). Conclusions: Telehealth interventions could effectively reduce the symptoms of depression and anxiety in women with PPD. However, better designed and more rigorous large-scale RCTs targeting specific therapies are needed to further explore the potential of telehealth interventions for PPD. Trial Registration: PROSPERO CRD42021258541; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=258541 ", doi="10.2196/32544", url="https://mhealth.jmir.org/2021/10/e32544", url="http://www.ncbi.nlm.nih.gov/pubmed/34617909" } @Article{info:doi/10.2196/24527, author="Tam, Lon Hon and Wong, Ling Eliza Mi and Cheung, Kin and Chung, Fung Siu", title="Effectiveness of Text Messaging Interventions on Blood Pressure Control Among Patients With Hypertension: Systematic Review of Randomized Controlled Trials", journal="JMIR Mhealth Uhealth", year="2021", month="Sep", day="22", volume="9", number="9", pages="e24527", keywords="text messaging", keywords="hypertension", keywords="blood pressure", keywords="mHealth", keywords="meta-analysis", abstract="Background: Controlling blood pressure (BP) is an international health concern, and high BP is a major contributor to cardiovascular disease mortality. Evidence has shown that educational interventions directed at patients potentially improve BP control and adherence to medications and lifestyle modifications. In addition, a text messaging intervention has a potential effect on BP control; however, the dosage of a text messaging intervention has not been determined in previous reviews, resulting in difficult application in practice. Objective: This review aimed to identify the effectiveness of a text messaging intervention on hypertension management with a specific focus on the dosage of text messaging and the type of additional interventions with text messaging. Methods: A systematic review was conducted and reported on in accordance with PRISMA guideline. Participants were aged 18 years and older and diagnosed with primary hypertension. The included studies used text messaging as a component of the intervention. We searched for randomized controlled trials published until June 30, 2020, from the following health-related electronic databases: Embase, Medline, CINAHL Complete, PsycINFO, and Scopus. Data were extracted for qualitative synthesis and meta-analysis. The Physiotherapy Evidence Database Scale was used to assess the methodological quality of each study, and the quality of the included studies was assessed independently by two authors. Results: Twelve studies met the inclusion criteria. The overall methodological quality was fair (mean score 5.75). The frequency of text message delivery varied from daily to biweekly. Health education was identified in 4 studies as an additional intervention with text messaging. The overall results showed that the text messaging intervention significantly reduced systolic BP (SBP) but not diastolic BP (DBP). There was no significant difference in BP reduction between studies that lasted 6 months or less and those that lasted more than 7 months. Seven studies that lasted 6 months or less involving 1428 patients with hypertension were pooled for further meta-analysis. Text messages delivered at a lower frequency (once per week or less) had a small effect on SBP reduction (effect size 0.35, P<.01) and DBP reduction (effect size 0.28, P=.01). In addition, the use of a text messaging intervention halved the odds of uncontrolled BP among patients with hypertension in 6 months (odds ratio 0.46, P=.02). Conclusions: This review found that a text messaging intervention was effective in BP control. One-way text messaging delivered in a weekly manner was suggested to be effective and required fewer resources. Future studies should use different forms of text message and be integrated into other interventions to improve adherence behaviors and BP control among patients with hypertension. ", doi="10.2196/24527", url="https://mhealth.jmir.org/2021/9/e24527", url="http://www.ncbi.nlm.nih.gov/pubmed/34550078" } @Article{info:doi/10.2196/24352, author="Flanagan, Olivia and Chan, Amy and Roop, Partha and Sundram, Frederick", title="Using Acoustic Speech Patterns From Smartphones to Investigate Mood Disorders: Scoping Review", journal="JMIR Mhealth Uhealth", year="2021", month="Sep", day="17", volume="9", number="9", pages="e24352", keywords="smartphone", keywords="data science", keywords="speech patterns", keywords="mood disorders", keywords="diagnosis", keywords="monitoring", abstract="Background: Mood disorders are commonly underrecognized and undertreated, as diagnosis is reliant on self-reporting and clinical assessments that are often not timely. Speech characteristics of those with mood disorders differs from healthy individuals. With the wide use of smartphones, and the emergence of machine learning approaches, smartphones can be used to monitor speech patterns to help the diagnosis and monitoring of mood disorders. Objective: The aim of this review is to synthesize research on using speech patterns from smartphones to diagnose and monitor mood disorders. Methods: Literature searches of major databases, Medline, PsycInfo, EMBASE, and CINAHL, initially identified 832 relevant articles using the search terms ``mood disorders'', ``smartphone'', ``voice analysis'', and their variants. Only 13 studies met inclusion criteria: use of a smartphone for capturing voice data, focus on diagnosing or monitoring a mood disorder(s), clinical populations recruited prospectively, and in the English language only. Articles were assessed by 2 reviewers, and data extracted included data type, classifiers used, methods of capture, and study results. Studies were analyzed using a narrative synthesis approach. Results: Studies showed that voice data alone had reasonable accuracy in predicting mood states and mood fluctuations based on objectively monitored speech patterns. While a fusion of different sensor modalities revealed the highest accuracy (97.4\%), nearly 80\% of included studies were pilot trials or feasibility studies without control groups and had small sample sizes ranging from 1 to 73 participants. Studies were also carried out over short or varying timeframes and had significant heterogeneity of methods in terms of the types of audio data captured, environmental contexts, classifiers, and measures to control for privacy and ambient noise. Conclusions: Approaches that allow smartphone-based monitoring of speech patterns in mood disorders are rapidly growing. The current body of evidence supports the value of speech patterns to monitor, classify, and predict mood states in real time. However, many challenges remain around the robustness, cost-effectiveness, and acceptability of such an approach and further work is required to build on current research and reduce heterogeneity of methodologies as well as clinical evaluation of the benefits and risks of such approaches. ", doi="10.2196/24352", url="https://mhealth.jmir.org/2021/9/e24352", url="http://www.ncbi.nlm.nih.gov/pubmed/34533465" } @Article{info:doi/10.2196/28378, author="Chen, Chih-Hao and Lin, Haley Heng-Yu and Wang, Mao-Che and Chu, Yuan-Chia and Chang, Chun-Yu and Huang, Chii-Yuan and Cheng, Yen-Fu", title="Diagnostic Accuracy of Smartphone-Based Audiometry for Hearing Loss Detection: Meta-analysis", journal="JMIR Mhealth Uhealth", year="2021", month="Sep", day="10", volume="9", number="9", pages="e28378", keywords="audiometry", keywords="hearing loss", keywords="hearing test", keywords="mhealth", keywords="mobile health", keywords="digital health", keywords="meta-analysis", keywords="mobile phone", keywords="smartphone diagnostic test accuracy", abstract="Background: Hearing loss is one of the most common disabilities worldwide and affects both individual and public health. Pure tone audiometry (PTA) is the gold standard for hearing assessment, but it is often not available in many settings, given its high cost and demand for human resources. Smartphone-based audiometry may be equally effective and can improve access to adequate hearing evaluations. Objective: The aim of this systematic review is to synthesize the current evidence of the role of smartphone-based audiometry in hearing assessments and further explore the factors that influence its diagnostic accuracy. Methods: Five databases---PubMed, Embase, Cochrane Library, Web of Science, and Scopus---were queried to identify original studies that examined the diagnostic accuracy of hearing loss measurement using smartphone-based devices with conventional PTA as a reference test. A bivariate random-effects meta-analysis was performed to estimate the pooled sensitivity and specificity. The factors associated with diagnostic accuracy were identified using a bivariate meta-regression model. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Results: In all, 25 studies with a total of 4470 patients were included in the meta-analysis. The overall sensitivity, specificity, and area under the receiver operating characteristic curve for smartphone-based audiometry were 89\% (95\% CI 83\%-93\%), 93\% (95\% CI 87\%-97\%), and 0.96 (95\% CI 0.93-0.97), respectively; the corresponding values for the smartphone-based speech recognition test were 91\% (95\% CI 86\%-94\%), 88\% (95\% CI 75\%-94\%), and 0.93 (95\% CI 0.90-0.95), respectively. Meta-regression analysis revealed that patient age, equipment used, and the presence of soundproof booths were significantly related to diagnostic accuracy. Conclusions: We have presented comprehensive evidence regarding the effectiveness of smartphone-based tests in diagnosing hearing loss. Smartphone-based audiometry may serve as an accurate and accessible approach to hearing evaluations, especially in settings where conventional PTA is unavailable. ", doi="10.2196/28378", url="https://mhealth.jmir.org/2021/9/e28378/", url="http://www.ncbi.nlm.nih.gov/pubmed/34515644" } @Article{info:doi/10.2196/29381, author="Azevedo, Salome and Rodrigues, Cipriano Teresa and Londral, Rita Ana", title="Domains and Methods Used to Assess Home Telemonitoring Scalability: Systematic Review", journal="JMIR Mhealth Uhealth", year="2021", month="Aug", day="19", volume="9", number="8", pages="e29381", keywords="telemonitoring", keywords="scalability", keywords="home telecare", keywords="systematic review", abstract="Background: The COVID-19 pandemic catalyzed the adoption of home telemonitoring to cope with social distancing challenges. Recent research on home telemonitoring demonstrated benefits concerning the capacity, patient empowerment, and treatment commitment of health care systems. Moreover, for some diseases, it revealed significant improvement in clinical outcomes. Nevertheless, when policy makers and practitioners decide whether to scale-up a technology-based health intervention from a research study to mainstream care delivery, it is essential to assess other relevant domains, such as its feasibility to be expanded under real-world conditions. Therefore, scalability assessment is critical, and it encompasses multiple domains to ensure population-wide access to the benefits of the growing technological potential for home telemonitoring services in health care. Objective: This systematic review aims to identify the domains and methods used in peer-reviewed research studies that assess the scalability of home telemonitoring--based interventions under real-world conditions. Methods: The authors followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines and used multiple databases (PubMed, Scopus, Web of Science, and EconLit). An integrative synthesis of the eligible studies was conducted to better explore each intervention and summarize relevant information concerning the target audience, intervention duration and setting, and type of technology. Each study design was classified based on the strength of its evidence. Lastly, the authors conducted narrative and thematic analyses to identify the domains, and qualitative and quantitative methods used to support scalability assessment. Results: This review evaluated 13 articles focusing on the potential of scaling up a home telemonitoring intervention. Most of the studies considered the following domains relevant for scalability assessment: problem (13), intervention (12), effectiveness (13), and costs and benefits (10). Although cost-effectiveness was the most common evaluation method, the authors identified seven additional cost analysis methods to evaluate the costs. Other domains were less considered, such as the sociopolitical context (2), workforce (4), and technological infrastructure (3). Researchers used different methodological approaches to assess the effectiveness, costs and benefits, fidelity, and acceptability. Conclusions: This systematic review suggests that when assessing scalability, researchers select the domains specifically related to the intervention while ignoring others related to the contextual, technological, and environmental factors, which are also relevant. Additionally, studies report using different methods to evaluate the same domain, which makes comparison difficult. Future work should address research on the minimum required domains to assess the scalability of remote telemonitoring services and suggest methods that allow comparison among studies to provide better support to decision makers during large-scale implementation. ", doi="10.2196/29381", url="https://mhealth.jmir.org/2021/8/e29381", url="http://www.ncbi.nlm.nih.gov/pubmed/34420917" } @Article{info:doi/10.2196/17411, author="Patel, Vikas and Orchanian-Cheff, Ani and Wu, Robert", title="Evaluating the Validity and Utility of Wearable Technology for Continuously Monitoring Patients in a Hospital Setting: Systematic Review", journal="JMIR Mhealth Uhealth", year="2021", month="Aug", day="18", volume="9", number="8", pages="e17411", keywords="wearable", keywords="inpatient", keywords="continuous monitoring", abstract="Background: The term posthospital syndrome has been used to describe the condition in which older patients are transiently frail after hospitalization and have a high chance of readmission. Since low activity and poor sleep during hospital stay may contribute to posthospital syndrome, the continuous monitoring of such parameters by using affordable wearables may help to reduce the prevalence of this syndrome. Although there have been systematic reviews of wearables for physical activity monitoring in hospital settings, there are limited data on the use of wearables for measuring other health variables in hospitalized patients. Objective: This systematic review aimed to evaluate the validity and utility of wearable devices for monitoring hospitalized patients. Methods: This review involved a comprehensive search of 7 databases and included articles that met the following criteria: inpatients must be aged >18 years, the wearable devices studied in the articles must be used to continuously monitor patients, and wearables should monitor biomarkers other than solely physical activity (ie, heart rate, respiratory rate, blood pressure, etc). Only English-language studies were included. From each study, we extracted basic demographic information along with the characteristics of the intervention. We assessed the risk of bias for studies that validated their wearable readings by using a modification of the Consensus-Based Standards for the Selection of Health Status Measurement Instruments. Results: Of the 2012 articles that were screened, 14 studies met the selection criteria. All included articles were observational in design. In total, 9 different commercial wearables for various body locations were examined in this review. The devices collectively measured 7 different health parameters across all studies (heart rate, sleep duration, respiratory rate, oxygen saturation, skin temperature, blood pressure, and fall risk). Only 6 studies validated their results against a reference device or standard. There was a considerable risk of bias in these studies due to the low number of patients in most of the studies (4/6, 67\%). Many studies that validated their results found that certain variables were inaccurate and had wide limits of agreement. Heart rate and sleep were the parameters with the most evidence for being valid for in-hospital monitoring. Overall, the mean patient completion rate across all 14 studies was >90\%. Conclusions: The included studies suggested that wearable devices show promise for monitoring the heart rate and sleep of patients in hospitals. Many devices were not validated in inpatient settings, and the readings from most of the devices that were validated in such settings had wide limits of agreement when compared to gold standards. Even some medical-grade devices were found to perform poorly in inpatient settings. Further research is needed to determine the accuracy of hospitalized patients' digital biomarker readings and eventually determine whether these wearable devices improve health outcomes. ", doi="10.2196/17411", url="https://mhealth.jmir.org/2021/8/e17411", url="http://www.ncbi.nlm.nih.gov/pubmed/34406121" } @Article{info:doi/10.2196/24308, author="Domin, Alex and Spruijt-Metz, Donna and Theisen, Daniel and Ouzzahra, Yacine and V{\"o}gele, Claus", title="Smartphone-Based Interventions for Physical Activity Promotion: Scoping Review of the Evidence Over the Last 10 Years", journal="JMIR Mhealth Uhealth", year="2021", month="Jul", day="21", volume="9", number="7", pages="e24308", keywords="scoping review", keywords="smartphone application", keywords="physical activity", keywords="behavior change", keywords="mobile health", keywords="research design", keywords="mHealth", keywords="adolescents", keywords="adults", keywords="BCT", keywords="mobile phonescoping review", keywords="mobile phone", abstract="Background: Several reviews of mobile health (mHealth) physical activity (PA) interventions suggest their beneficial effects on behavior change in adolescents and adults. Owing to the ubiquitous presence of smartphones, their use in mHealth PA interventions seems obvious; nevertheless, there are gaps in the literature on the evaluation reporting processes and best practices of such interventions. Objective: The primary objective of this review is to analyze the development and evaluation trajectory of smartphone-based mHealth PA interventions and to review systematic theory- and evidence-based practices and methods that are implemented along this trajectory. The secondary objective is to identify the range of evidence (both quantitative and qualitative) available on smartphone-based mHealth PA interventions to provide a comprehensive tabular and narrative review of the available literature in terms of its nature, features, and volume. Methods: We conducted a scoping review of qualitative and quantitative studies examining smartphone-based PA interventions published between 2008 and 2018. In line with scoping review guidelines, studies were not rejected based on their research design or quality. This review, therefore, includes experimental and descriptive studies, as well as reviews addressing smartphone-based mHealth interventions aimed at promoting PA in all age groups (with a subanalysis conducted for adolescents). Two groups of studies were additionally included: reviews or content analyses of PA trackers and meta-analyses exploring behavior change techniques and their efficacy. Results: Included articles (N=148) were categorized into 10 groups: commercial smartphone app content analyses, smartphone-based intervention review studies, activity tracker content analyses, activity tracker review studies, meta-analyses of PA intervention studies, smartphone-based intervention studies, qualitative formative studies, app development descriptive studies, qualitative follow-up studies, and other related articles. Only 24 articles targeted children or adolescents (age range: 5-19 years). There is no agreed evaluation framework or taxonomy to code or report smartphone-based PA interventions. Researchers did not state the coding method, used various evaluation frameworks, or used different versions of behavior change technique taxonomies. In addition, there is no consensus on the best behavior change theory or model that should be used in smartphone-based interventions for PA promotion. Commonly reported systematic practices and methods have been successfully identified. They include PA recommendations, trial designs (randomized controlled trials, experimental trials, and rapid design trials), mixed methods data collection (surveys, questionnaires, interviews, and focus group discussions), scales to assess app quality, and industry-recognized reporting guidelines. Conclusions: Smartphone-based mHealth interventions aimed at promoting PA showed promising results for behavior change. Although there is a plethora of published studies on the adult target group, the number of studies and consequently the evidence base for adolescents is limited. Overall, the efficacy of smartphone-based mHealth PA interventions can be considerably improved through a more systematic approach of developing, reporting, and coding of the interventions. ", doi="10.2196/24308", url="https://mhealth.jmir.org/2021/7/e24308", url="http://www.ncbi.nlm.nih.gov/pubmed/34287209" } @Article{info:doi/10.2196/28168, author="Sommers-Spijkerman, Marion and Austin, Judith and Bohlmeijer, Ernst and Pots, Wendy", title="New Evidence in the Booming Field of Online Mindfulness: An Updated Meta-analysis of Randomized Controlled Trials", journal="JMIR Ment Health", year="2021", month="Jul", day="19", volume="8", number="7", pages="e28168", keywords="mindfulness", keywords="mental health", keywords="intervention", keywords="online", keywords="meta-analysis", keywords="mobile phone", abstract="Background: There is a need to regularly update the evidence base on the effectiveness of online mindfulness-based interventions (MBIs), especially considering how fast this field is growing and developing. Objective: This study presents an updated meta-analysis of randomized controlled trials assessing the effects of online MBIs on mental health and the potential moderators of these effects. Methods: We conducted a systematic literature search in PsycINFO, PubMed, and Web of Science up to December 4, 2020, and included 97 trials, totaling 125 comparisons. Pre-to-post and pre-to-follow-up between-group effect sizes (Hedges g) were calculated for depression, anxiety, stress, well-being, and mindfulness using a random effects model. Results: The findings revealed statistically significant moderate pre-to-post effects on depression (g=0.34, 95\% CI 0.18-0.50; P<.001), stress (g=0.44, 95\% CI 0.32-0.55; P<.001), and mindfulness (g=0.40, 95\% CI 0.30-0.50; P<.001) and small effects on anxiety (g=0.26, 95\% CI 0.18-0.33; P<.001). For well-being, a significant small effect was found only when omitting outliers (g=0.22, 95\% CI 0.15-0.29; P<.001) or low-quality studies (g=0.26, 95\% CI 0.12-0.41; P<.001). Significant but small follow-up effects were found for depression (g=0.25, 95\% CI 0.12-0.38) and anxiety (g=0.23, 95\% CI 0.13-0.32). Subgroup analyses revealed that online MBIs resulted in higher effect sizes for stress when offered with guidance. In terms of stress and mindfulness, studies that used inactive control conditions yielded larger effects. For anxiety, populations with psychological symptoms had higher effect sizes. Adherence rates for the interventions ranged from 35\% to 92\%, but most studies lacked clear definitions or cut-offs. Conclusions: Our findings not only demonstrate that online MBIs are booming but also corroborate previous findings that online MBIs are beneficial for improving mental health outcomes in a broad range of populations. To advance the field of online MBIs, future trials should pay specific attention to methodological quality, adherence, and long-term follow-up measurements. ", doi="10.2196/28168", url="https://mental.jmir.org/2021/7/e28168", url="http://www.ncbi.nlm.nih.gov/pubmed/34279240" } @Article{info:doi/10.2196/26098, author="Qian, Jiafen and Wu, Tingting and Lv, Meina and Fang, Zongwei and Chen, Mingrong and Zeng, Zhiwei and Jiang, Shaojun and Chen, Wenjun and Zhang, Jinhua", title="The Value of Mobile Health in Improving Breastfeeding Outcomes Among Perinatal or Postpartum Women: Systematic Review and Meta-analysis of Randomized Controlled Trials", journal="JMIR Mhealth Uhealth", year="2021", month="Jul", day="16", volume="9", number="7", pages="e26098", keywords="mHealth", keywords="breastfeeding", keywords="randomized controlled trial", keywords="meta-analysis", abstract="Background: Breastfeeding is essential for maintaining the health of mothers and babies. Breastfeeding can reduce the infection rate and mortality in newborns, and can reduce the chances of overweight and obesity in children and adolescents. For mothers, a longer duration of breastfeeding can reduce the risk of breast cancer, ovarian cancer, and type 2 diabetes. Although breastfeeding has many benefits, the global breastfeeding rate is low. With the progress of time, the popularity of mobile devices has increased rapidly, and interventions based on mobile health (mHealth) may have the potential to facilitate the improvement of the breastfeeding status. Objective: The main objective of this study was to analyze the existing evidence to determine whether mHealth-based interventions can improve the status of breastfeeding. Methods: We systematically searched multiple electronic databases (PubMed, Web of Science, The Cochrane Library, Embase, CNKI, WanFang, and Vip ) to identify eligible studies published from 1966 to October 29, 2020. Included studies were randomized controlled trials (RCTs) studying the influence of mHealth on breastfeeding. The Cochrane Collaboration Risk of Bias tool was used to examine the risk of publication bias. RevMan 5.3 was used to analyze the data. Results: A total of 15 RCTs with a total sample size of 4366 participates met the inclusion criteria. Compared with usual care, interventions based on mHealth significantly increased the postpartum exclusive breastfeeding rate (odds ratio [OR] 3.18, 95\% CI 2.20-4.59; P<.001), enhanced breastfeeding self-efficacy (mean difference [MD] 8.15, 95\% CI 3.79-12.51; P=.002; I2=88\%), reduced health problems in infants (OR 0.62, 95\% CI 0.43-0.90; P=.01; I2=0\%), and improved participants' attitudes toward breastfeeding compared with usual care (MD 3.94, 95\% CI 1.95-5.92; P<.001; I2=0\%). There was no significant difference in the initiation of breastfeeding within an hour of birth between the intervention group and the usual care group (OR 1.26, 95\% CI 0.55-2.90; P=.59). In addition, subgroup analysis was carried out according to different subjects and publication times. The results showed that the breastfeeding rate was not limited by the types of subjects. The breastfeeding rate based on mHealth at 1 month and 2 months after delivery did not change over the time of publication (2009 to 2020), and the breastfeeding rate based on mHealth at 3 months and 6 months after delivery gradually increased with time (2009 to 2020). Conclusions: Interventions based on mHealth can significantly improve the rate of postpartum exclusive breastfeeding, breastfeeding efficacy, and participants' attitudes toward breastfeeding, and reduce health problems in infants. Therefore, encouraging women to join the mHealth team is feasible, and breastfeeding-related information can be provided through simple measures, such as text messages, phone calls, and the internet, to improve the health of postpartum women and their babies. ", doi="10.2196/26098", url="https://mhealth.jmir.org/2021/7/e26098", url="http://www.ncbi.nlm.nih.gov/pubmed/34269681" } @Article{info:doi/10.2196/25381, author="Rampioni, Margherita and Stara, Vera and Felici, Elisa and Rossi, Lorena and Paolini, Susy", title="Embodied Conversational Agents for Patients With Dementia: Thematic Literature Analysis", journal="JMIR Mhealth Uhealth", year="2021", month="Jul", day="16", volume="9", number="7", pages="e25381", keywords="dementia", keywords="patient with dementia", keywords="older adults with dementia", keywords="embodied conversational agent", keywords="virtual personal assistant", keywords="virtual agent", keywords="virtual companion", keywords="design for older adults", keywords="patients", keywords="elderly", keywords="virtual", keywords="personal assistant", keywords="cognitive", keywords="cognitive impairment", abstract="Background: As the world's population rapidly ages, the number of older adults with cognitive impairment will also increase. Several studies have identified numerous complex needs of people with dementia, which assistive technologies still fail to support. Recent trends have led to an increasing focus on the use of embodied conversational agents (ECAs) as virtual entities able to interact with a person through natural and familiar verbal and nonverbal communication. The use of ECAs could improve the accessibility and acceptance of assistive technologies matching those high-level needs that are not well covered to date. Objective: The aim of this thematic literature analysis was to map current studies in the field of designing ECAs for patients with dementia in order to identify the existing research trend and possible gaps that need to be covered in the near future. The review questions in this study were as follows: (1) what research frameworks are used to study the interaction between patients with dementia and ECAs? (2) what are the findings? and (3) what are the barriers reported in these studies? Methods: Separate literature searches were conducted in PubMed, Web of Science, Scopus, and Embase databases by using specific umbrella phrases to target the population (patients with dementia) and the technology-based intervention (embodied conversational agent). Studies that met the inclusion criteria were appraised through the Mixed Methods Appraisal Tool and then discussed in a thematic analysis. Results: The search process identified 115 records from the databases and study references. After duplicates (n=45) were removed, 70 papers remained for the initial screening. A total of 7 studies were finally included in the qualitative synthesis. A thematic analysis of the reviewed studies identified major themes and subthemes: the research frameworks used to gather users' perspectives on ECAs (theme 1), the insights shared by the 7 studies as well as the value of user involvement in the development phases and the challenge of matching the system functionalities with the users' needs (theme 2), and the main methodological and technical problems faced by each study team (theme 3). Conclusions: Our thematic literature analysis shows that the field of ECAs is novel and poorly discussed in the scientific community and that more sophisticated study designs and proofs of efficacy of the approach are required. Therefore, by analyzing the main topic of the narrative review, this study underscores the challenge of synchronizing and harmonizing knowledge, efforts, and challenges in the dementia care field and its person-centered paradigm through the user-centered design approach. Enabling strict collaboration between interdisciplinary research networks, medical scientists, technology developers, patients, and their formal and informal caregivers is still a great challenge in the field of technologies for older adults. ", doi="10.2196/25381", url="https://mhealth.jmir.org/2021/7/e25381", url="http://www.ncbi.nlm.nih.gov/pubmed/34269686" } @Article{info:doi/10.2196/20037, author="K{\"o}nig, Maria Laura and Attig, Christiane and Franke, Thomas and Renner, Britta", title="Barriers to and Facilitators for Using Nutrition Apps: Systematic Review and Conceptual Framework", journal="JMIR Mhealth Uhealth", year="2021", month="Jun", day="19", volume="9", number="6", pages="e20037", keywords="nutrition apps", keywords="mHealth", keywords="digital health", keywords="usage facilitators", keywords="usage barriers", abstract="Background: Nutrition apps are effective in changing eating behavior and diet-related health risk factors. However, while they may curb growing overweight and obesity rates, widespread adoption is yet to be achieved. Hence, profound knowledge regarding factors motivating and hindering (long-term) nutrition app use is crucial for developing design guidelines aimed at supporting uptake and prolonged use of nutrition apps. Objective: In this systematic review, we synthesized the literature on barriers to and facilitators for nutrition app use across disciplines including empirical qualitative and quantitative studies with current users, ex-users, and nonusers of nutrition apps. Methods: A systematic literature search including 6 databases (PubMed, Web of Science, PsychINFO, PSYNDEX, PsycArticles, and SPORTDiscus) as well as backward and forward citation search was conducted. Search strategy, inclusion and exclusion criteria, and the planned data extraction process were preregistered. All empirical qualitative and quantitative studies published in German or English were eligible for inclusion if they examined adolescents (aged 13-18) or adults who were either current users, ex-users, and nonusers of nutrition apps. Based on qualitative content analysis, extracted individual barriers and facilitators were grouped into categories. Results: A total of 28 publications were identified as eligible. A framework with a 3-level hierarchy was designed which grouped 328 individual barriers and facilitators into 23 subcategories, 12 categories, and 4 clusters that focus on either the individual user (goal setting and goal striving, motivation, routines, lack of awareness of knowledge), different aspects of the app and the smartphone (features, usability of the app or food database, technical issues, data security, accuracy/trustworthiness, costs), positive and negative outcomes of nutrition app use, or interactions between the user and their social environment. Conclusions: The resulting conceptual framework underlines a pronounced diversity of reasons for (not) using nutrition apps, indicating that there is no ``one-size-fits-all'' approach for uptake and prolonged use of nutrition apps. Hence, tailoring nutrition apps to needs of specific user groups seems promising for increasing engagement. ", doi="10.2196/20037", url="https://mhealth.jmir.org/2021/6/e20037/" } @Article{info:doi/10.2196/15654, author="Aljedaani, Bakheet and Babar, Ali M.", title="Challenges With Developing Secure Mobile Health Applications: Systematic Review", journal="JMIR Mhealth Uhealth", year="2021", month="Jun", day="21", volume="9", number="6", pages="e15654", keywords="systematic literature review", keywords="mHealth apps", keywords="secure apps", keywords="developers", keywords="security knowledge", abstract="Background: Mobile health (mHealth) apps have gained significant popularity over the last few years due to their tremendous benefits, such as lowering health care costs and increasing patient awareness. However, the sensitivity of health care data makes the security of mHealth apps a serious concern. Poor security practices and lack of security knowledge on the developers' side can cause several vulnerabilities in mHealth apps. Objective: In this review paper, we aimed to identify and analyze the reported challenges concerning security that developers of mHealth apps face. Additionally, our study aimed to develop a conceptual framework with the challenges for developing secure apps faced by mHealth app development organizations. The knowledge of such challenges can help to reduce the risk of developing insecure mHealth apps. Methods: We followed the systematic literature review method for this review. We selected studies that were published between January 2008 and October 2020 since the major app stores launched in 2008. We selected 32 primary studies using predefined criteria and used a thematic analysis method for analyzing the extracted data. Results: Of the 1867 articles obtained, 32 were included in this review based on the predefined criteria. We identified 9 challenges that can affect the development of secure mHealth apps. These challenges include lack of security guidelines and regulations for developing secure mHealth apps (20/32, 63\%), developers' lack of knowledge and expertise for secure mHealth app development (18/32, 56\%), lack of stakeholders' involvement during mHealth app development (6/32, 19\%), no/little developer attention towards the security of mHealth apps (5/32, 16\%), lack of resources for developing a secure mHealth app (4/32, 13\%), project constraints during the mHealth app development process (4/32, 13\%), lack of security testing during mHealth app development (4/32, 13\%), developers' lack of motivation and ethical considerations (3/32, 9\%), and lack of security experts' engagement during mHealth app development (2/32, 6\%). Based on our analysis, we have presented a conceptual framework that highlights the correlation between the identified challenges. Conclusions: While mHealth app development organizations might overlook security, we conclude that our findings can help them to identify the weaknesses and improve their security practices. Similarly, mHealth app developers can identify the challenges they face to develop mHealth apps that do not pose security risks for users. Our review is a step towards providing insights into the development of secure mHealth apps. Our proposed conceptual framework can act as a practice guideline for practitioners to enhance secure mHealth app development. ", doi="10.2196/15654", url="https://mhealth.jmir.org/2021/6/e15654", url="http://www.ncbi.nlm.nih.gov/pubmed/34152277" } @Article{info:doi/10.2196/20199, author="Buck, Christoph and Keweloh, Christian and Bouras, Adam and Simoes, J. Eduardo", title="Efficacy of Short Message Service Text Messaging Interventions for Postoperative Pain Management: Systematic Review", journal="JMIR Mhealth Uhealth", year="2021", month="Jun", day="16", volume="9", number="6", pages="e20199", keywords="systematic literature review", keywords="pain management", keywords="opioid", keywords="short message service (SMS)", keywords="postoperative", abstract="Background: Addiction to opiates and synthetic opioids poses a major threat to public health worldwide, with pharmaceutical opioids prescribed to manage pain constituting the main problem. To counteract this threat, suitable pain management strategies should be implemented in health care. Monitoring pain management seems to be feasible using telemedicine with a certain degree of resource intensity and digitization. As a communication channel for this type of monitoring, SMS appears to be a valid alternative. Objective: The aim of this systematic literature review was to (1) provide information on the state of research regarding postoperative pain management via SMS, (2) establish a basic understanding of SMS-based pain management, and (3) provide insight into the feasibility of these management strategies. The research question was as follows: Is postoperative pain management feasible and effective utilizing SMS? Methods: A systematic literature review was performed mainly following the PRISMA guidelines and another guide on performing a systematic literature review for information systems--related research. A search string was developed based on the objectives and research question, and eight databases were searched. Results: The initial search resulted in 2083 records, which could be narrowed down by applying various exclusion criteria. Thereby, 11 articles were identified as relevant, which were accordingly analyzed and evaluated by full-text screening. In all articles, pain management interventions were performed using SMS communication between health care professionals and patients or their legal guardians. A prospective approach was predominantly chosen as the study design (91\%) with the leading research objective of determining the intervention's feasibility (73\%). The primary reason for sending SMS messages was to monitor patients (64\%). Overall, the use of SMS improved adherence, acceptance, and satisfaction regarding postoperative pain management. With an average response rate of approximately 89.5\% (SD 3.8\%), the reliability of SMS as a communication and monitoring tool was further emphasized. This response rate is significantly higher than that for email interventions (66.63\%, P<.001). Conclusions: This study provides a comprehensive picture of the current status on postoperative pain management by SMS. Communication via SMS was beneficial in all interventions, even preoperative. Six SMS interventions could be certified by the respective institutional review board and three were Health Insurance Portability and Accountability Act--compliant. Therefore, the results of this study could be leveraged to address the opioid epidemic. Overall, the research question could be confirmed. Future research should extend this systematic literature review regarding preoperative pain management. Based on these findings, a pre- and postoperative communication model should be developed to address the opioid epidemic effectively. ", doi="10.2196/20199", url="https://mhealth.jmir.org/2021/6/e20199", url="http://www.ncbi.nlm.nih.gov/pubmed/34132646" } @Article{info:doi/10.2196/26095, author="Chen, Mingrong and Wu, Tingting and Lv, Meina and Chen, Chunmei and Fang, Zongwei and Zeng, Zhiwei and Qian, Jiafen and Jiang, Shaojun and Chen, Wenjun and Zhang, Jinhua", title="Efficacy of Mobile Health in Patients With Low Back Pain: Systematic Review and Meta-analysis of Randomized Controlled Trials", journal="JMIR Mhealth Uhealth", year="2021", month="Jun", day="11", volume="9", number="6", pages="e26095", keywords="mobile health", keywords="mHealth", keywords="low back pain", keywords="meta-analysis", keywords="pain intensity", keywords="disability", abstract="Background: Low back pain is one of the most common health problems and a main cause of disability, which imposes a great burden on patients. Mobile health (mHealth) affects many aspects of people's lives, and it has progressed rapidly, showing promise as an effective intervention for patients with low back pain. However, the efficacy of mHealth interventions for patients with low back pain remains unclear; thus, further exploration is necessary. Objective: The purpose of this study was to evaluate the efficacy of mHealth interventions in patients with low back pain compared to usual care. Methods: This was a systematic review and meta-analysis of randomized controlled trials designed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) statement standard. We searched for studies published in English before October 2020 in the PubMed, EMBASE, Web of Science, and Cochrane Library databases. Two researchers independently scanned the literature, extracted data, and assessed the methodological quality of the included studies. Bias risks were assessed using the Cochrane Collaboration tool. We used RevMan 5.4 software to perform the meta-analysis. Results: A total of 9 studies with 792 participants met the inclusion criteria. The simultaneous use of mHealth and usual care showed a better reduction in pain intensity than usual care alone, as measured by the numeric rating scale (mean difference [MD] --0.85, 95\% CI --1.29 to --0.40; P<.001), and larger efficacy in reducing disability, as measured by the Rolland-Morris Disability Questionnaire (MD --1.54, 95\% CI --2.35 to --0.73; P<.001). Subgroup analyses showed that compared with usual care, mHealth using telephone calls significantly reduced pain intensity (MD --1.12, 95\% CI --1.71 to --0.53; P<.001) and disability score (MD --1.68, 95\% CI --2.74 to --0.63; P<.001). However, without the use of telephone calls, mHealth had no obvious advantage over usual care in improving pain intensity (MD --0.48, 95\% CI --1.16 to 0.20; P=.16) and the disability score (MD --0.41, 95\% CI --1.88 to 1.05; P=.58). The group that received a more sensitive feedback intervention showed a significantly reduced disability score (MD --4.30, 95\% CI --6.95 to --1.69; P=.001). Conclusions: The use of simultaneous mHealth and usual care interventions has better efficacy than usual care alone in reducing pain intensity and disability in patients with low back pain. Moreover, the results of subgroup analysis revealed that mHealth using telephone calls might play a positive role in improving pain intensity and disability in patients with low back pain. ", doi="10.2196/26095", url="https://mhealth.jmir.org/2021/6/e26095", url="http://www.ncbi.nlm.nih.gov/pubmed/34114965" } @Article{info:doi/10.2196/24116, author="Lv, Meina and Wu, Tingting and Jiang, Shaojun and Chen, Wenjun and Zhang, Jinhua", title="Effects of Telemedicine and mHealth on Systolic Blood Pressure Management in Stroke Patients: Systematic Review and Meta-Analysis of Randomized Controlled Trials", journal="JMIR Mhealth Uhealth", year="2021", month="Jun", day="11", volume="9", number="6", pages="e24116", keywords="stroke", keywords="systolic blood pressure", keywords="mHealth", keywords="telemedicine", keywords="meta-analysis", keywords="self-management", abstract="Background: Stroke is a common, harmful disease with high recurrence and mortality rates. Uncontrolled blood pressure is an important and changeable risk factor for stroke recurrence. Telemedicine and mobile health (mHealth) interventions may have the potential to facilitate the control of blood pressure among stroke survivors, but their effect has not been established. Objective: This systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted to estimate the effects of telemedicine and mHealth interventions on the control of systolic blood pressure among stroke survivors. Methods: The research literature published up to June 28, 2020, and consisting of RCTs related to telemedicine and mHealth interventions was searched in PubMed, EMBASE, Web of Science, and the Cochrane Library. The Cochrane risk of bias tool (RoB 2.0) was used to evaluate the quality of the studies. The Cochran Q test and I2 statistic were used to assess heterogeneity. Data were meta-analyzed using a random-effects model. Mean difference (MD) with 95\% CI and 95\% prediction interval (PI) were calculated. Results: In total, 9 RCTs with a total sample size of 1583 stroke survivors met the inclusion criteria. Compared with the usual care, telemedicine and mHealth had a significantly greater impact on the control of systolic blood pressure (MD --5.49; 95\% CI --7.87 to --3.10; P<.001; 95\% PI --10.46 to --0.51). A subgroup analysis showed that the intervention mode of telephone plus SMS text messaging (MD --9.09; 95\% CI --12.71 to --5.46; P<.001) or only telephone (MD --4.34; 95\% CI --6.55 to --2.13; P<.001; 95\% PI --7.24 to --1.45) had a greater impact on the control of systolic blood pressure than usual care. Among the stroke survivors with an intervention interval ?1 week (MD --6.51; 95\% CI --9.36 to --3.66; P<.001; 95\% PI --12.91 to --0.10) or a baseline systolic blood pressure ?140 mm Hg (MD --6.15; 95\% CI --9.44 to --2.86; P<.001; 95\% PI --13.55 to 1.26), the control of systolic blood pressure using telemedicine and mHealth was better than that of usual care. Conclusions: In general, telemedicine and mHealth reduced the systolic blood pressure of stroke survivors by an average of 5.49 mm Hg compared with usual care. Telemedicine and mHealth are a relatively new intervention mode with potential applications for the control of systolic blood pressure among stroke survivors, especially those with hypertensive stroke. ", doi="10.2196/24116", url="https://mhealth.jmir.org/2021/6/e24116", url="http://www.ncbi.nlm.nih.gov/pubmed/34114961" } @Article{info:doi/10.2196/27102, author="Osmanlliu, Esli and Rafie, Edmond and B{\'e}dard, Sylvain and Paquette, Jesseca and Gore, Genevieve and Pomey, Marie-Pascale", title="Considerations for the Design and Implementation of COVID-19 Contact Tracing Apps: Scoping Review", journal="JMIR Mhealth Uhealth", year="2021", month="Jun", day="9", volume="9", number="6", pages="e27102", keywords="COVID-19", keywords="contact tracing", keywords="exposure notification", keywords="app", keywords="design", keywords="implementation", keywords="participatory", keywords="eHealth", keywords="surveillance", keywords="monitoring", keywords="review", abstract="Background: Given the magnitude and speed of SARS-CoV-2 transmission, achieving timely and effective manual contact tracing has been a challenging task. Early in the pandemic, contact tracing apps generated substantial enthusiasm due to their potential for automating tracing and reducing transmission rates while enabling targeted confinement strategies. However, although surveys demonstrate public interest in using such apps, their actual uptake remains limited. Their social acceptability is challenged by issues around privacy, fairness, and effectiveness, among other concerns. Objective: This study aims to examine the extent to which design and implementation considerations for contact tracing apps are detailed in the available literature, focusing on aspects related to participatory and responsible eHealth innovation, and synthesize recommendations that support the development of successful COVID-19 contact tracing apps and related eHealth technologies. Methods: Searches were performed on five databases, and articles were selected based on eligibility criteria. Papers pertaining to the design, implementation, or acceptability of contact tracing apps were included. Articles published since 2019, written in English or French, and for which the full articles were available were considered eligible for analysis. To assess the scope of the knowledge found in the current literature, we used three complementary frameworks: (1) the Holistic Framework to Improve the Uptake and Impact of eHealth Technologies, (2) the Montreal model, and (3) the Responsible Innovation in Health Assessment Tool. Results: A total of 63 articles qualified for the final analysis. Less than half of the selected articles cited the need for a participatory process (n=25, 40\%), which nonetheless was the most frequently referenced item of the Framework to Improve the Uptake and Impact of eHealth Technologies. Regarding the Montreal model, stakeholder consultation was the most frequently described level of engagement in the development of contact tracing apps (n=24, 38\%), while collaboration and partnership were cited the least (n=2, 3\%). As for the Responsible Innovation in Health framework, all the articles (n=63, 100\%) addressed population health, whereas only 2\% (n=1) covered environmental considerations. Conclusions: Most studies lacked fundamental aspects of eHealth development and implementation. Our results demonstrate that stakeholders of COVID-19 contact tracing apps lack important information to be able to critically appraise this eHealth innovation. This may have contributed to the modest uptake of contact tracing apps worldwide. We make evidence-informed recommendations regarding data management, communication, stakeholder engagement, user experience, and implementation strategies for the successful and responsible development of contact tracing apps. ", doi="10.2196/27102", url="https://mhealth.jmir.org/2021/6/e27102", url="http://www.ncbi.nlm.nih.gov/pubmed/34038376" } @Article{info:doi/10.2196/20330, author="Odukoya, Ololade Oluwakemi and Ohazurike, Chidumga and Akanbi, Maxwell and O'Dwyer, C. Linda and Isikekpei, Brenda and Kuteyi, Ewemade and Ameh, O. Idaomeh and Osadiaye, Olanlesi and Adebayo, Khadijat and Usinoma, Adewunmi and Adewole, Ajoke and Odunukwe, Nkiruka and Okuyemi, Kola and Kengne, Pascal Andre", title="mHealth Interventions for Treatment Adherence and Outcomes of Care for Cardiometabolic Disease Among Adults Living With HIV: Systematic Review", journal="JMIR Mhealth Uhealth", year="2021", month="Jun", day="9", volume="9", number="6", pages="e20330", keywords="mHealth", keywords="HIV", keywords="cardiometabolic disease", keywords="text messaging", keywords="mobile", keywords="systematic review", keywords="telephone calls", keywords="wearable devices", keywords="smartphones", keywords="desktop", keywords="web-based", keywords="mobile apps", abstract="Background: The success of antiretroviral therapy has led to an increase in life expectancy and an associated rise in the risk of cardiometabolic diseases (CMDs) among people living with HIV. Objective: Our aim was to conduct a systematic review to synthesize the existing literature on the patterns of use and effects of mobile health (mHealth) interventions for improving treatment adherence and outcomes of care for CMD among people living with HIV. Methods: A systematic search of multiple databases, including PubMed-MEDLINE, Embase, CINAHL, Scopus, Web of Science, African Journals online, ClinicalTrials.gov, and the World Health Organization Global Index Medicus of peer-reviewed articles, was conducted with no date or language restrictions. Unpublished reports on mHealth interventions for treatment adherence and outcomes of care for CMD among adults living with HIV were also included in this review. Studies were included if they had at least 1 component that used an mHealth intervention to address treatment adherence or 1 or more of the stated outcomes of care for CMD among people living with HIV. Results: Our search strategy yielded 1148 unique records. In total, 10 articles met the inclusion criteria and were included in this review. Of the 10 studies, only 4 had published results. The categories of mHealth interventions ranged from short messaging, telephone calls, and wearable devices to smartphone and desktop web-based mobile apps. Across the different categories of interventions, there were no clear patterns in terms of consistency in the use of a particular intervention, as most studies (9/10, 90\%) assessed a combination of mHealth interventions. Short messaging and telephone calls were however the most common interventions. Half of the studies (5/10, 50\%) reported on outcomes that were indirectly linked to CMD, and none of them provided reliable evidence for evaluating the effectiveness of mHealth interventions for treatment adherence and outcomes of care for CMD among people living with HIV. Conclusions: Due to the limited number of studies and the heterogeneity of interventions and outcome measures in the studies, no definitive conclusions could be drawn on the patterns of use and effects of mHealth interventions for treatment adherence and outcomes of care for CMD among people living with HIV. We therefore recommend that future trials should focus on standardized outcomes for CMD. We also suggest that future studies should consider having a longer follow-up period in order to determine the long-term effects of mHealth interventions on CMD outcomes for people living with HIV. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42018086940; https://www.crd.york.ac.uk/prospero/display\_record.php?ID=CRD42018086940 ", doi="10.2196/20330", url="https://mhealth.jmir.org/2021/6/e20330", url="http://www.ncbi.nlm.nih.gov/pubmed/34106075" } @Article{info:doi/10.2196/27753, author="O'Connell, James and Abbas, Manzar and Beecham, Sarah and Buckley, Jim and Chochlov, Muslim and Fitzgerald, Brian and Glynn, Liam and Johnson, Kevin and Laffey, John and McNicholas, Bairbre and Nuseibeh, Bashar and O'Callaghan, Michael and O'Keeffe, Ian and Razzaq, Abdul and Rekanar, Kaavya and Richardson, Ita and Simpkin, Andrew and Storni, Cristiano and Tsvyatkova, Damyanka and Walsh, Jane and Welsh, Thomas and O'Keeffe, Derek", title="Best Practice Guidance for Digital Contact Tracing Apps: A Cross-disciplinary Review of the Literature", journal="JMIR Mhealth Uhealth", year="2021", month="Jun", day="7", volume="9", number="6", pages="e27753", keywords="digital contact tracing", keywords="automated contact tracing", keywords="COVID-19", keywords="SARS-CoV-2", keywords="mHealth", keywords="mobile app", keywords="app", keywords="tracing", keywords="monitoring", keywords="surveillance", keywords="review", keywords="best practice", keywords="design", abstract="Background: Digital contact tracing apps have the potential to augment contact tracing systems and disrupt COVID-19 transmission by rapidly identifying secondary cases prior to the onset of infectiousness and linking them into a system of quarantine, testing, and health care worker case management. The international experience of digital contact tracing apps during the COVID-19 pandemic demonstrates how challenging their design and deployment are. Objective: This study aims to derive and summarize best practice guidance for the design of the ideal digital contact tracing app. Methods: A collaborative cross-disciplinary approach was used to derive best practice guidance for designing the ideal digital contact tracing app. A search of the indexed and gray literature was conducted to identify articles describing or evaluating digital contact tracing apps. MEDLINE was searched using a combination of free-text terms and Medical Subject Headings search terms. Gray literature sources searched were the World Health Organization Institutional Repository for Information Sharing, the European Centre for Disease Prevention and Control publications library, and Google, including the websites of many health protection authorities. Articles that were acceptable for inclusion in this evidence synthesis were peer-reviewed publications, cohort studies, randomized trials, modeling studies, technical reports, white papers, and media reports related to digital contact tracing. Results: Ethical, user experience, privacy and data protection, technical, clinical and societal, and evaluation considerations were identified from the literature. The ideal digital contact tracing app should be voluntary and should be equitably available and accessible. User engagement could be enhanced by small financial incentives, enabling users to tailor aspects of the app to their particular needs and integrating digital contact tracing apps into the wider public health information campaign. Adherence to the principles of good data protection and privacy by design is important to convince target populations to download and use digital contact tracing apps. Bluetooth Low Energy is recommended for a digital contact tracing app's contact event detection, but combining it with ultrasound technology may improve a digital contact tracing app's accuracy. A decentralized privacy-preserving protocol should be followed to enable digital contact tracing app users to exchange and record temporary contact numbers during contact events. The ideal digital contact tracing app should define and risk-stratify contact events according to proximity, duration of contact, and the infectiousness of the case at the time of contact. Evaluating digital contact tracing apps requires data to quantify app downloads, use among COVID-19 cases, successful contact alert generation, contact alert receivers, contact alert receivers that adhere to quarantine and testing recommendations, and the number of contact alert receivers who subsequently are tested positive for COVID-19. The outcomes of digital contact tracing apps' evaluations should be openly reported to allow for the wider public to review the evaluation of the app. Conclusions: In conclusion, key considerations and best practice guidance for the design of the ideal digital contact tracing app were derived from the literature. ", doi="10.2196/27753", url="https://mhealth.jmir.org/2021/6/e27753", url="http://www.ncbi.nlm.nih.gov/pubmed/34003764" } @Article{info:doi/10.2196/25138, author="Rodriguez-Le{\'o}n, Ciro and Villalonga, Claudia and Munoz-Torres, Manuel and Ruiz, R. Jonatan and Banos, Oresti", title="Mobile and Wearable Technology for the Monitoring of Diabetes-Related Parameters: Systematic Review", journal="JMIR Mhealth Uhealth", year="2021", month="Jun", day="3", volume="9", number="6", pages="e25138", keywords="diabetes", keywords="monitoring", keywords="passive sensing", keywords="smartphone", keywords="wearable", keywords="mobile phone", abstract="Background: Diabetes mellitus is a metabolic disorder that affects hundreds of millions of people worldwide and causes several million deaths every year. Such a dramatic scenario puts some pressure on administrations, care services, and the scientific community to seek novel solutions that may help control and deal effectively with this condition and its consequences. Objective: This study aims to review the literature on the use of modern mobile and wearable technology for monitoring parameters that condition the development or evolution of diabetes mellitus. Methods: A systematic review of articles published between January 2010 and July 2020 was performed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Manuscripts were identified through searching the databases Web of Science, Scopus, and PubMed as well as through hand searching. Manuscripts were included if they involved the measurement of diabetes-related parameters such as blood glucose level, performed physical activity, or feet condition via wearable or mobile devices. The quality of the included studies was assessed using the Newcastle-Ottawa Scale. Results: The search yielded 1981 articles. A total of 26 publications met the eligibility criteria and were included in the review. Studies predominantly used wearable devices to monitor diabetes-related parameters. The accelerometer was by far the most used sensor, followed by the glucose monitor and heart rate monitor. Most studies applied some type of processing to the collected data, mainly consisting of statistical analysis or machine learning for activity recognition, finding associations among health outcomes, and diagnosing conditions related to diabetes. Few studies have focused on type 2 diabetes, even when this is the most prevalent type and the only preventable one. None of the studies focused on common diabetes complications. Clinical trials were fairly limited or nonexistent in most of the studies, with a common lack of detail about cohorts and case selection, comparability, and outcomes. Explicit endorsement by ethics committees or review boards was missing in most studies. Privacy or security issues were seldom addressed, and even if they were addressed, they were addressed at a rather insufficient level. Conclusions: The use of mobile and wearable devices for the monitoring of diabetes-related parameters shows early promise. Its development can benefit patients with diabetes, health care professionals, and researchers. However, this field is still in its early stages. Future work must pay special attention to privacy and security issues, the use of new emerging sensor technologies, the combination of mobile and clinical data, and the development of validated clinical trials. ", doi="10.2196/25138", url="https://mhealth.jmir.org/2021/6/e25138", url="http://www.ncbi.nlm.nih.gov/pubmed/34081010" } @Article{info:doi/10.2196/23832, author="Moore, Kevin and O'Shea, Emma and Kenny, Lorna and Barton, John and Tedesco, Salvatore and Sica, Marco and Crowe, Colum and Alam{\"a}ki, Antti and Condell, Joan and Nordstr{\"o}m, Anna and Timmons, Suzanne", title="Older Adults' Experiences With Using Wearable Devices: Qualitative Systematic Review and Meta-synthesis", journal="JMIR Mhealth Uhealth", year="2021", month="Jun", day="3", volume="9", number="6", pages="e23832", keywords="wearable device", keywords="older adult", keywords="digital health", keywords="meta-synthesis", keywords="qualitative review", keywords="acceptance", keywords="adherence", keywords="mobile phone", abstract="Background: Older adults may use wearable devices for various reasons, ranging from monitoring clinically relevant health metrics or detecting falls to monitoring physical activity. Little is known about how this population engages with wearable devices, and no qualitative synthesis exists to describe their shared experiences with long-term use. Objective: This study aims to synthesize qualitative studies of user experience after a multi-day trial with a wearable device to understand user experience and the factors that contribute to the acceptance and use of wearable devices. Methods: We conducted a systematic search in CINAHL, APA PsycINFO, PubMed, and Embase (2015-2020; English) with fixed search terms relating to older adults and wearable devices. A meta-synthesis methodology was used. We extracted themes from primary studies, identified key concepts, and applied reciprocal and refutational translation techniques; findings were synthesized into third-order interpretations, and finally, a ``line-of-argument'' was developed. Our overall goal was theory development, higher-level abstraction, and generalizability for making this group of qualitative findings more accessible. Results: In total, we reviewed 20 papers; 2 evaluated fall detection devices, 1 tested an ankle-worn step counter, and the remaining 17 tested activity trackers. The duration of wearing ranged from 3 days to 24 months. The views of 349 participants (age: range 51-94 years) were synthesized. Four key concepts were identified and outlined: motivation for device use, user characteristics (openness to engage and functional ability), integration into daily life, and device features. Motivation for device use is intrinsic and extrinsic, encompassing many aspects of the user experience, and appears to be as, if not more, important than the actual device features. To overcome usability barriers, an older adult must be motivated by the useful purpose of the device. A device that serves its intended purpose adds value to the user's life. The user's needs and the support structure around the device---aspects that are often overlooked---seem to play a crucial role in long-term adoption. Our ``line-of-argument'' model describes how motivation, ease of use, and device purpose determine whether a device is perceived to add value to the user's life, which subsequently predicts whether the device will be integrated into the user's life. Conclusions: The added value of a wearable device is the resulting balance of motivators (or lack thereof), device features (and their accuracy), ease of use, device purpose, and user experience. The added value contributes to the successful integration of the device into the daily life of the user. Useful device features alone do not lead to continued use. A support structure should be placed around the user to foster motivation, encourage peer engagement, and adapt to the user's preferences. ", doi="10.2196/23832", url="https://mhealth.jmir.org/2021/6/e23832", url="http://www.ncbi.nlm.nih.gov/pubmed/34081020" } @Article{info:doi/10.2196/19536, author="Dani{\"e}ls, M. Naomi E. and Hochstenbach, J. Laura M. and van Zelst, Catherine and van Bokhoven, A. Marloes and Delespaul, G. Philippe A. E. and Beurskens, M. Anna J. H.", title="Factors That Influence the Use of Electronic Diaries in Health Care: Scoping Review", journal="JMIR Mhealth Uhealth", year="2021", month="Jun", day="1", volume="9", number="6", pages="e19536", keywords="compliance", keywords="delivery of health care", keywords="diary", keywords="ecological momentary assessment", keywords="intention", keywords="motivation", keywords="scoping review", abstract="Background: A large number of people suffer from psychosocial or physical problems. Adequate strategies to alleviate needs are scarce or lacking. Symptom variation can offer insights into personal profiles of coping and resilience (detailed functional analyses). Hence, diaries are used to report mood and behavior occurring in daily life. To reduce inaccuracies, biases, and noncompliance with paper diaries, a shift to electronic diaries has occurred. Although these diaries are increasingly used in health care, information is lacking about what determines their use. Objective: The aim of this study was to map the existing empirical knowledge and gaps concerning factors that influence the use of electronic diaries, defined as repeated recording of psychosocial or physical data lasting at least one week using a smartphone or a computer, in health care. Methods: A scoping review of the literature published between January 2000 and December 2018 was conducted using queries in PubMed and PsycInfo databases. English or Dutch publications based on empirical data about factors that influence the use of electronic diaries for psychosocial or physical purposes in health care were included. Both databases were screened, and findings were summarized using a directed content analysis organized by the Consolidated Framework for Implementation Research (CFIR). Results: Out of 3170 articles, 22 studies were selected for qualitative synthesis. Eleven themes were determined in the CFIR categories of intervention, user characteristics, and process. No information was found for the CFIR categories inner (eg, organizational resources, innovation climate) and outer (eg, external policies and incentives, pressure from competitors) settings. Reminders, attractive designs, tailored and clear data visualizations (intervention), smartphone experience, and intrinsic motivation to change behavior (user characteristics) could influence the use of electronic diaries. During the implementation process, attention should be paid to both theoretical and practical training. Conclusions: Design aspects, user characteristics, and training and instructions determine the use of electronic diaries in health care. It is remarkable that there were no empirical data about factors related to embedding electronic diaries in daily clinical practice. More research is needed to better understand influencing factors for optimal electronic diary use. ", doi="10.2196/19536", url="https://mhealth.jmir.org/2021/6/e19536", url="http://www.ncbi.nlm.nih.gov/pubmed/34061036" } @Article{info:doi/10.2196/23411, author="St Fleur, Gaelle Ruth and St George, Mijares Sara and Leite, Rafael and Kobayashi, Marissa and Agosto, Yaray and Jake-Schoffman, E. Danielle", title="Use of Fitbit Devices in Physical Activity Intervention Studies Across the Life Course: Narrative Review", journal="JMIR Mhealth Uhealth", year="2021", month="May", day="28", volume="9", number="5", pages="e23411", keywords="physical activity", keywords="Fitbit", keywords="eHealth", keywords="life course", keywords="mobile phone", abstract="Background: Commercial off-the-shelf activity trackers (eg, Fitbit) allow users to self-monitor their daily physical activity (PA), including the number of steps, type of PA, amount of sleep, and other features. Fitbits have been used as both measurement and intervention tools. However, it is not clear how they are being incorporated into PA intervention studies, and their use in specific age groups across the life course is not well understood. Objective: This narrative review aims to characterize how PA intervention studies across the life course use Fitbit devices by synthesizing and summarizing information on device selection, intended use (intervention vs measurement tool), participant wear instructions, rates of adherence to device wear, strategies used to boost adherence, and the complementary use of other PA measures. This review provides intervention scientists with a synthesis of information that may inform future trials involving Fitbit devices. Methods: We conducted a search of the Fitabase Fitbit Research Library, a database of studies published between 2012 and 2018. Of the 682 studies available on the Fitabase research library, 60 interventions met the eligibility criteria and were included in this review. A supplemental search in PubMed resulted in the inclusion of 15 additional articles published between 2019 and 2020. A total of 75 articles were reviewed, which represented interventions conducted in childhood; adolescence; and early, middle, and older adulthood. Results: There was considerable heterogeneity in the use of Fitbit within and between developmental stages. Interventions for adults typically required longer wear periods, whereas studies on children and adolescents tended to have more limited device wear periods. Most studies used developmentally appropriate behavior change techniques and device wear instructions. Regardless of the developmental stage and intended Fitbit use (ie, measurement vs intervention tool), the most common strategies used to enhance wear time included sending participants reminders through texts or emails and asking participants to log their steps or synchronize their Fitbit data daily. The rates of adherence to the wear time criteria were reported using varying metrics. Most studies supplemented the use of Fitbit with additional objective or self-reported measures for PA. Conclusions: Overall, the heterogeneity in Fitbit use across PA intervention studies reflects its relative novelty in the field of research. As the use of monitoring devices continues to expand in PA research, the lack of uniformity in study protocols and metrics of reported measures represents a major issue for comparability purposes. There is a need for increased transparency in the prospective registration of PA intervention studies. Researchers need to provide a clear rationale for the use of several PA measures and specify the source of their main PA outcome and how additional measures will be used in the context of Fitbit-based interventions. ", doi="10.2196/23411", url="https://mhealth.jmir.org/2021/5/e23411", url="http://www.ncbi.nlm.nih.gov/pubmed/34047705" } @Article{info:doi/10.2196/27165, author="Elrose, Francine and Hill, Andrew and Liu, David and Salisbury, Isaac and LeCong, Thien and Loeb, G. Robert and Sanderson, Penelope", title="The Use of Head-Worn Displays for Vital Sign Monitoring in Critical and Acute Care: Systematic Review", journal="JMIR Mhealth Uhealth", year="2021", month="May", day="11", volume="9", number="5", pages="e27165", keywords="wearable", keywords="wearable device", keywords="head-mounted display", keywords="head-worn display", keywords="clinical setting", keywords="medical setting", keywords="patient monitoring", keywords="healthcare", abstract="Background: Continuous monitoring of patient vital signs may improve patient outcomes. Head-worn displays (HWDs) can provide hands-free access to continuous vital sign information of patients in critical and acute care contexts and thus may reduce instances of unrecognized patient deterioration. Objective: The purpose of the study is to conduct a systematic review of the literature to evaluate clinical, surrogate, and process outcomes when clinicians use HWDs for continuous patient vital sign monitoring. Methods: The review was registered with PROSPERO (CRD42019119875) and followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines. A literature search was conducted for articles published between January 1995 and June 2020 using the following databases: PubMed, Embase, CINAHL, PsycINFO, and Web of Science. Overall, 2 reviewers independently screened titles and abstracts and then assessed the full text of the articles. Original research articles that evaluated the clinical, surrogate, or process outcomes of head-mounted displays for continuous vital sign monitoring in critical care or acute care contexts were included. Results: Of the 214 records obtained, 15 (7\%) articles met the predefined criteria and were included in this review. Of the 15 studies, 7 (47\%) took place in a clinical context, whereas the remainder took place in a simulation environment. In 100\% (7/7) of the studies that evaluated gaze behavior, changes were found in gaze direction with HWDs. Change detection improvements were found in 67\% (2/3) of the studies evaluating changes in the participants' ability to detect changes in vital signs. Of the 10 studies assessing the ease of use of the HWD, most participants of 7 (70\%) studies reported that the HWD was easy to use. In all 6 studies in which participants were asked if they would consider using the HWD in their practice, most participants responded positively, but they often suggested improvements on the HWD hardware or display design. Of the 7 studies conducted in clinical contexts, none reported any clinical outcomes. Conclusions: Although there is limited and sometimes conflicting evidence about the benefits of HWDs from certain surrogate and process outcomes, evidence for clinical outcomes is lacking. Recommendations are to employ user-centered design when developing HWDs, perform longitudinal studies, and seek clinical outcomes. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42019119875; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=119875 ", doi="10.2196/27165", url="https://mhealth.jmir.org/2021/5/e27165", url="http://www.ncbi.nlm.nih.gov/pubmed/33973863" } @Article{info:doi/10.2196/26161, author="Biersteker, E. Tom and Schalij, J. Martin and Treskes, W. Roderick", title="Impact of Mobile Health Devices for the Detection of Atrial Fibrillation: Systematic Review", journal="JMIR Mhealth Uhealth", year="2021", month="Apr", day="28", volume="9", number="4", pages="e26161", keywords="eHealth", keywords="mHealth", keywords="telemedicine", keywords="cardiology", keywords="atrial fibrillation", keywords="systematic review", abstract="Background: Atrial fibrillation (AF) is the most common arrhythmia, and its prevalence is increasing. Early diagnosis is important to reduce the risk of stroke. Mobile health (mHealth) devices, such as single-lead electrocardiogram (ECG) devices, have been introduced to the worldwide consumer market over the past decade. Recent studies have assessed the usability of these devices for detection of AF, but it remains unclear if the use of mHealth devices leads to a higher AF detection rate. Objective: The goal of the research was to conduct a systematic review of the diagnostic detection rate of AF by mHealth devices compared with traditional outpatient follow-up. Study participants were aged 16 years or older and had an increased risk for an arrhythmia and an indication for ECG follow-up---for instance, after catheter ablation or presentation to the emergency department with palpitations or (near) syncope. The intervention was the use of an mHealth device, defined as a novel device for the diagnosis of rhythm disturbances, either a handheld electronic device or a patch-like device worn on the patient's chest. Control was standard (traditional) outpatient care, defined as follow-up via general practitioner or regular outpatient clinic visits with a standard 12-lead ECG or Holter monitoring. The main outcome measures were the odds ratio (OR) of AF detection rates. Methods: Two reviewers screened the search results, extracted data, and performed a risk of bias assessment. A heterogeneity analysis was performed, forest plot made to summarize the results of the individual studies, and albatross plot made to allow the P values to be interpreted in the context of the study sample size. Results: A total of 3384 articles were identified after a database search, and 14 studies with a 4617 study participants were selected. All studies but one showed a higher AF detection rate in the mHealth group compared with the control group (OR 1.00-35.71), with all RCTs showing statistically significant increases of AF detection (OR 1.54-19.16). Statistical heterogeneity between studies was considerable, with a Q of 34.1 and an I2 of 61.9, and therefore it was decided to not pool the results into a meta-analysis. Conclusions: Although the results of 13 of 14 studies support the effectiveness of mHealth interventions compared with standard care, study results could not be pooled due to considerable clinical and statistical heterogeneity. However, smartphone-connectable ECG devices provide patients with the ability to document a rhythm disturbance more easily than with standard care, which may increase empowerment and engagement with regard to their illness. Clinicians must beware of overdiagnosis of AF, as it is not yet clear when an mHealth-detected episode of AF must be deemed significant. ", doi="10.2196/26161", url="https://mhealth.jmir.org/2021/4/e26161", url="http://www.ncbi.nlm.nih.gov/pubmed/33908885" } @Article{info:doi/10.2196/25377, author="Gladman, Tehmina and Tylee, Grace and Gallagher, Steve and Mair, Jonathan and Grainger, Rebecca", title="Measuring the Quality of Clinical Skills Mobile Apps for Student Learning: Systematic Search, Analysis, and Comparison of Two Measurement Scales", journal="JMIR Mhealth Uhealth", year="2021", month="Apr", day="23", volume="9", number="4", pages="e25377", keywords="mobile apps", keywords="MARS", keywords="MARuL", keywords="medical education", keywords="app review", keywords="mobile phone", abstract="Background: Mobile apps are widely used in health professions, which increases the need for simple methods to determine the quality of apps. In particular, teachers need the ability to curate high-quality mobile apps for student learning. Objective: This study aims to systematically search for and evaluate the quality of clinical skills mobile apps as learning tools. The quality of apps meeting the specified criteria was evaluated using two measures---the widely used Mobile App Rating Scale (MARS), which measures general app quality, and the Mobile App Rubric for Learning (MARuL), a recently developed instrument that measures the value of apps for student learning---to assess whether MARuL is more effective than MARS in identifying high-quality apps for learning. Methods: Two mobile app stores were systematically searched using clinical skills terms commonly found in medical education and apps meeting the criteria identified using an approach based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A total of 9 apps were identified during the screening process. The apps were rated independently by 2 reviewers using MARS and MARuL. Results: The intraclass correlation coefficients (ICCs) for the 2 raters using MARS and MARuL were the same (MARS ICC [two-way]=0.68; P<.001 and MARuL ICC [two-way]=0.68; P<.001). Of the 9 apps, Geeky Medics-OSCE revision (MARS Android=3.74; MARS iOS=3.68; MARuL Android=75; and MARuL iOS=73) and OSCE PASS: Medical Revision (MARS Android=3.79; MARS iOS=3.71; MARuL Android=69; and MARuL iOS=73) scored highly on both measures of app quality and for both Android and iOS. Both measures also showed agreement for the lowest rated app, Patient Education Institute (MARS Android=2.21; MARS iOS=2.11; MARuL Android=18; and MARuL iOS=21.5), which had the lowest scores in all categories except information (MARS) and professional (MARuL) in both operating systems. MARS and MARuL were both able to differentiate between the highest and lowest quality apps; however, MARuL was better able to differentiate apps based on teaching and learning quality. Conclusions: This systematic search and rating of clinical skills apps for learning found that the quality of apps was highly variable. However, 2 apps---Geeky Medics-OSCE revision and OSCE PASS: Medical Revision---rated highly for both versions and with both quality measures. MARS and MARuL showed similar abilities to differentiate the quality of the 9 apps. However, MARuL's incorporation of teaching and learning elements as part of a multidimensional measure of quality may make it more appropriate for use with apps focused on teaching and learning, whereas MARS's more general rating of quality may be more appropriate for health apps targeting a general health audience. Ratings of the 9 apps by both measures also highlighted the variable quality of clinical skills mobile apps for learning. ", doi="10.2196/25377", url="https://mhealth.jmir.org/2021/4/e25377", url="http://www.ncbi.nlm.nih.gov/pubmed/33890859" } @Article{info:doi/10.2196/26038, author="Alneyadi, Mahra and Drissi, Nidal and Almeqbaali, Mariam and Ouhbi, Sofia", title="Biofeedback-Based Connected Mental Health Interventions for Anxiety: Systematic Literature Review", journal="JMIR Mhealth Uhealth", year="2021", month="Apr", day="22", volume="9", number="4", pages="e26038", keywords="anxiety", keywords="biofeedback", keywords="systematic literature review", keywords="mental health", keywords="eHealth", keywords="mHealth", keywords="connected health", keywords="digital health", abstract="Background: Connected mental health, which refers to the use of technology for mental health care and technology-based therapeutic solutions, has become an established field of research. Biofeedback is one of the approaches used in connected mental health solutions, which is mainly based on the analysis of physiological indicators for the assessment and management of the psychological state. Biofeedback is recommended by many therapists and has been used for conditions including depression, insomnia, and anxiety. Anxiety is associated with several physiological symptoms, including muscle tension and breathing issues, which makes the inclusion of biofeedback useful for anxiety detection and management. Objective: The aim of this study was to identify interventions using biofeedback as a part of their process for anxiety management and investigate their perceived effectiveness. Methods: A systematic literature review of publications presenting empirically evaluated biofeedback-based interventions for anxiety was conducted. The systematic literature review was based on publications retrieved from IEEE Digital Library, PubMed, ScienceDirect, and Scopus. A preliminary selection of papers was identified, examined, and filtered to include only relevant publications. Studies in the final selection were classified and analyzed to extract the modalities of use of biofeedback in the identified interventions, the types of physiological data that were collected and analyzed and the sensors used to collect them. Processes and outcomes of the empirical evaluations were also extracted. Results: After final selection, 13 publications presenting different interventions were investigated. The interventions addressed either primarily anxiety disorders or anxiety associated with health issues such as migraine, Parkinson disease, and rheumatology. Solutions combined biofeedback with other techniques including virtual reality, music therapy, games, and relaxation practices and used different sensors including cardiovascular belts, wrist sensors, or stretch sensors to collect physiological data such as heart rate, respiration indicators, and movement information. The interventions targeted different cohorts including children, students, and patients. Overall, outcomes from the empirical evaluations yielded positive results and emphasized the effectiveness of connected mental health solutions using biofeedback for anxiety; however, certain unfavorable outcomes, such as interventions not having an effect on anxiety and patients' preferring traditional therapy, were reported in studies addressing patients with specific physical health issues. Conclusions: The use of biofeedback in connected mental health interventions for the treatment and management of anxiety allows better screening and understanding of both psychological and physiological patient information, as well as of the association between the two. The inclusion of biofeedback could improve the outcome of interventions and boost their effectiveness; however, when used with patients suffering from certain physical health issues, suitability investigations are needed. ", doi="10.2196/26038", url="https://mhealth.jmir.org/2021/4/e26038", url="http://www.ncbi.nlm.nih.gov/pubmed/33792548" } @Article{info:doi/10.2196/24743, author="Houlding, Elizabeth and Mate, V. Kedar K. and Engler, Kim and Ortiz-Paredes, David and Pomey, Marie-Pascale and Cox, Joseph and Hijal, Tarek and Lebouch{\'e}, Bertrand", title="Barriers to Use of Remote Monitoring Technologies Used to Support Patients With COVID-19: Rapid Review", journal="JMIR Mhealth Uhealth", year="2021", month="Apr", day="20", volume="9", number="4", pages="e24743", keywords="remote monitoring", keywords="technology", keywords="COVID-19, telehealth", keywords="asynchronous technology", keywords="synchronous technology", keywords="mHealth", keywords="monitoring", keywords="review", keywords="barrier", keywords="benefit", keywords="equity", abstract="Background: The COVID-19 pandemic has acted as a catalyst for the development and adoption of a broad range of remote monitoring technologies (RMTs) in health care delivery. It is important to demonstrate how these technologies were implemented during the early stages of this pandemic to identify their application and barriers to adoption, particularly among vulnerable populations. Objective: The purpose of this knowledge synthesis was to present the range of RMTs used in delivering care to patients with COVID-19 and to identify perceived benefits of and barriers to their use. The review placed a special emphasis on health equity considerations. Methods: A rapid review of published research was conducted using Embase, MEDLINE, and QxMD for records published from the inception of COVID-19 (December 2019) to July 6, 2020. Synthesis involved content analysis of reported benefits of and barriers to the use of RMTs when delivering health care to patients with COVID-19, in addition to health equity considerations. Results: Of 491 records identified, 48 publications that described 35 distinct RMTs were included in this review. RMTs included use of existing technologies (eg, videoconferencing) and development of new ones that have COVID-19--specific applications. Content analysis of perceived benefits generated 34 distinct codes describing advantages of RMTs, mapped to 10 themes overall. Further, 52 distinct codes describing barriers to use of RMTs were mapped to 18 themes. Prominent themes associated with perceived benefits included a lower burden of care (eg, for hospitals, health care practitioners; 28 records), reduced infection risk (n=33), and support for vulnerable populations (n=14). Prominent themes reflecting barriers to use of RMTs included equity-related barriers (eg, affordability of technology for users, poor internet connectivity, poor health literacy; n=16), the need for quality ``best practice'' guidelines for use of RMTs in clinical care (n=12), and the need for additional resources to develop and support new technologies (n=11). Overall, 23 of 48 records commented on equity characteristics that stratify health opportunities and outcomes, including general characteristics that vary over time (eg, age, comorbidities; n=17), place of residence (n=11), and socioeconomic status (n=7). Conclusions: Results of this rapid review highlight the breadth of RMTs being used to monitor and inform treatment of COVID-19, the potential benefits of using these technologies, and existing barriers to their use. Results can be used to prioritize further efforts in the implementation of RMTs (eg, developing ``best practice'' guidelines for use of RMTs and generating strategies to improve equitable access for marginalized populations). ", doi="10.2196/24743", url="https://mhealth.jmir.org/2021/4/e24743", url="http://www.ncbi.nlm.nih.gov/pubmed/33769943" } @Article{info:doi/10.2196/26167, author="Yang, Yun Tien and Huang, Li and Malwade, Shwetambara and Hsu, Chien-Yi and Chen, Ching Yang", title="Diagnostic Accuracy of Ambulatory Devices in Detecting Atrial Fibrillation: Systematic Review and Meta-analysis", journal="JMIR Mhealth Uhealth", year="2021", month="Apr", day="9", volume="9", number="4", pages="e26167", keywords="atrial fibrillation", keywords="ambulatory devices", keywords="electrocardiogram", keywords="photoplethysmography", keywords="diagnostic accuracy", keywords="ubiquitous health", keywords="mobile health", keywords="technology", keywords="ambulatory device", abstract="Background: Atrial fibrillation (AF) is the most common cardiac arrhythmia worldwide. Early diagnosis of AF is crucial for preventing AF-related morbidity, mortality, and economic burden, yet the detection of the disease remains challenging. The 12-lead electrocardiogram (ECG) is the gold standard for the diagnosis of AF. Because of technological advances, ambulatory devices may serve as convenient screening tools for AF. Objective: The objective of this review was to investigate the diagnostic accuracy of 2 relatively new technologies used in ambulatory devices, non-12-lead ECG and photoplethysmography (PPG), in detecting AF. We performed a meta-analysis to evaluate the diagnostic accuracy of non-12-lead ECG and PPG compared to the reference standard, 12-lead ECG. We also conducted a subgroup analysis to assess the impact of study design and participant recruitment on diagnostic accuracy. Methods: This systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. MEDLINE and EMBASE were systematically searched for articles published from January 1, 2015 to January 23, 2021. A bivariate model was used to pool estimates of sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and area under the summary receiver operating curve (SROC) as the main diagnostic measures. Study quality was evaluated using the quality assessment of diagnostic accuracy studies (QUADAS-2) tool. Results: Our search resulted in 16 studies using either non-12-lead ECG or PPG for detecting AF, comprising 3217 participants and 7623 assessments. The pooled estimates of sensitivity, specificity, PLR, NLR, and diagnostic odds ratio for the detection of AF were 89.7\% (95\% CI 83.2\%-93.9\%), 95.7\% (95\% CI 92.0\%-97.7\%), 20.64 (95\% CI 10.10-42.15), 0.11 (95\% CI 0.06-0.19), and 224.75 (95\% CI 70.10-720.56), respectively, for the automatic interpretation of non-12-lead ECG measurements and 94.7\% (95\% CI 93.3\%-95.8\%), 97.6\% (95\% CI 94.5\%-99.0\%), 35.51 (95\% CI 18.19-69.31), 0.05 (95\% CI 0.04-0.07), and 730.79 (95\% CI 309.33-1726.49), respectively, for the automatic interpretation of PPG measurements. Conclusions: Both non-12-lead ECG and PPG offered high diagnostic accuracies for AF. Detection employing automatic analysis techniques may serve as a useful preliminary screening tool before administering a gold standard test, which generally requires competent physician analyses. Subgroup analysis indicated variations of sensitivity and specificity between studies that recruited low-risk and high-risk populations, warranting future validity tests in the general population. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42020179937; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=179937 ", doi="10.2196/26167", url="https://mhealth.jmir.org/2021/4/e26167", url="http://www.ncbi.nlm.nih.gov/pubmed/33835039" } @Article{info:doi/10.2196/20738, author="Cho, Sylvia and Ensari, Ipek and Weng, Chunhua and Kahn, G. Michael and Natarajan, Karthik", title="Factors Affecting the Quality of Person-Generated Wearable Device Data and Associated Challenges: Rapid Systematic Review", journal="JMIR Mhealth Uhealth", year="2021", month="Mar", day="19", volume="9", number="3", pages="e20738", keywords="patient generated health data", keywords="data accuracy", keywords="data quality", keywords="wearable device", keywords="fitness trackers", keywords="mobile phone", abstract="Background: There is increasing interest in reusing person-generated wearable device data for research purposes, which raises concerns about data quality. However, the amount of literature on data quality challenges, specifically those for person-generated wearable device data, is sparse. Objective: This study aims to systematically review the literature on factors affecting the quality of person-generated wearable device data and their associated intrinsic data quality challenges for research. Methods: The literature was searched in the PubMed, Association for Computing Machinery, Institute of Electrical and Electronics Engineers, and Google Scholar databases by using search terms related to wearable devices and data quality. By using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, studies were reviewed to identify factors affecting the quality of wearable device data. Studies were eligible if they included content on the data quality of wearable devices, such as fitness trackers and sleep monitors. Both research-grade and consumer-grade wearable devices were included in the review. Relevant content was annotated and iteratively categorized into semantically similar factors until a consensus was reached. If any data quality challenges were mentioned in the study, those contents were extracted and categorized as well. Results: A total of 19 papers were included in this review. We identified three high-level factors that affect data quality---device- and technical-related factors, user-related factors, and data governance-related factors. Device- and technical-related factors include problems with hardware, software, and the connectivity of the device; user-related factors include device nonwear and user error; and data governance-related factors include a lack of standardization. The identified factors can potentially lead to intrinsic data quality challenges, such as incomplete, incorrect, and heterogeneous data. Although missing and incorrect data are widely known data quality challenges for wearable devices, the heterogeneity of data is another aspect of data quality that should be considered for wearable devices. Heterogeneity in wearable device data exists at three levels: heterogeneity in data generated by a single person using a single device (within-person heterogeneity); heterogeneity in data generated by multiple people who use the same brand, model, and version of a device (between-person heterogeneity); and heterogeneity in data generated from multiple people using different devices (between-person heterogeneity), which would apply especially to data collected under a bring-your-own-device policy. Conclusions: Our study identifies potential intrinsic data quality challenges that could occur when analyzing wearable device data for research and three major contributing factors for these challenges. As poor data quality can compromise the reliability and accuracy of research results, further investigation is needed on how to address the data quality challenges of wearable devices. ", doi="10.2196/20738", url="https://mhealth.jmir.org/2021/3/e20738", url="http://www.ncbi.nlm.nih.gov/pubmed/33739294" } @Article{info:doi/10.2196/21061, author="Akinosun, Samuel Adewale and Polson, Rob and Diaz - Skeete, Yohanca and De Kock, Hendrikus Johannes and Carragher, Lucia and Leslie, Stephen and Grindle, Mark and Gorely, Trish", title="Digital Technology Interventions for Risk Factor Modification in Patients With Cardiovascular Disease: Systematic Review and Meta-analysis", journal="JMIR Mhealth Uhealth", year="2021", month="Mar", day="3", volume="9", number="3", pages="e21061", keywords="digital technologies", keywords="mHealth", keywords="eHealth", keywords="risk factors", keywords="cardiovascular diseases", keywords="telehealth", keywords="cardiac rehabilitation", keywords="behavior", keywords="systematic review", keywords="meta-analysis", keywords="mobile phone", abstract="Background: Approximately 50\% of cardiovascular disease (CVD) cases are attributable to lifestyle risk factors. Despite widespread education, personal knowledge, and efficacy, many individuals fail to adequately modify these risk factors, even after a cardiovascular event. Digital technology interventions have been suggested as a viable equivalent and potential alternative to conventional cardiac rehabilitation care centers. However, little is known about the clinical effectiveness of these technologies in bringing about behavioral changes in patients with CVD at an individual level. Objective: The aim of this study is to identify and measure the effectiveness of digital technology (eg, mobile phones, the internet, software applications, wearables, etc) interventions in randomized controlled trials (RCTs) and determine which behavior change constructs are effective at achieving risk factor modification in patients with CVD. Methods: This study is a systematic review and meta-analysis of RCTs designed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) statement standard. Mixed data from studies extracted from selected research databases and filtered for RCTs only were analyzed using quantitative methods. Outcome hypothesis testing was set at 95\% CI and P=.05 for statistical significance. Results: Digital interventions were delivered using devices such as cell phones, smartphones, personal computers, and wearables coupled with technologies such as the internet, SMS, software applications, and mobile sensors. Behavioral change constructs such as cognition, follow-up, goal setting, record keeping, perceived benefit, persuasion, socialization, personalization, rewards and incentives, support, and self-management were used. The meta-analyzed effect estimates (mean difference [MD]; standard mean difference [SMD]; and risk ratio [RR]) calculated for outcomes showed benefits in total cholesterol SMD at ?0.29 [?0.44, ?0.15], P<.001; high-density lipoprotein SMD at --0.09 [--0.19, 0.00], P=.05; low-density lipoprotein SMD at ?0.18 [?0.33, ?0.04], P=.01; physical activity (PA) SMD at 0.23 [0.11, 0.36], P<.001; physical inactivity (sedentary) RR at 0.54 [0.39, 0.75], P<.001; and diet (food intake) RR at 0.79 [0.66, 0.94], P=.007. Initial effect estimates showed no significant benefit in body mass index (BMI) MD at ?0.37 [?1.20, 0.46], P=.38; diastolic blood pressure (BP) SMD at ?0.06 [?0.20, 0.08], P=.43; systolic BP SMD at ?0.03 [?0.18, 0.13], P=.74; Hemoglobin A1C blood sugar (HbA1c) RR at 1.04 [0.40, 2.70], P=.94; alcohol intake SMD at ?0.16 [?1.43, 1.10], P=.80; smoking RR at 0.87 [0.67, 1.13], P=.30; and medication adherence RR at 1.10 [1.00, 1.22], P=.06. Conclusions: Digital interventions may improve healthy behavioral factors (PA, healthy diet, and medication adherence) and are even more potent when used to treat multiple behavioral outcomes (eg, medication adherence plus). However, they did not appear to reduce unhealthy behavioral factors (smoking, alcohol intake, and unhealthy diet) and clinical outcomes (BMI, triglycerides, diastolic and systolic BP, and HbA1c). ", doi="10.2196/21061", url="https://mhealth.jmir.org/2021/3/e21061", url="http://www.ncbi.nlm.nih.gov/pubmed/33656444" } @Article{info:doi/10.2196/26360, author="Jones, Chelsea and Harasym, Jessica and Miguel-Cruz, Antonio and Chisholm, Shannon and Smith-MacDonald, Lorraine and Br{\'e}mault-Phillips, Suzette", title="Neurocognitive Assessment Tools for Military Personnel With Mild Traumatic Brain Injury: Scoping Literature Review", journal="JMIR Ment Health", year="2021", month="Feb", day="22", volume="8", number="2", pages="e26360", keywords="military", keywords="rehabilitation", keywords="head injury", keywords="posttraumatic stress disorder", keywords="cognition", keywords="neurocognitive assessment tool", keywords="traumatic brain injury", keywords="assessment", keywords="brain concussion", keywords="mobile phone", abstract="Background: Mild traumatic brain injury (mTBI) occurs at a higher frequency among military personnel than among civilians. A common symptom of mTBIs is cognitive dysfunction. Health care professionals use neuropsychological assessments as part of a multidisciplinary and best practice approach for mTBI management. Such assessments support clinical diagnosis, symptom management, rehabilitation, and return-to-duty planning. Military health care organizations currently use computerized neurocognitive assessment tools (NCATs). NCATs and more traditional neuropsychological assessments present unique challenges in both clinical and military settings. Many research gaps remain regarding psychometric properties, usability, acceptance, feasibility, effectiveness, sensitivity, and utility of both types of assessments in military environments. Objective: The aims of this study were to explore evidence regarding the use of NCATs among military personnel who have sustained mTBIs; evaluate the psychometric properties of the most commonly tested NCATs for this population; and synthesize the data to explore the range and extent of NCATs among this population, clinical recommendations for use, and knowledge gaps requiring future research. Methods: Studies were identified using MEDLINE, Embase, American Psychological Association PsycINFO, CINAHL Plus with Full Text, Psych Article, Scopus, and Military \& Government Collection. Data were analyzed using descriptive analysis, thematic analysis, and the Randolph Criteria. Narrative synthesis and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews) guided the reporting of findings. The psychometric properties of NCATs were evaluated with specific criteria and summarized. Results: Of the 104 papers, 33 met the inclusion criteria for this scoping review. Thematic analysis and NCAT psychometrics were reported and summarized. Conclusions: When considering the psychometric properties of the most commonly used NCATs in military populations, these assessments have yet to demonstrate adequate validity, reliability, sensitivity, and clinical utility among military personnel with mTBIs. Additional research is needed to further validate NCATs within military populations, especially for those living outside of the United States and individuals experiencing other conditions known to adversely affect cognitive processing. Knowledge gaps remain, warranting further study of psychometric properties and the utility of baseline and normative testing for NCATs. ", doi="10.2196/26360", url="https://mental.jmir.org/2021/2/e26360", url="http://www.ncbi.nlm.nih.gov/pubmed/33616538" } @Article{info:doi/10.2196/23912, author="Queiroz, Nunes Artur Acelino Francisco Luz and Mendes, Costa Isabel Am{\'e}lia and de Godoy, Simone and Velez Lap{\~a}o, Lu{\'i}s and Dias, S{\'o}nia", title="mHealth Strategies Related to HIV Postexposure Prophylaxis Knowledge and Access: Systematic Literature Review, Technology Prospecting of Patent Databases, and Systematic Search on App Stores", journal="JMIR Mhealth Uhealth", year="2021", month="Feb", day="16", volume="9", number="2", pages="e23912", keywords="HIV", keywords="eHealth", keywords="mHealth", keywords="postexposure prophylaxis", keywords="PEP", keywords="prevention", keywords="mobile phone", abstract="Background: Globally, the number of HIV cases continue to increase, despite the development of multiple prevention strategies. New cases of HIV have been reported disproportionately more in men who have sex with men and other vulnerable populations. Issues such as internalized and structural homophobia prevent these men from accessing prevention strategies such as postexposure prophylaxis (PEP). Mobile health (mHealth) interventions are known to be one of the newest and preferred options to enhance PEP knowledge and access. Objective: The aim of this study was to identify and analyze the mobile apps addressing PEP for HIV infections. Methods: We conducted a descriptive exploratory study in 3 sequential phases: systematic literature review, patent analysis, and systematic search of app stores. For the systematic review, we followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines adapted for an integrative review in the databases of PubMed, Web of Knowledge, Scopus, Cochrane, Embase, Science Direct, Eric, Treasure, and CINAHL. The patent analysis was performed by exploring the databases of the Brazilian National Institute of Industrial Property, the United States Patent and Trademark Office, and the European Patent Office. For the systematic search, we analyzed mHealth apps related to HIV in 2 major app libraries, that is, Google Play Store and App Store. The apps were evaluated by name, characteristics, functions, and availability in iPhone operating system/Android phones. Results: We analyzed 22 studies, of which 2 were selected for the final stage. Both studies present the use of apps as mHealth strategies aimed at improving the sexual health of men who have sex with men, and they were classified as decision support systems. The search in the patent databases showed only 1 result, which was not related to the topic since it was a drug intervention. In the app libraries, 25 apps were found and analyzed, with 15 (60\%) apps available for Android systems but only 3 (12\%) addressing PEP. In general, the apps inform about HIV and HIV prevention and treatment, with the focus users being health care providers, people with HIV, or the general population, but they have only limited features available, that is, mainly text, images, and videos. The 3 apps exclusively focusing on PEP were created by researchers from Brazilian universities. Conclusions: Our review found no connection between the scientific studies, registered patents, and the available apps related to PEP; this finding indicates that these available apps do not have a theoretical or a methodological background in their creation. Thus, since the scientific knowledge on HIV is not translated into technological products, preventing the emergence of new infections, especially in the more vulnerable groups, is difficult. In the future, researchers and the community must work in synergy to create more mHealth tools aimed at PEP. ", doi="10.2196/23912", url="http://mhealth.jmir.org/2021/2/e23912/", url="http://www.ncbi.nlm.nih.gov/pubmed/33591289" } @Article{info:doi/10.2196/24080, author="Kim, Mihui and Kim, Changhwan and Kim, Eunkyo and Choi, Mona", title="Effectiveness of Mobile Health--Based Exercise Interventions for Patients with Peripheral Artery Disease: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2021", month="Feb", day="15", volume="9", number="2", pages="e24080", keywords="peripheral artery disease", keywords="mobile health", keywords="exercise", keywords="adherence", keywords="meta-analysis", abstract="Background: Peripheral artery disease (PAD) affects over 236 million people worldwide, and exercise interventions are commonly used to alleviate symptoms of this condition. However, no previous systematic review has evaluated the effects of mobile health (mHealth)--based exercise interventions for patients with PAD. Objective: This study aimed to assess the effect of mHealth-based exercise interventions on walking performance, functional status, and quality of life in patients with PAD. Methods: A systematic review and meta-analysis were conducted. We searched in seven databases to identify randomized controlled trials of patients with PAD published in English up to December 4, 2020. Studies were included if patients participated in mHealth-based exercise interventions and were assessed for walking performance. We analyzed pooled effect size on walking performance, functional status, and quality of life based on the standardized mean differences between groups. Results: A total of seven studies were selected for the systematic review, and six studies were included in the meta-analysis. The duration of interventions in the included studies was 12 to 48 weeks. In the pooled analysis, when compared with the control groups, the mHealth-based exercise intervention groups were associated with significant improvements in pain-free walking (95\% CI 0.13-0.88), maximal walking (95\% CI 0.03-0.87), 6-minute walk test (6MWT) distance (95\% CI 0.59-1.24), and walking distance (95\% CI 0.02-0.49). However, benefits of the interventions on walking speed, stair-climbing ability, and quality of life were not observed. Conclusions: mHealth-based exercise interventions for patients with PAD were beneficial for improving pain-free walking, maximal walking, and 6MWT distance. We found that exercise interventions using mHealth are an important strategy for improving the exercise effectiveness and adherence rate of patients with PAD. Future studies should consider the use of various and suitable functions of mHealth that can increase the adherence rates and improve the effectiveness of exercise. ", doi="10.2196/24080", url="http://mhealth.jmir.org/2021/2/e24080/", url="http://www.ncbi.nlm.nih.gov/pubmed/33587042" } @Article{info:doi/10.2196/23477, author="Eberle, Claudia and L{\"o}hnert, Maxine and Stichling, Stefanie", title="Effectiveness of Disease-Specific mHealth Apps in Patients With Diabetes Mellitus: Scoping Review", journal="JMIR Mhealth Uhealth", year="2021", month="Feb", day="15", volume="9", number="2", pages="e23477", keywords="diabetes mellitus", keywords="mobile apps", keywords="mHealth apps", keywords="medical apps", abstract="Background: According to the World Health Organization, the worldwide prevalence of diabetes mellitus (DM) is increasing dramatically and DM comprises a large part of the global burden of disease. At the same time, the ongoing digitalization that is occurring in society today offers novel possibilities to deal with this challenge, such as the creation of mobile health (mHealth) apps. However, while a great variety of DM-specific mHealth apps exist, the evidence in terms of their clinical effectiveness is still limited. Objective: The objective of this review was to evaluate the clinical effectiveness of mHealth apps in DM management by analyzing health-related outcomes in patients diagnosed with type 1 DM (T1DM), type 2 DM (T2DM), and gestational DM. Methods: A scoping review was performed. A systematic literature search was conducted in MEDLINE (PubMed), Cochrane Library, EMBASE, CINAHL, and Web of Science Core Collection databases for studies published between January 2008 and October 2020. The studies were categorized by outcomes and type of DM. In addition, we carried out a meta-analysis to determine the impact of DM-specific mHealth apps on the management of glycated hemoglobin (HbA1c). Results: In total, 27 studies comprising 2887 patients were included. We analyzed 19 randomized controlled trials, 1 randomized crossover trial, 1 exploratory study, 1 observational study, and 5 pre-post design studies. Overall, there was a clear improvement in HbA1c values in patients diagnosed with T1DM and T2DM. In addition, positive tendencies toward improved self-care and self-efficacy as a result of mHealth app use were found. The meta-analysis revealed an effect size, compared with usual care, of a mean difference of --0.54\% (95\% CI --0.8 to --0.28) for T2DM and --0.63\% (95\% CI --0.93 to --0.32) for T1DM. Conclusions: DM-specific mHealth apps improved the glycemic control by significantly reducing HbA1c values in patients with T1DM and T2DM patients. In general, mHealth apps effectively enhanced DM management. However, further research in terms of clinical effectiveness needs to be done in greater detail. ", doi="10.2196/23477", url="http://mhealth.jmir.org/2021/2/e23477/", url="http://www.ncbi.nlm.nih.gov/pubmed/33587045" } @Article{info:doi/10.2196/26145, author="Oh, Soyeon Sarah and Kim, Kyoung-A and Kim, Minsu and Oh, Jaeuk and Chu, Hui Sang and Choi, JiYeon", title="Measurement of Digital Literacy Among Older Adults: Systematic Review", journal="J Med Internet Res", year="2021", month="Feb", day="3", volume="23", number="2", pages="e26145", keywords="healthy aging", keywords="eHealth", keywords="telehealth", keywords="mobile health", keywords="digital literacy", keywords="ehealth literacy", keywords="aging", keywords="elderly", keywords="older adults", keywords="review", keywords="literacy", abstract="Background: Numerous instruments are designed to measure digital literacy among the general population. However, few studies have assessed the use and appropriateness of these measurements for older populations. Objective: This systematic review aims to identify and critically appraise studies assessing digital literacy among older adults and to evaluate how digital literacy instruments used in existing studies address the elements of age-appropriate digital literacy using the European Commission's Digital Competence (DigComp) Framework. Methods: Electronic databases were searched for studies using validated instruments to assess digital literacy among older adults. The quality of all included studies was evaluated using the Crowe Critical Appraisal Tool (CCAT). Instruments were assessed according to their ability to incorporate the competence areas of digital literacy as defined by the DigComp Framework: (1) information and data literacy, (2) communication and collaboration, (3) digital content creation, (4) safety, and (5) problem-solving ability, or attitudes toward information and communication technology use. Results: Searches yielded 1561 studies, of which 27 studies (17 cross-sectional, 2 before and after, 2 randomized controlled trials, 1 longitudinal, and 1 mixed methods) were included in the final analysis. Studies were conducted in the United States (18/27), Germany (3/27), China (1/27), Italy (1/27), Sweden (1/27), Canada (1/27), Iran (1/27), and Bangladesh (1/27). Studies mostly defined older adults as aged ?50 years (10/27) or ?60 years (8/27). Overall, the eHealth Literacy Scale (eHEALS) was the most frequently used instrument measuring digital literacy among older adults (16/27, 59\%). Scores on the CCAT ranged from 34 (34/40, 85\%) to 40 (40/40, 100\%). Most instruments measured 1 or 2 of the DigComp Framework's elements, but the Mobile Device Proficiency Questionnaire (MDPQ) measured all 5 elements, including ``digital content creation'' and ``safety.'' Conclusions: The current digital literacy assessment instruments targeting older adults have both strengths and weaknesses, relative to their study design, administration method, and ease of use. Certain instrument modalities like the MDPQ are more generalizable and inclusive and thus, favorable for measuring the digital literacy of older adults. More studies focusing on the suitability of such instruments for older populations are warranted, especially for areas like ``digital content creation'' and ``safety'' that currently lack assessment. Evidence-based discussions regarding the implications of digitalization for the treatment of older adults and how health care professionals may benefit from this phenomenon are encouraged. ", doi="10.2196/26145", url="https://www.jmir.org/2021/2/e26145", url="http://www.ncbi.nlm.nih.gov/pubmed/33533727" } @Article{info:doi/10.2196/22601, author="He, Zihao and Wu, Hua and Yu, Fengyu and Fu, Jinmei and Sun, Shunli and Huang, Ting and Wang, Runze and Chen, Delong and Zhao, Guanggao and Quan, Minghui", title="Effects of Smartphone-Based Interventions on Physical Activity in Children and Adolescents: Systematic Review and Meta-analysis", journal="JMIR Mhealth Uhealth", year="2021", month="Feb", day="1", volume="9", number="2", pages="e22601", keywords="adolescents", keywords="children", keywords="mHealth", keywords="physical activity", keywords="smartphone", abstract="Background: About 70\% of children and adolescents worldwide do not meet the recommended level of physical activity (PA), which is closely associated with physical, psychological, and cognitive well-being. Nowadays, the use of technologies to change PA is of interest due to the need for novel, more effective intervention approaches. The previous meta-analyses have examined smartphone-based interventions and their impact on PA in adults, but evidence in children and adolescents still needs further research. Objective: This systematic review and meta-analysis aimed to determine the effectiveness of smartphone-based interventions for improving PA in children and adolescents. Methods: Five electronic databases (PubMed, Web of Science, OVID, Scopus, and the China National Knowledge Infrastructure) were searched up to June 29, 2020. Randomized controlled trials with a control group that examine the effect of smartphone interventions on PA among children and adolescents were included. Bias risks were assessed using the Cochrane collaboration tool. Meta-analysis was performed to assess the pooled effect on PA using a random effects model. Subgroup analyses were conducted to examine the potential modifying effects of different factors (eg, types of intervention, intervention duration, age, measurement, study quality). Results: A total of 9 studies were included in this review, including 4 mobile app interventions, 3 SMS text messaging interventions, and 2 app + SMS text messaging interventions. In general, the risk of bias of included studies was low. Compared with the control group, the use of smartphone intervention significantly improved PA (standardized mean difference [SMD] 0.44, 95\% CI 0.11-0.77, P=.009), especially for total PA (TPA; weighted mean difference [WMD] 32.35, 95\% CI 10.36-54.33, P=.004) and daily steps (WMD 1185, 95\% CI 303-2068, P=.008), but not for moderate-to-vigorous PA (WMD 3.91, 95\% CI --1.99 to 9.81, P=.19). High statistical heterogeneity was detected (I2=73.9\%, P<.001) for PA. Meta-regression showed that duration ($\beta$=--.08, 95\% CI --0.15 to --0.01, n=16) was a potential factor for high heterogeneity. The results of subgroup analyses indicated that app intervention (SMD 0.76, 95\% CI 0.23-1.30, P=.005), children (SMD 0.64, 95\% CI 0.10-1.18, P=.02), ``?8 weeks'' (SMD 0.76, 95\% CI 0.23-1.30, P=.005), objective measurement (SMD 0.50, 95\% CI 0.09-0.91, P=.02), and low risk of bias (SMD 0.96, 95\% CI 0.38-1.54, P=.001) can significantly improve PA. Conclusions: The evidence of meta-analysis shows that smartphone-based intervention may be a promising strategy to increase TPA and steps in children and adolescents. Currently, app intervention may be a more effective strategy among smartphone intervention technologies. To extend the promise of smartphone intervention, the future needs to design comparative trials among different smartphone technologies. Trial Registration: PROSPERO CRD42019148261; https://tinyurl.com/y5modsrd ", doi="10.2196/22601", url="https://mhealth.jmir.org/2021/2/e22601", url="http://www.ncbi.nlm.nih.gov/pubmed/33522980" } @Article{info:doi/10.2196/23409, author="Ni, Zhenni and Wang, Yiying and Qian, Yuxing", title="Privacy Policy Compliance of Chronic Disease Management Apps in China: Scale Development and Content Evaluation", journal="JMIR Mhealth Uhealth", year="2021", month="Jan", day="28", volume="9", number="1", pages="e23409", keywords="mHealth", keywords="noncommunicable diseases", keywords="content analysis", abstract="Background: With the development of mobile health (mHealth), chronic disease management apps have brought not only the possibility of reducing the burden of chronic diseases but also huge privacy risks to patients' health data. Objective: The purpose of the study was to analyze the extent to which chronic disease management apps in China comply with the Personal Information Security Specification (PI Specification). Methods: The compliance of 45 popular chronic disease management apps was evaluated from the perspective of the information life cycle. To conduct a fine-grained evaluation, a scale based on the PI Specification was developed. Finally, 6 level 1 indicators, 22 level 2 indicators, and 61 level 3 indicators were defined. Results: There were 33/45 apps (73\%) with a privacy policy, and the average score of these apps was 40.4 out of 100. Items of level 1 indicators with high scores included general characteristics (mean 51.9\% [SD 28.1\%]), information collection and use (mean 51.1\% [SD 36.7\%]), and information sharing and transfer (mean 50.3\% [SD 33.5\%]). Information storage and protection had the lowest compliance with PI Specification (mean 29.4\% [SD 32.4\%]). Few personal information (PI) controllers have stated how to handle security incidents, including security incident reporting (7/33, 21\%), security incident notification (10/33, 30\%), and commitment to bear corresponding legal responsibility for PI security incidents (1/33, 3\%). The performance of apps in the stage of information destruction (mean 31.8\% [SD 40.0\%]) was poor, and only 21\% (7/33) apps would notify third parties to promptly delete PI after individuals cancelled their accounts. Moreover, the scoring rate for rights of PI subjects is generally low (mean 31.2\% [SD 35.5\%]), especially for obtaining copies of PI (15\%) and responding to requests (25\%). Conclusions: Although most chronic disease management apps had a privacy policy, the total compliance rate of the policy content was low, especially in the stage of information storage and protection. Thus, the field has a long way to go with regard to compliance around personal privacy protection in China. ", doi="10.2196/23409", url="http://mhealth.jmir.org/2021/1/e23409/", url="http://www.ncbi.nlm.nih.gov/pubmed/33507159" } @Article{info:doi/10.2196/16282, author="Sporrel, Karlijn and Nibbeling, Nicky and Wang, Shihan and Ettema, Dick and Simons, Monique", title="Unraveling Mobile Health Exercise Interventions for Adults: Scoping Review on the Implementations and Designs of Persuasive Strategies", journal="JMIR Mhealth Uhealth", year="2021", month="Jan", day="18", volume="9", number="1", pages="e16282", keywords="mobile health", keywords="physical activity", keywords="goals", keywords="feedback", keywords="rewards", keywords="reminder systems", keywords="social support", keywords="adult", abstract="Background: It is unclear why some physical activity (PA) mobile health (mHealth) interventions successfully promote PA whereas others do not. One possible explanation is the variety in PA mHealth interventions---not only do interventions differ in the selection of persuasive strategies but also the design and implementation of persuasive strategies can vary. However, limited studies have examined the different designs and technical implementations of strategies or explored if they indeed influenced the effectiveness of the intervention. Objective: This scoping review sets out to explore the different technical implementations and design characteristics of common and likely most effective persuasive strategies, namely, goal setting, monitoring, reminders, rewards, sharing, and social comparison. Furthermore, this review aims to explore whether previous mHealth studies examined the influence of the different design characteristics and technical operationalizations of common persuasive strategies on the effectiveness of the intervention to persuade the user to engage in PA. Methods: An unsystematic snowball and gray literature search was performed to identify the literature that evaluated the persuasive strategies in experimental trials (eg, randomized controlled trial, pre-post test). Studies were included if they targeted adults, if they were (partly) delivered by a mobile system, if they reported PA outcomes, if they used an experimental trial, and when they specifically compared the effect of different designs or implementations of persuasive strategies. The study methods, implementations, and designs of persuasive strategies, and the study results were systematically extracted from the literature by the reviewers. Results: A total of 29 experimental trials were identified. We found a heterogeneity in how the strategies are being implemented and designed. Moreover, the findings indicated that the implementation and design of the strategy has an influence on the effectiveness of the PA intervention. For instance, the effectiveness of rewarding was shown to vary between types of rewards; rewarding goal achievement seems to be more effective than rewarding each step taken. Furthermore, studies comparing different ways of goal setting suggested that assigning a goal to users might appear to be more effective than letting the user set their own goal, similar to using adaptively tailored goals as opposed to static generic goals. This study further demonstrates that only a few studies have examined the influence of different technical implementations on PA behavior. Conclusions: The different implementations and designs of persuasive strategies in mHealth interventions should be critically considered when developing such interventions and before drawing conclusions on the effectiveness of the strategy as a whole. Future efforts are needed to examine which implementations and designs are most effective to improve the translation of theory-based persuasive strategies into practical delivery forms. ", doi="10.2196/16282", url="http://mhealth.jmir.org/2021/1/e16282/", url="http://www.ncbi.nlm.nih.gov/pubmed/33459598" } @Article{info:doi/10.2196/22478, author="Carrion, Carme and Robles, Noem{\'i} and Sola-Morales, Oriol and Aymerich, Marta and Ruiz Postigo, Antonio Jose", title="Mobile Health Strategies to Tackle Skin Neglected Tropical Diseases With Recommendations From Innovative Experiences: Systematic Review", journal="JMIR Mhealth Uhealth", year="2020", month="Dec", day="31", volume="8", number="12", pages="e22478", keywords="mHealth", keywords="mobile health", keywords="neglected tropical diseases", keywords="skin neglected tropical diseases", keywords="apps", keywords="SMS text messaging", keywords="low- and middle-income countries", abstract="Background: Neglected tropical diseases (NTDs) represent a diverse group of 20 communicable diseases that occur in tropical and subtropical areas in 149 countries, affecting over 1 billion people and costing developing economies billions of dollars every year. Within these diseases, those that present lesions on the skin surface are classified as skin NTDs (sNTDs). Mobile health interventions are currently being used worldwide to manage skin diseases and can be a good strategy in the epidemiological and clinical management of sNTDs. Objective: We aimed to analyze existing evidence about mobile health interventions to control and manage sNTDs in low- and middle-income countries (LMICs) and make recommendations for what should be considered in future interventions. Methods: A systematic review was conducted of the MEDLINE, Embase, and Scopus databases over 10 years up to April 30, 2020. All types of clinical studies were considered. Data were synthesized into evidence tables. Apps were selected through a comprehensive systematic search in the Google Play Store and Apple App Store conducted between March 20 and April 15, 2020. Results: From 133 potentially relevant publications, 13 studies met our criteria (9.8\%). These analyzed eight different interventions (three SMS text messaging interventions and five app interventions). Six of the 13 (46\%) studies were community-based cross-sectional studies intended to epidemiologically map a specific disease, mainly lymphatic filariasis, but also cutaneous leishmaniasis, leprosy, and NTDs, as well as sNTDs in general. Most of the studies were considered to have a high (5/13, 39\%) or moderate (4/13, 31\%) risk of bias. Fifteen apps were identified in the Google Play Store, of which three were also in the Apple App Store. Most of the apps (11/15, 73\%) were targeted at health care professionals, with only four targeted at patients. The apps focused on scabies (3/15, 20\%), lymphatic filariasis (3/15, 20\%), cutaneous leishmaniasis (1/15, 7\%), leprosy (1/15, 7\%), yaws and Buruli ulcer (1/15, 7\%), tropical diseases including more than one sNTDs (3/15, 20\%), and NTDs including sNTDs (2/15, 13\%). Only 1 (7\%) app focused on the clinical management of sNTDs. Conclusions: All mobile health interventions that were identified face technological, legal, final user, and organizational issues. There was a remarkable heterogeneity among studies, and the majority had methodological limitations that leave considerable room for improvement. Based on existing evidence, eight recommendations have been made for future interventions. ", doi="10.2196/22478", url="http://mhealth.jmir.org/2020/12/e22478/", url="http://www.ncbi.nlm.nih.gov/pubmed/33382382" } @Article{info:doi/10.2196/18513, author="Plaza Roncero, Alejandro and Marques, Gon{\c{c}}alo and Sainz-De-Abajo, Beatriz and Mart{\'i}n-Rodr{\'i}guez, Francisco and del Pozo Vegas, Carlos and Garcia-Zapirain, Begonya and de la Torre-D{\'i}ez, Isabel", title="Mobile Health Apps for Medical Emergencies: Systematic Review", journal="JMIR Mhealth Uhealth", year="2020", month="Dec", day="11", volume="8", number="12", pages="e18513", keywords="mobile health", keywords="mHealth", keywords="eHealth", keywords="Android", keywords="iOS", keywords="medical emergencies", keywords="mobile apps", abstract="Background: Mobile health apps are used to improve the quality of health care. These apps are changing the current scenario in health care, and their numbers are increasing. Objective: We wanted to perform an analysis of the current status of mobile health technologies and apps for medical emergencies. We aimed to synthesize the existing body of knowledge to provide relevant insights for this topic. Moreover, we wanted to identify common threads and gaps to support new challenging, interesting, and relevant research directions. Methods: We reviewed the main relevant papers and apps available in the literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was used in this review. The search criteria were adopted using systematic methods to select papers and apps. On one hand, a bibliographic review was carried out in different search databases to collect papers related to each application in the health emergency field using defined criteria. On the other hand, a review of mobile apps in two virtual storage platforms (Google Play Store and Apple App Store) was carried out. The Google Play Store and Apple App Store are related to the Android and iOS operating systems, respectively. Results: In the literature review, 28 papers in the field of medical emergency were included. These studies were collected and selected according to established criteria. Moreover, we proposed a taxonomy using six groups of applications. In total, 324 mobile apps were found, with 192 identified in the Google Play Store and 132 identified in the Apple App Store. Conclusions: We found that all apps in the Google Play Store were free, and 73 apps in the Apple App Store were paid, with the price ranging from US \$0.89 to US \$5.99. Moreover, 39\% (11/28) of the included studies were related to warning systems for emergency services and 21\% (6/28) were associated with disaster management apps. ", doi="10.2196/18513", url="http://mhealth.jmir.org/2020/12/e18513/", url="http://www.ncbi.nlm.nih.gov/pubmed/33306037" } @Article{info:doi/10.2196/18316, author="Aida, Azusa and Svensson, Thomas and Svensson, Kishi Akiko and Chung, Ung-Il and Yamauchi, Toshimasa", title="eHealth Delivery of Educational Content Using Selected Visual Methods to Improve Health Literacy on Lifestyle-Related Diseases: Literature Review", journal="JMIR Mhealth Uhealth", year="2020", month="Dec", day="9", volume="8", number="12", pages="e18316", keywords="application", keywords="educational", keywords="eHealth", keywords="health literacy", keywords="lifestyle-related disease", keywords="mHealth", keywords="review", abstract="Background: Lifestyle-related diseases, such as stroke, heart disease, and diabetes, are examples of noncommunicable diseases. Noncommunicable diseases are now the leading cause of death in the world, and their major causes are lifestyle related. The number of eHealth interventions is increasing, which is expected to improve individuals' health literacy on lifestyle-related diseases. Objective: This literature review aims to identify existing literature published in the past decade on eHealth interventions aimed at improving health literacy on lifestyle-related diseases among the general population using selected visual methods, such as educational videos, films, and movies. Methods: A systematic literature search of the PubMed database was conducted in April 2019 for papers written in English and published from April 2, 2009, through April 2, 2019. A total of 538 papers were identified and screened in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram. Finally, 23 papers were included in this review. Results: The 23 papers were characterized according to study characteristics (author and year of publication, study design and region where the study was conducted, study objective, service platform, target disease and participant age, research period, outcomes, and research method); the playback time of the educational videos, films, and movies; and the evaluation of the study's impacts on health literacy. A total of 7 studies compared results using statistical methods. Of these, 5 studies reported significant positive effects of the intervention on health literacy and health-related measures (eg, physical activity, body weight). Although most of the studies included educational content aimed at improving health literacy, only 7 studies measured health literacy. In addition, only 5 studies assessed literacy using health literacy measurement tools. Conclusions: This review found that the provision of educational content was satisfactory in most eHealth studies using selected visual methods, such as videos, films, and movies. These findings suggest that eHealth interventions influence people's health behaviors and that the need for this intervention is expected to increase. Despite the need to develop eHealth interventions, standardized measurement tools to evaluate health literacy are lacking. Further research is required to clarify acceptable health literacy measurements. ", doi="10.2196/18316", url="http://mhealth.jmir.org/2020/12/e18316/", url="http://www.ncbi.nlm.nih.gov/pubmed/33295296" } @Article{info:doi/10.2196/21576, author="Baeza-Barrag{\'a}n, Rosa Maria and Labajos Manzanares, Teresa Maria and Ruiz Vergara, Carmen and Casuso-Holgado, Jes{\'u}s Mar{\'i}a and Mart{\'i}n-Valero, Roc{\'i}o", title="The Use of Virtual Reality Technologies in the Treatment of Duchenne Muscular Dystrophy: Systematic Review", journal="JMIR Mhealth Uhealth", year="2020", month="Dec", day="8", volume="8", number="12", pages="e21576", keywords="Duchenne muscular dystrophy", keywords="virtual reality", keywords="upper limb", keywords="physical therapy", keywords="muscular dystrophy", keywords="mutation", keywords="muscle", keywords="degeneration", abstract="Background: Duchenne muscular dystrophy is a serious and progressive disease affecting one in 3500-6000 live male births. The use of new virtual reality technologies has revolutionized the world of youth rehabilitation. Objective: We performed a systematic review to study the effectiveness of the use of virtual reality systems applied in the rehabilitation of the upper limbs of individuals with Duchenne muscular dystrophy. Methods: Between June 2018 and September 2019, we carried out a series of searches in 5 scientific databases: (1) PubMed, (2) Web of Science, (3) Scopus, (4) The Cochrane Library, and (5) MEDLINE via EBSCO. Two evaluators independently conducted the searches following the PRISMA recommendations for systematic reviews for articles. Two independent evaluators collated the results. Article quality was determined using the PEDro scale. Results: A total of 7 clinical trials were included in the final review. These studies used new technologies as tools for physiotherapeutic rehabilitation of the upper limbs of patients with Duchenne muscular dystrophy. Collectively, the studies showed improvement in functionality, quality of life, and motivation with the use of virtual reality technologies in the rehabilitation of upper limbs of individuals with Duchenne muscular dystrophy. Conclusions: The treatment of neuromuscular diseases has changed in recent years, from palliative symptom management to preventive methods for capacity building. The use of virtual reality is beginning to be necessary in the treatment of progressive diseases involving movement difficulties, as it provides freedom and facilitates the improvement of results in capacity training. Given that new technologies are increasingly accessible, rehabilitation and physiotherapy programs can use these technologies more frequently, and virtual reality environments can be used to improve task performance, which is essential for people with disabilities. Ultimately, virtual reality can be a great tool for physiotherapy and can be used for Duchenne muscular dystrophy rehabilitation programs to improve patient performance during training. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42018102548; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=102548 ", doi="10.2196/21576", url="http://mhealth.jmir.org/2020/12/e21576/", url="http://www.ncbi.nlm.nih.gov/pubmed/33289679" } @Article{info:doi/10.2196/22537, author="De Miguel-Rubio, Amaranta and Rubio, Dolores M. and Alba-Rueda, Alvaro and Salazar, Alejandro and Moral-Munoz, A. Jose and Lucena-Anton, David", title="Virtual Reality Systems for Upper Limb Motor Function Recovery in Patients With Spinal Cord Injury: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2020", month="Dec", day="3", volume="8", number="12", pages="e22537", keywords="virtual reality", keywords="spinal cord injuries", keywords="neurological rehabilitation", keywords="motor function", keywords="physical therapy", abstract="Background: Patients with spinal cord injury (SCI) usually present with different motor impairments, including a deterioration of upper limb motor function (ULMF), that limit their performance of activities of daily living and reduce their quality of life. Virtual reality (VR) is being used in neurological rehabilitation for the assessment and treatment of the physical impairments of this condition. Objective: A systematic review and meta-analysis was conducted to evaluate the effectiveness of VR on ULMF in patients with SCI compared with conventional physical therapy. Methods: The search was performed from October to December 2019 in Embase, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Scopus, Medline, Physiotherapy Evidence Database (PEDro), PubMed, and Cochrane Central Register of Controlled Trials. The inclusion criteria of selected studies were as follows: (1) comprised adults with SCI, (2) included an intervention with VR, (3) compared VR intervention with conventional physical therapy, (4) reported outcomes related to ULMF, and (5) was a controlled clinical trial. The Cochrane Collaboration's tool was used to evaluate the risk of bias. The RevMan 5.3 statistical software was used to obtain the meta-analysis according to the standardized mean difference (SMD) and 95\% CIs. Results: Six articles were included in this systematic review. Four of them contributed information to the meta-analysis. A total of 105 subjects were analyzed. All of the studies used semi-immersive or nonimmersive VR systems. The statistical analysis showed nonsignificant results for the Nine-Hole Peg Test (SMD --0.93, 95\% CI --1.95 to 0.09), muscle balance test (SMD --0.27, 95\% CI --0.82 to 0.27), Motricity Index (SMD 0.16, 95\% CI ?0.37 to 0.68), Jebsen-Taylor Hand Function Test (JTHFT) subtests (writing, SMD --0.10, 95\% CI --4.01 to 3.82; simulated page turning, SMD --0.99, 95\% CI --2.01 to 0.02; simulated feeding, SMD --0.64, 95\% CI --1.61 to 0.32; stacking checkers, SMD 0.99, 95\% CI --0.02 to 2.00; picking up large light objects, SMD --0.42, 95\% CI --1.37 to 0.54; and picking up large heavy objects, SMD 0.52, 95\% CI --0.44 to 1.49), range of motion of shoulder abduction/adduction (SMD --0.23, 95\% CI --1.48 to 1.03), shoulder flexion/extension (SMD 0.56, 95\% CI --1.24 to 2.36), elbow flexion (SMD --0.36, 95\% CI --1.14 to 0.42), elbow extension (SMD --0.21, 95\% CI --0.99 to 0.57), wrist extension (SMD 1.44, 95\% CI --2.19 to 5.06), and elbow supination (SMD --0.18, 95\% CI --1.80 to 1.44). Favorable results were found for the JTHFT subtest picking up small common objects (SMD --1.33, 95\% CI --2.42 to --0.24). Conclusions: The current evidence for VR interventions to improve ULMF in patients with SCI is limited. Future studies employing immersive systems to identify the key aspects that increase the clinical impact of VR interventions are needed, as well as research to prove the benefits of the use of VR in the rehabilitation of patients with SCI in the clinical setting. ", doi="10.2196/22537", url="http://mhealth.jmir.org/2020/12/e22537/", url="http://www.ncbi.nlm.nih.gov/pubmed/33270040" } @Article{info:doi/10.2196/19237, author="Robinson, Anna and Oksuz, Umay and Slight, Robert and Slight, Sarah and Husband, Andrew", title="Digital and Mobile Technologies to Promote Physical Health Behavior Change and Provide Psychological Support for Patients Undergoing Elective Surgery: Meta-Ethnography and Systematic Review", journal="JMIR Mhealth Uhealth", year="2020", month="Dec", day="1", volume="8", number="12", pages="e19237", keywords="mobile health", keywords="mHealth", keywords="healthy lifestyle", keywords="bariatric surgery", keywords="cancer", keywords="orthopedic procedures", keywords="qualitative research", keywords="systematic review", keywords="telemedicine", keywords="mobile phone", abstract="Background: Digital technology has influenced many aspects of modern living, including health care. In the context of elective surgeries, there is a strong association between preoperative physical and psychological preparedness, and improved postoperative outcomes. Health behavior changes made in the pre- and postoperative periods can be fundamental in determining the outcomes and success of elective surgeries. Understanding the potential unmet needs of patients undergoing elective surgery is central to motivating health behavior change. Integrating digital and mobile health technologies within the elective surgical pathway could be a strategy to remotely deliver this support to patients. Objective: This meta-ethnographic systematic review explores digital interventions supporting patients undergoing elective surgery with health behavior changes, specifically physical activity, weight loss, dietary intake, and psychological support. Methods: A literature search was conducted in October 2019 across 6 electronic databases (International Prospective Register of Systematic Reviews [PROSPERO]: CRD42020157813). Qualitative studies were included if they evaluated the use of digital technologies supporting behavior change in adult patients undergoing elective surgery during the pre- or postoperative period. Study quality was assessed using the Critical Appraisal Skills Programme tool. A meta-ethnographic approach was used to synthesize existing qualitative data, using the 7 phases of meta-ethnography by Noblit and Hare. Using this approach, along with reciprocal translation, enabled the development of 4 themes from the data. Results: A total of 18 studies were included covering bariatric (n=2, 11\%), cancer (n=13, 72\%), and orthopedic (n=3, 17\%) surgeries. The 4 overarching themes appear to be key in understanding and determining the effectiveness of digital and mobile interventions to support surgical patients. To successfully motivate health behavior change, technologies should provide motivation and support, enable patient engagement, facilitate peer networking, and meet individualized patient needs. Self-regulatory features such as goal setting heightened patient motivation. The personalization of difficulty levels in virtual reality--based rehabilitation was positively received. Internet-based cognitive behavioral therapy reduced depression and distress in patients undergoing cancer surgery. Peer networking provided emotional support beyond that of patient-provider relationships, improving quality of life and care satisfaction. Patients expressed the desire for digital interventions to be individually tailored according to their physical and psychological needs, before and after surgery. Conclusions: These findings have the potential to influence the future design of patient-centered digital and mobile health technologies and demonstrate a multipurpose role for digital technologies in the elective surgical pathway by motivating health behavior change and offering psychological support. Through the synthesis of patient suggestions, we highlight areas for digital technology optimization and emphasize the importance of content tailored to suit individual patients and surgical procedures. There is a significant rationale for involving patients in the cocreation of digital health technologies to enhance engagement, better support behavior change, and improve surgical outcomes. ", doi="10.2196/19237", url="https://mhealth.jmir.org/2020/12/e19237", url="http://www.ncbi.nlm.nih.gov/pubmed/33258787" } @Article{info:doi/10.2196/18774, author="de Jong, Andrea and Donelle, Lorie and Kerr, Michael", title="Nurses' Use of Personal Smartphone Technology in the Workplace: Scoping Review", journal="JMIR Mhealth Uhealth", year="2020", month="Nov", day="26", volume="8", number="11", pages="e18774", keywords="nurses", keywords="digital health", keywords="smartphone", keywords="evidence-informed practice", abstract="Background: There has been an increase in the technological infrastructures of many health care organizations to support the practice of health care providers. However, many nurses are using their personal digital devices, such as smartphones, while at work for personal and professional purposes. Despite the proliferation of smartphone use in the health care setting, there is limited research on the clinical use of these devices by nurses. It is unclear as to what extent and for what reasons nurses are using their personal smartphones to support their practice. Objective: This review aimed to understand the current breadth of research on nurses' personal smartphone use in the workplace and to identify implications for research, practice, and education. Methods: A scoping review using Arksey and O'Malley's methodological framework was conducted, and the following databases were used in the literature search: CINAHL, PubMed, ProQuest Dissertations and Theses, Embase, MEDLINE, Nursing and Allied Health Database, Scopus, Web of Science, and Cochrane Reviews. Search terms used were Nurs* AND (personal digital technology OR smartphone OR cellphone OR mobile phone OR cellular phone). Inclusion criteria included research focused on nurses' use of their own digital technologies, reported in English, and published between January 2010 and January 2020. Exclusion criteria were if the device or app was implemented for research purposes, if it was provided by the organization, if it focused on infection control, and if it was focused on nursing students or nursing education. Results: A total of 22 out of 2606 articles met the inclusion criteria. Two main themes from the thematic analyses included personal smartphone use for patient care and implications of personal smartphone use. Nurses used their smartphones to locate information about medications, procedures, diagnoses, and laboratory tests. Downloaded apps were used by nurses to locate patient care--related information. Nurses reported improved communication among health team members and used their personal devices to communicate patient information via text messaging, calling, and picture and video functions. Nurses expressed insight into personal smartphone use and challenges related to distraction, information privacy, organizational policies, and patient perception. Conclusions: Nurses view personal smartphones as an efficient method to gather patient care information and to communicate with the health care team. This review highlights knowledge gaps regarding nurses' personal device use and information safety, patient care outcomes, and communication practices. This scoping review facilitates critical reflection on patient care practices within the digital context. We infer that nurses' use of their personal devices to communicate among the health care team may demonstrate a technological ``work-around'' meant to reconcile health system demands for cost-efficiency with efforts to provide quality patient care. The current breadth of research is focused on acute care, with little research focus in other practices settings. Research initiatives are needed to explore personal device use across the continuum of health care settings. ", doi="10.2196/18774", url="https://mhealth.jmir.org/2020/11/e18774", url="http://www.ncbi.nlm.nih.gov/pubmed/33242012" } @Article{info:doi/10.2196/19391, author="Kulakli, Atik and Shubina, Ivanna", title="Scientific Publication Patterns of Mobile Technologies and Apps for Posttraumatic Stress Disorder Treatment: Bibliometric Co-Word Analysis", journal="JMIR Mhealth Uhealth", year="2020", month="Nov", day="26", volume="8", number="11", pages="e19391", keywords="posttraumatic stress disorder (PTSD)", keywords="mobile technologies", keywords="mobile apps", keywords="treatment", keywords="text analysis", keywords="co-word analysis", keywords="bibliometric", keywords="Web of Science", abstract="Background: Mobile apps are viewed as a promising opportunity to provide support for patients who have posttraumatic stress disorder (PTSD). The development of mobile technologies and apps shows similar trends in PTSD treatment. Therefore, this emerging research field has received substantial attention. Consequently, various research settings are planned for current and further studies. Objective: The aim of this study was to explore the scientific patterns of research domains related to mobile apps and other technologies for PTSD treatment in scholarly publications, and to suggest further studies for this emerging research field. Methods: We conducted a bibliometric analysis to identify publication patterns, most important keywords, trends for topicality, and text analysis, along with construction of a word cloud for papers published in the last decade (2010 to 2019). Research questions were formulated based on the relevant literature. In particular, we concentrated on highly ranked sources. Based on the proven bibliometric approach, the data were ultimately retrieved from the Web of Science Core Collection (Clarivate Analytics). Results: A total of 64 studies were found concerning the research domains. The vast majority of the papers were written in the English language (63/64, 98\%) with the remaining article (1/64, 2\%) written in French. The articles were written by 323 authors/coauthors from 11 different countries, with the United States predominating, followed by England, Canada, Italy, the Netherlands, Australia, France, Germany, Mexico, Sweden, and Vietnam. The most common publication type was peer-reviewed journal articles (48/64, 75\%), followed by reviews (8/64, 13\%), meeting abstracts (5/64, 8\%), news items (2/64, 3\%), and a proceeding (1/64, 2\%). There was a mean of 6.4 papers published per year over the study period. There was a 100\% increase in the number of publications published from 2016 to 2019 with a mean of 13.33 papers published per year during this latter period. Conclusions: Although the number of papers on mobile technologies for PTSD was quite low in the early period, there has been an overall increase in this research domain in recent years (2016-2019). Overall, these findings indicate that mobile health tools in combination with traditional treatment for mental disorders among veterans increase the efficiency of health interventions, including reducing PTSD symptoms, improving quality of life, conducting intervention evaluation, and monitoring of improvements. Mobile apps and technologies can be used as supportive tools in managing pain, anger, stress, and sleep disturbance. These findings therefore provide a useful overview of the publication trends on research domains that can inform further studies and highlight potential gaps in this field. ", doi="10.2196/19391", url="http://mhealth.jmir.org/2020/11/e19391/", url="http://www.ncbi.nlm.nih.gov/pubmed/33242019" } @Article{info:doi/10.2196/21759, author="Xu, Hongxuan and Long, Huanyu", title="The Effect of Smartphone App--Based Interventions for Patients With Hypertension: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2020", month="Oct", day="19", volume="8", number="10", pages="e21759", keywords="hypertension", keywords="smartphone", keywords="blood pressure", keywords="mobile", keywords="lifestyle", keywords="adherence", keywords="smartphone app", keywords="medication adherence", abstract="Background: Hypertension is a major cause of cardiovascular disease, which is the leading cause of premature death. People with hypertension who do not comply with recommended treatment strategies have a higher risk of heart attacks and strokes, leading to hospitalization and consequently greater health care costs. The smartphone, which is now ubiquitous, offers a convenient tool to aid in the treatment of hypertension through the use of apps targeting lifestyle management, and such app-based interventions have shown promising results. In particular, recent evidence has shown the feasibility, acceptability, and success of digital interventions in changing the behavior of people with chronic conditions. Objective: The aim of this study was to systematically compile available evidence to determine the overall effect of smartphone apps on blood pressure control, medication adherence, and lifestyle changes for people with hypertension. Methods: This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement guidelines. Databases were searched to identify randomized controlled trials related to the influence of an app-based intervention in people with hypertension. Data extracted from the included studies were subjected to a meta-analysis to compare the effects of the smartphone app intervention to a control. Results: Eight studies with a total of 1657 participants fulfilled the inclusion criteria. Pooled analysis of 6 studies assessing systolic blood pressure showed a significant overall effect in favor of the smartphone intervention (weighted mean difference --2.28, 95\% CI --3.90-0.66). Pooled analysis of studies assessing medication adherence demonstrated a significant effect (P<.001) in favor of the intervention group (standard mean difference 0.38, 95\% CI 0.26-0.50) with low heterogeneity (I2=0\%). No difference between groups was demonstrated with respect to physical activity. Conclusions: A smartphone intervention leads to a reduction in blood pressure and an increase in medication adherence for people with hypertension. Future research should focus on the effect of behavior coaching apps on medication adherence, lifestyle change, and blood pressure reduction. ", doi="10.2196/21759", url="http://mhealth.jmir.org/2020/10/e21759/", url="http://www.ncbi.nlm.nih.gov/pubmed/33074161" } @Article{info:doi/10.2196/19459, author="Teadt, Sierra and Burns, C. Jade and Montgomery, M. Tiffany and Darbes, Lynae", title="African American Adolescents and Young Adults, New Media, and Sexual Health: Scoping Review", journal="JMIR Mhealth Uhealth", year="2020", month="Oct", day="5", volume="8", number="10", pages="e19459", keywords="African American", keywords="adolescent", keywords="young adult", keywords="technology", keywords="safe sex", keywords="sexually transmitted infections", keywords="sexual behavior", keywords="new media", keywords="social media", keywords="internet", abstract="Background: Rates of sexually transmitted infections and unintended pregnancies are disproportionately high among African American adolescents and young adults (AYA). New media platforms such as social networking sites, microblogs, online video sites, and mobile phone applications may be a promising approach in promoting safe sex and preventing sexually transmitted infections. Objective: The purpose of this scoping review was to address promising approaches in new media that may serve as valuable tools in health promotion, prevention, education, and intervention development aimed at African American AYA. Methods: An electronic search was conducted using Google Scholar, Scopus, Cumulative Index to Nursing and Allied Health (CINHAL), and PubMed online databases. Concept blocks and MeSH terminology were used to identify articles around African American youth and new media. Results: The search yielded 1169 articles, and 16 publications met the criteria. Studies from the review found themes in new media that included feasibility, changing attitudes, and improving knowledge related to sexual health behavior among youth of color. Conclusions: New media is a promising and feasible platform for improving the sexual health of African American AYA. Further research is suggested to better understand the benefits of new media as a sexual health promotion tool among this specific population. ", doi="10.2196/19459", url="https://mhealth.jmir.org/2020/10/e19459", url="http://www.ncbi.nlm.nih.gov/pubmed/33016890" } @Article{info:doi/10.2196/18694, author="Fuller, Daniel and Colwell, Emily and Low, Jonathan and Orychock, Kassia and Tobin, Ann Melissa and Simango, Bo and Buote, Richard and Van Heerden, Desiree and Luan, Hui and Cullen, Kimberley and Slade, Logan and Taylor, A. Nathan G.", title="Reliability and Validity of Commercially Available Wearable Devices for Measuring Steps, Energy Expenditure, and Heart Rate: Systematic Review", journal="JMIR Mhealth Uhealth", year="2020", month="Sep", day="8", volume="8", number="9", pages="e18694", keywords="commercial wearable devices", keywords="systematic review", keywords="heart rate", keywords="energy expenditure", keywords="step count", keywords="Fitbit", keywords="Apple Watch", keywords="Garmin", keywords="Polar", abstract="Background: Consumer-wearable activity trackers are small electronic devices that record fitness and health-related measures. Objective: The purpose of this systematic review was to examine the validity and reliability of commercial wearables in measuring step count, heart rate, and energy expenditure. Methods: We identified devices to be included in the review. Database searches were conducted in PubMed, Embase, and SPORTDiscus, and only articles published in the English language up to May 2019 were considered. Studies were excluded if they did not identify the device used and if they did not examine the validity or reliability of the device. Studies involving the general population and all special populations were included. We operationalized validity as criterion validity (as compared with other measures) and construct validity (degree to which the device is measuring what it claims). Reliability measures focused on intradevice and interdevice reliability. Results: We included 158 publications examining nine different commercial wearable device brands. Fitbit was by far the most studied brand. In laboratory-based settings, Fitbit, Apple Watch, and Samsung appeared to measure steps accurately. Heart rate measurement was more variable, with Apple Watch and Garmin being the most accurate and Fitbit tending toward underestimation. For energy expenditure, no brand was accurate. We also examined validity between devices within a specific brand. Conclusions: Commercial wearable devices are accurate for measuring steps and heart rate in laboratory-based settings, but this varies by the manufacturer and device type. Devices are constantly being upgraded and redesigned to new models, suggesting the need for more current reviews and research. ", doi="10.2196/18694", url="http://mhealth.jmir.org/2020/9/e18694/", url="http://www.ncbi.nlm.nih.gov/pubmed/32897239" } @Article{info:doi/10.2196/13179, author="Jansen, Ronelle and Reid, Marianne", title="Communication Technology Use by Caregivers of Adolescents With Mental Health Issues: Systematic Review", journal="JMIR Mhealth Uhealth", year="2020", month="Aug", day="19", volume="8", number="8", pages="e13179", keywords="caregiver", keywords="communication technology", keywords="adolescent", keywords="mental health issues", keywords="systematic review", keywords="self-efficacy, knowledge", keywords="parental skills", keywords="IMBP", abstract="Background: Caregivers of adolescents with mental health issues experience challenges that may result in the caregivers having a variety of unmet needs. There is a growing need to support these caregivers. Effective support to strengthen positive caregiving behavior in caregivers may address their challenges. Communication technologies offer novel opportunities to assist these caregivers and may contribute to strengthening caregiver behavior. However, little is known about the use of communication technologies among caregivers of adolescents with mental health issues. Objective: The study aimed to answer the question: ``What is the best evidence available to strengthen positive behavior of caregivers of adolescents with mental health issues using communication technology.'' Methods: A systematic review of articles published between January 2007 and August 2018 was conducted. Searches included articles of multiple study designs from EBSCO Host and Scopus platforms with prespecified eligibility criteria. Methodological quality was evaluated using the applicable Critical Appraisal Skills Programme and Joanna Briggs Institute assessment tools. Results: The search yielded 1746 articles. Altogether, 5 articles met the eligibility criteria and were included in the review for data synthesis. Data analysis and synthesis identified three thematic conclusions reflecting the types of communication technologies used, caregivers as the target population, and strengthening of positive behavior through determinants of the Integrated Model of Behavior Prediction. Conclusions: The review reported the usefulness of communication technology by caregivers. Caregivers also demonstrated improvement in self-efficacy, knowledge, parent-child communication, and parental skills reflecting positive behavior. Although the use of communication technology is expanding as a supportive intervention to address caregivers' needs, the evidence for usefulness among caregivers of adolescents with mental health issues is still scarce. More research and information related to preferred methods of communication delivery among caregivers of adolescents is still needed. ", doi="10.2196/13179", url="http://mhealth.jmir.org/2020/8/e13179/", url="http://www.ncbi.nlm.nih.gov/pubmed/32663143" } @Article{info:doi/10.2196/15779, author="Liu, Kaifeng and Xie, Zhenzhen and Or, Kalun Calvin", title="Effectiveness of Mobile App-Assisted Self-Care Interventions for Improving Patient Outcomes in Type 2 Diabetes and/or Hypertension: Systematic Review and Meta-Analysis of Randomized Controlled Trials", journal="JMIR Mhealth Uhealth", year="2020", month="Aug", day="4", volume="8", number="8", pages="e15779", keywords="mobile app", keywords="type 2 diabetes", keywords="hypertension", keywords="self-care", abstract="Background: Mobile app-assisted self-care interventions are emerging promising tools to support self-care of patients with chronic diseases such as type 2 diabetes and hypertension. The effectiveness of such interventions requires further exploration for more supporting evidence. Objective: A systematic review and meta-analysis of randomized controlled trials (RCTs) were conducted to examine the effectiveness of mobile app-assisted self-care interventions developed for type 2 diabetes and/or hypertension in improving patient outcomes. Methods: We followed the Cochrane Collaboration guidelines and searched MEDLINE, Cochrane Library, EMBASE, and CINAHL Plus for relevant studies published between January 2007 and January 2019. Primary outcomes included changes in hemoglobin A1c (HbA1c) levels, systolic blood pressure (SBP), and diastolic blood pressure (DBP). Changes in other clinical-, behavioral-, knowledge-, and psychosocial-related outcomes were included as secondary outcomes. Primary outcomes and objective secondary outcomes that were reported in at least two trials were meta-analyzed; otherwise, a narrative synthesis was used for data analysis. Results: A total of 27 trials were identified and analyzed. For primary outcomes, the use of mobile app-assisted self-care interventions was associated with significant reductions in HbA1c levels (standardized mean difference [SMD] ?0.44, 95\% CI ?0.59 to ?0.29; P<.001), SBP (SMD ?0.17, 95\% CI ?0.31 to ?0.03, P=.02), and DBP (SMD ?0.17, 95\% CI ?0.30 to ?0.03, P=.02). Subgroup analyses for primary outcomes showed that several intervention features were supportive of self-management, including blood glucose, blood pressure, and medication monitoring, communication with health care providers, automated feedback, personalized goal setting, reminders, education materials, and data visualization. In addition, 8 objective secondary outcomes were meta-analyzed, which showed that the interventions had significant lowering effects on fasting blood glucose levels and waist circumference. A total of 42 secondary outcomes were narratively synthesized, and mixed results were found. Conclusions: Mobile app-assisted self-care interventions can be effective tools for managing blood glucose and blood pressure, likely because their use facilitates remote management of health issues and data, provision of personalized self-care recommendations, patient--care provider communication, and decision making. More studies are required to further determine which combinations of intervention features are most effective in improving the control of the diseases. Moreover, evidence regarding the effects of these interventions on the behavioral, knowledge, and psychosocial outcomes of patients is still scarce, which warrants further examination. ", doi="10.2196/15779", url="http://mhealth.jmir.org/2020/8/e15779/", url="http://www.ncbi.nlm.nih.gov/pubmed/32459654" } @Article{info:doi/10.2196/14315, author="Tuvesson, Hanna and Eriks{\'e}n, Sara and Fagerstr{\"o}m, Cecilia", title="mHealth and Engagement Concerning Persons With Chronic Somatic Health Conditions: Integrative Literature Review", journal="JMIR Mhealth Uhealth", year="2020", month="Jul", day="24", volume="8", number="7", pages="e14315", keywords="engagement", keywords="eHealth", keywords="mHealth", keywords="somatic disease", keywords="integrative literature review", keywords="telehealth", abstract="Background: Chronic somatic health conditions are a global public health challenge. Being engaged in one's own health management for such conditions is important, and mobile health (mHealth) solutions are often suggested as key to promoting engagement. Objective: The aim of this study was to review, critically appraise, and synthesize the available research regarding engagement through mHealth for persons with chronic somatic health conditions. Methods: An integrative literature review was conducted. The PubMed, CINAHL, and Inspec databases were used for literature searches. Quality assessment was done with the guidance of Critical Appraisal Skills Programme (CASP) checklists. We used a self-designed study protocol comprising 4 engagement aspects---cognitive, behavioral and emotional, interactional, and the usage of mHealth---as part of the synthesis and analysis. Results: A total of 44 articles met the inclusion criteria and were included in the analysis. mHealth usage was the most commonly occurring engagement aspect, behavioral and emotional aspects the second, cognitive aspects the third, and interactional aspects of engagement the least common aspect in the included articles. The results showed that there is a mix of enablers and barriers to engagement in relation to the 4 engagement aspects. The perceived meaningfulness and need for the solution and its content were important to create and maintain engagement. When perceived as meaningful, suitable, and usable, mHealth can support knowledge gain and learning, facilitate emotional and behavioral aspects such as a sense of confidence, and improve interactions and communications with health care professionals. Conclusions: mHealth solutions have the potential to support health care engagement for persons with chronic somatic conditions. More research is needed to further understand how, by which means, when, and among whom mHealth could further improve engagement for this population. ", doi="10.2196/14315", url="http://mhealth.jmir.org/2020/7/e14315/", url="http://www.ncbi.nlm.nih.gov/pubmed/32706686" } @Article{info:doi/10.2196/17039, author="Islam, Mohaimenul Md and Poly, Nasrin Tahmina and Walther, Andres Bruno and (Jack) Li, Yu-Chuan", title="Use of Mobile Phone App Interventions to Promote Weight Loss: Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2020", month="Jul", day="22", volume="8", number="7", pages="e17039", keywords="mobile app", keywords="mHealth", keywords="obesity", keywords="physical activity", keywords="weight gain prevention", abstract="Background: Obesity and lack of physical activity are major health risk factors for many life-threatening diseases, such as cardiovascular diseases, type 2 diabetes, and cancer. The use of mobile app interventions to promote weight loss and boost physical activity among children and adults is fascinating owing to the demand for cutting-edge and more efficient interventions. Previously published studies have examined different types of technology-based interventions and their impact on weight loss and increase in physical activity, but evidence regarding the impact of only a mobile phone app on weight loss and increase in physical activity is still lacking. Objective: The main objective of this study was to assess the efficacy of a mobile phone app intervention for reducing body weight and increasing physical activity among children and adults. Methods: PubMed, Google Scholar, Scopus, EMBASE, and the Web of Science electronic databases were searched for studies published between January 1, 2000, and April 30, 2019, without language restrictions. Two experts independently screened all the titles and abstracts to find the most appropriate studies. To be included, studies had to be either a randomized controlled trial or a case-control study that assessed a mobile phone app intervention with body weight loss and physical activity outcomes. The Cochrane Collaboration Risk of Bias tool was used to examine the risk of publication bias. Results: A total of 12 studies involving a mobile phone app intervention were included in this meta-analysis. Compared with the control group, the use of a mobile phone app was associated with significant changes in body weight (?1.07 kg, 95\% CI ?1.92 to ?0.21, P=.01) and body mass index (?0.45 kg/m2, 95\% CI ?0.78 to ?0.12, P=.008). Moreover, a nonsignificant increase in physical activity was observed (0.17, 95\% CI ?2.21 to 2.55, P=.88). Conclusions: The findings of this study demonstrate the promising and emerging efficacy of using mobile phone app interventions for weight loss. Future studies are needed to explore the long-term efficacy of mobile app interventions in larger samples. ", doi="10.2196/17039", url="https://mhealth.jmir.org/2020/7/e17039", url="http://www.ncbi.nlm.nih.gov/pubmed/32706724" } @Article{info:doi/10.2196/18255, author="Rhodes, Alexandra and Smith, D. Andrea and Chadwick, Paul and Croker, Helen and Llewellyn, H. Clare", title="Exclusively Digital Health Interventions Targeting Diet, Physical Activity, and Weight Gain in Pregnant Women: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2020", month="Jul", day="10", volume="8", number="7", pages="e18255", keywords="gestational weight gain", keywords="digital interventions", keywords="behavior change techniques", keywords="user engagement", keywords="smartphone", keywords="mobile phone", abstract="Background: Interventions to promote a healthy diet, physical activity, and weight management during pregnancy are increasingly embracing digital technologies. Although some interventions have combined digital with interpersonal (face-to-face or telephone) delivery, others have relied exclusively on digital delivery. Exclusively digital interventions have the advantages of greater cost-effectiveness and broader reach and as such can be a valuable resource for health care providers. Objective: This systematic review aims to focus on exclusively digital interventions to determine their effectiveness, identify behavior change techniques (BCTs), and investigate user engagement. Methods: A total of 6 databases (Medical Literature Analysis and Retrieval System Online [MEDLINE], Excerpta Medica dataBASE [EMBASE], PsycINFO, Cumulated Index to Nursing and Allied Health Literature [CINAHL] Plus, Web of Science, and ProQuest) were searched for randomized controlled trials or pilot control trials of exclusively digital interventions to encourage healthy eating, physical activity, or appropriate weight gain during pregnancy. The outcome measures were gestational weight gain (GWG) and changes in physical activity and dietary behaviors. Study quality was assessed using the Cochrane Risk of Bias tool 2.0. Where possible, pooled effect sizes were calculated using a random effects meta-analysis. Results: In total, 11 studies met the inclusion criteria. The risk of bias was mostly high (n=5) or moderate (n=3). Of the 11 studies, 6 reported on GWG as the primary outcome, 4 of which also measured changes in physical activity and dietary behaviors, and 5 studies focused either on dietary behaviors only (n=2) or physical activity only (n=3). The meta-analyses showed no significant benefit of interventions on total GWG for either intention-to-treat data (?0.28 kg; 95\% CI ?1.43 to 0.87) or per-protocol data (?0.65 kg; 95\% CI ?1.98 to 0.67). Substantial heterogeneity in outcome measures of change in dietary behaviors and physical activity precluded further meta-analyses. BCT coding identified 7 BCTs that were common to all effective interventions. Effective interventions averaged over twice as many BCTs from the goals and planning, and feedback and monitoring domains as ineffective interventions. Data from the 6 studies reporting on user engagement indicated a positive association between high engagement with key BCTs and greater intervention effectiveness. Interventions using proactive messaging and feedback appeared to have higher levels of engagement. Conclusions: In contrast to interpersonal interventions, there is little evidence of the effectiveness of exclusively digital interventions to encourage a healthy diet, physical activity, or weight management during pregnancy. In this review, effective interventions used proactive messaging, such as reminders to engage in BCTs, feedback on progress, or tips, suggesting that interactivity may drive engagement and lead to greater effectiveness. Given the benefits of cost and reach of digital interventions, further research is needed to understand how to use advancing technologies to enhance user engagement and improve effectiveness. ", doi="10.2196/18255", url="https://mhealth.jmir.org/2020/7/e18255", url="http://www.ncbi.nlm.nih.gov/pubmed/32673251" } @Article{info:doi/10.2196/18072, author="Jacob, Christine and Sanchez-Vazquez, Antonio and Ivory, Chris", title="Understanding Clinicians' Adoption of Mobile Health Tools: A Qualitative Review of the Most Used Frameworks", journal="JMIR Mhealth Uhealth", year="2020", month="Jul", day="6", volume="8", number="7", pages="e18072", keywords="telemedicine", keywords="smartphone", keywords="electronic health record", keywords="workflow", keywords="workload", keywords="workplace", keywords="public health practice", keywords="technology", keywords="perception", keywords="health education", keywords="mHealth", keywords="mobile health", keywords="telehealth", keywords="eHealth", abstract="Background: Although there is a push toward encouraging mobile health (mHealth) adoption to harness its potential, there are many challenges that sometimes go beyond the technology to involve other elements such as social, cultural, and organizational factors. Objective: This review aimed to explore which frameworks are used the most, to understand clinicians' adoption of mHealth as well as to identify potential shortcomings in these frameworks. Highlighting these gaps and the main factors that were not specifically covered in the most frequently used frameworks will assist future researchers to include all relevant key factors. Methods: This review was an in-depth subanalysis of a larger systematic review that included research papers published between 2008 and 2018 and focused on the social, organizational, and technical factors impacting clinicians' adoption of mHealth. The initial systematic review included 171 studies, of which 50 studies used a theoretical framework. These 50 studies are the subject of this qualitative review, reflecting further on the frameworks used and how these can help future researchers design studies that investigate the topic of mHealth adoption more robustly. Results: The most commonly used frameworks were different forms of extensions of the Technology Acceptance Model (TAM; 17/50, 34\%), the diffusion of innovation theory (DOI; 8/50, 16\%), and different forms of extensions of the unified theory of acceptance and use of technology (6/50, 12\%). Some studies used a combination of the TAM and DOI frameworks (3/50, 6\%), whereas others used the consolidated framework for implementation research (3/50, 6\%) and sociotechnical systems (STS) theory (2/50, 4\%). The factors cited by more than 20\% of the studies were usefulness, output quality, ease of use, technical support, data privacy, self-efficacy, attitude, organizational inner setting, training, leadership engagement, workload, and workflow fit. Most factors could be linked to one framework or another, but there was no single framework that could adequately cover all relevant and specific factors without some expansion. Conclusions: Health care technologies are generally more complex than tools that address individual user needs as they usually support patients with comorbidities who are typically treated by multidisciplinary teams who might even work in different health care organizations. This special nature of how the health care sector operates and its highly regulated nature, the usual budget deficits, and the interdependence between health care organizations necessitate some crucial expansions to existing theoretical frameworks usually used when studying adoption. We propose a shift toward theoretical frameworks that take into account implementation challenges that factor in the complexity of the sociotechnical structure of health care organizations and the interplay between the technical, social, and organizational aspects. Our consolidated framework offers recommendations on which factors to include when investigating clinicians' adoption of mHealth, taking into account all three aspects. ", doi="10.2196/18072", url="https://mhealth.jmir.org/2020/7/e18072", url="http://www.ncbi.nlm.nih.gov/pubmed/32442132" } @Article{info:doi/10.2196/16695, author="Indraratna, Praveen and Tardo, Daniel and Yu, Jennifer and Delbaere, Kim and Brodie, Matthew and Lovell, Nigel and Ooi, Sze-Yuan", title="Mobile Phone Technologies in the Management of Ischemic Heart Disease, Heart Failure, and Hypertension: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2020", month="Jul", day="6", volume="8", number="7", pages="e16695", keywords="mobile phone", keywords="text messaging", keywords="telemedicine", keywords="myocardial ischemia", keywords="heart failure", keywords="hypertension", abstract="Background: Cardiovascular disease (CVD) remains the leading cause of death worldwide. Mobile phones have become ubiquitous in most developed societies. Smartphone apps, telemonitoring, and clinician-driven SMS allow for novel opportunities and methods in managing chronic CVD, such as ischemic heart disease, heart failure, and hypertension, and in the conduct and support of cardiac rehabilitation. Objective: A systematic review was conducted using seven electronic databases, identifying all relevant randomized control trials (RCTs) featuring a mobile phone intervention (MPI) used in the management of chronic CVD. Outcomes assessed included mortality, hospitalizations, blood pressure (BP), and BMI. Methods: Electronic data searches were performed using seven databases from January 2000 to June 2019. Relevant articles were reviewed and analyzed. Meta-analysis was performed using standard techniques. The odds ratio (OR) was used as a summary statistic for dichotomous variables. A random effect model was used. Results: A total of 26 RCTs including 6713 patients were identified and are described in this review, and 12 RCTs were included in the meta-analysis. In patients with heart failure, MPIs were associated with a significantly lower rate of hospitalizations (244/792, 30.8\% vs 287/803, 35.7\%; n=1595; OR 0.77, 95\% CI 0.62 to 0.97; P=.03; I2=0\%). In patients with hypertension, patients exposed to MPIs had a significantly lower systolic BP (mean difference 4.3 mm Hg; 95\% CI ?7.8 to ?0.78 mm Hg; n=2023; P=.02). Conclusions: The available data suggest that MPIs may have a role as a valuable adjunct in the management of chronic CVD. ", doi="10.2196/16695", url="https://mhealth.jmir.org/2020/7/e16695", url="http://www.ncbi.nlm.nih.gov/pubmed/32628615" } @Article{info:doi/10.2196/18868, author="Benjumea, Jaime and Ropero, Jorge and Rivera-Romero, Octavio and Dorronzoro-Zubiete, Enrique and Carrasco, Alejandro", title="Privacy Assessment in Mobile Health Apps: Scoping Review", journal="JMIR Mhealth Uhealth", year="2020", month="Jul", day="2", volume="8", number="7", pages="e18868", keywords="privacy", keywords="mHealth", keywords="apps", keywords="privacy assessment", keywords="data privacy", keywords="review", keywords="security", keywords="mobile phone", abstract="Background: Privacy has always been a concern, especially in the health domain. The proliferation of mobile health (mHealth) apps has led to a large amount of sensitive data being generated. Some authors have performed privacy assessments of mHealth apps. They have evaluated diverse privacy components; however, different authors have used different criteria for their assessments. Objective: This scoping review aims to understand how privacy is assessed for mHealth apps, focusing on the components, scales, criteria, and scoring methods used. A simple taxonomy to categorize the privacy assessments of mHealth apps based on component evaluation is also proposed. Methods: We followed the methodology defined by Arksey and O'Malley to conduct a scoping review. Included studies were categorized based on the privacy component, which was assessed using the proposed taxonomy. Results: The database searches retrieved a total of 710 citations---24 of them met the defined selection criteria, and data were extracted from them. Even though the inclusion criteria considered articles published since 2009, all the studies that were ultimately included were published from 2014 onward. Although 12 papers out of 24 (50\%) analyzed only privacy, 8 (33\%) analyzed both privacy and security. Moreover, 4 papers (17\%) analyzed full apps, with privacy being just part of the assessment. The evaluation criteria used by authors were heterogeneous and were based on their experience, the literature, and/or existing legal frameworks. Regarding the set of items used for the assessments, each article defined a different one. Items included app permissions, analysis of the destination, analysis of the content of communications, study of the privacy policy, use of remote storage, and existence of a password to access the app, among many others. Most of the included studies provided a scoring method that enables the comparison of privacy among apps. Conclusions: The privacy assessment of mHealth apps is a complex task, as the criteria used by different authors for their evaluations are very heterogeneous. Although some studies about privacy assessment have been conducted, a very large set of items to evaluate privacy has been used up until now. In-app information and privacy policies are primarily utilized by the scientific community to extract privacy information from mHealth apps. The creation of a scale based on more objective criteria is a desirable step forward for privacy assessment in the future. ", doi="10.2196/18868", url="https://mhealth.jmir.org/2020/7/e18868", url="http://www.ncbi.nlm.nih.gov/pubmed/32459640" } @Article{info:doi/10.2196/15942, author="Lo, Brian and Shi, Jenny and Hollenberg, Elisa and Abi-Jaoud{\'e}, Alexxa and Johnson, Andrew and Wiljer, David", title="Surveying the Role of Analytics in Evaluating Digital Mental Health Interventions for Transition-Aged Youth: Scoping Review", journal="JMIR Ment Health", year="2020", month="Jun", day="25", volume="7", number="6", pages="e15942", keywords="user engagement", keywords="mobile apps", keywords="mHealth", keywords="telemedicine", keywords="mental health", keywords="adolescent", keywords="data analytics", abstract="Background: Consumer-facing digital health interventions provide a promising avenue to bridge gaps in mental health care delivery. To evaluate these interventions, understanding how the target population uses a solution is critical to the overall validity and reliability of the evaluation. As a result, usage data (analytics) can provide a proxy for evaluating the engagement of a solution. However, there is paucity of guidance on how usage data or analytics should be used to assess and evaluate digital mental health interventions. Objective: This review aimed to examine how usage data are collected and analyzed in evaluations of mental health mobile apps for transition-aged youth (15-29 years). Methods: A scoping review was conducted using the Arksey and O'Malley framework. A systematic search was conducted on 5 journal databases using keywords related to usage and engagement, mental health apps, and evaluation. A total of 1784 papers from 2008 to 2019 were identified and screened to ensure that they included analytics and evaluated a mental health app for transition-aged youth. After full-text screening, 49 papers were included in the analysis. Results: Of the 49 papers included in the analysis, 40 unique digital mental health innovations were evaluated, and about 80\% (39/49) of the papers were published over the past 6 years. About 80\% involved a randomized controlled trial and evaluated apps with information delivery features. There were heterogeneous findings in the concept that analytics was ascribed to, with the top 3 being engagement, adherence, and acceptability. There was also a significant spread in the number of metrics collected by each study, with 35\% (17/49) of the papers collecting only 1 metric and 29\% (14/49) collecting 4 or more analytic metrics. The number of modules completed, the session duration, and the number of log ins were the most common usage metrics collected. Conclusions: This review of current literature identified significant variability and heterogeneity in using analytics to evaluate digital mental health interventions for transition-aged youth. The large proportion of publications from the last 6 years suggests that user analytics is increasingly being integrated into the evaluation of these apps. Numerous gaps related to selecting appropriate and relevant metrics and defining successful or high levels of engagement have been identified for future exploration. Although long-term use or adoption is an important precursor to realizing the expected benefits of an app, few studies have examined this issue. Researchers would benefit from clarification and guidance on how to measure and analyze app usage in terms of evaluating digital mental health interventions for transition-aged youth. Given the established role of adoption in the success of health information technologies, understanding how to abstract and analyze user adoption for consumer digital mental health apps is also an emerging priority. ", doi="10.2196/15942", url="https://mental.jmir.org/2020/6/e15942", url="http://www.ncbi.nlm.nih.gov/pubmed/32348261" } @Article{info:doi/10.2196/16214, author="Tully, Louise and Burls, Amanda and Sorensen, Jan and El-Moslemany, Riyad and O'Malley, Grace", title="Mobile Health for Pediatric Weight Management: Systematic Scoping Review", journal="JMIR Mhealth Uhealth", year="2020", month="Jun", day="3", volume="8", number="6", pages="e16214", keywords="childhood obesity", keywords="behavior change", keywords="weight management", keywords="mHealth", keywords="eHealth", keywords="connected health", keywords="lifestyle medicine", keywords="digital health", abstract="Background: The prevalence and consequences of obesity among children and adolescents remain a leading global public health concern, and evidence-based, multidisciplinary lifestyle interventions are the cornerstone of treatment. Mobile electronic devices are widely used across socioeconomic categories and may provide a means of extending the reach and efficiency of health care interventions. Objective: We aimed to synthesize the evidence regarding mobile health (mHealth) for the treatment of childhood overweight and obesity to map the breadth and nature of the literature in this field and describe the characteristics of published studies. Methods: We conducted a systematic scoping review in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews, by searching nine academic databases in addition to gray literature for studies describing acceptability, usability, feasibility, effectiveness, adherence, or cost-effectiveness of interventions assessing mHealth for childhood obesity treatment. We also hand searched the reference lists of relevant articles. Studies aimed at the prevention of overweight or obesity were excluded, as were studies in which mHealth was not the primary mode of treatment delivery for at least one study arm or was not independently assessed. A random portion of all abstracts and full texts was double screened by a second reviewer to ensure consistency. Data were charted according to study characteristics, including design, participants, intervention content, behavior change theory (BCT) underpinning the study, mode of delivery, and outcomes measured. Results: We identified 42 eligible studies assessing acceptability (n=7), usability (n=2), feasibility or pilot studies (n=15), treatment effect (n=17), and fidelity (n=1). Change in BMI z-scores or percentiles was most commonly measured, among a variety of dietary, physical activity, psychological, and usability or acceptability measures. SMS, mobile apps, and wearable devices made up the majority of mobile interventions, and 69\% (29/42) of the studies specified a BCT used. Conclusions: Pediatric weight management using mHealth is an emerging field, with most work to date aimed at developing and piloting such interventions. Few large trials are published, and these are heterogeneous in nature and rarely reported according to the Consolidated Standards of Reporting Trials for eHealth guidelines. There is an evidence gap in the cost-effectiveness analyses of such studies. ", doi="10.2196/16214", url="https://mhealth.jmir.org/2020/6/e16214", url="http://www.ncbi.nlm.nih.gov/pubmed/32490849" } @Article{info:doi/10.2196/15111, author="Hussain, Tasmeen and Smith, Patricia and Yee, M. Lynn", title="Mobile Phone--Based Behavioral Interventions in Pregnancy to Promote Maternal and Fetal Health in High-Income Countries: Systematic Review", journal="JMIR Mhealth Uhealth", year="2020", month="May", day="28", volume="8", number="5", pages="e15111", keywords="mHealth", keywords="mobile health", keywords="pregnancy", keywords="smartphone", keywords="text messaging", keywords="mobile applications", keywords="software", keywords="chronic disease", keywords="health behavior", abstract="Background: Chronic diseases have recently had an increasing effect on maternal-fetal health, especially in high-income countries. However, there remains a lack of discussion regarding health management with technological approaches, including mobile health (mHealth) interventions. Objective: This study aimed to systematically evaluate mHealth interventions used in pregnancy in high-income countries and their effects on maternal health behaviors and maternal-fetal health outcomes. Methods: This systematic review identified studies published between January 1, 2000, and November 30, 2018, in MEDLINE via PubMed, Cochrane Library, EMBASE, CINAHL, PsycINFO, Web of Science, and gray literature. Studies were eligible for inclusion if they included only pregnant women in high-income countries and evaluated stand-alone mobile phone interventions intended to promote healthy maternal beliefs, behaviors, and/or maternal-fetal health outcomes. Two researchers independently reviewed and categorized aspects of full-text articles, including source, study design, intervention and control, duration, participant age, attrition rate, main outcomes, and risk of bias. Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed, and the study was registered in PROSPERO before initiation. Results: Of the 2225 records examined, 28 studies were included and categorized into 4 themes: (1) gestational weight gain, obesity and physical activity (n=9); (2) smoking cessation (n=9); (3) influenza vaccination (n=2); and (4) general prenatal health, preventive strategies, and miscellaneous topics (n=8). Reported sample sizes ranged from 16 to 5243 with a median of 91. Most studies were performed in the United States (18/28, 64\%) and were randomized controlled trials (21/28, 75\%). All participants in the included studies were pregnant at the time of study initiation. Overall, 14\% (4/28) of studies showed association between intervention use and improved health outcomes; all 4 studies focused on healthy gestational weight. Among those, 3 studies showed intervention use was associated with less overall gestational weight gain. These 3 studies involved interventions with text messaging or an app in combination with another communication strategy (Facebook or email). Regarding smoking cessation, influenza vaccination, and miscellaneous topics, there was some evidence of positive effects on health behaviors and beliefs, but very limited correlation with improved health outcomes. Data and interventions were heterogeneous, precluding a meta-analysis. Conclusions: In high-income countries, utilization of mobile phone--based health behavior interventions in pregnancy demonstrates some correlation with positive beliefs, behaviors, and health outcomes. More effective interventions are multimodal in terms of features and tend to focus on healthy gestational weight gain. ", doi="10.2196/15111", url="https://mhealth.jmir.org/2020/5/e15111", url="http://www.ncbi.nlm.nih.gov/pubmed/32463373" } @Article{info:doi/10.2196/18092, author="Khundaqji, Hamzeh and Hing, Wayne and Furness, James and Climstein, Mike", title="Smart Shirts for Monitoring Physiological Parameters: Scoping Review", journal="JMIR Mhealth Uhealth", year="2020", month="May", day="27", volume="8", number="5", pages="e18092", keywords="wearable electronic devices", keywords="biomedical technology", keywords="telemedicine", keywords="fitness trackers", keywords="sports", keywords="exercise", keywords="physiology", keywords="clinical decision making", keywords="vital signs", abstract="Background: The recent trends of technological innovation and widescale digitization as potential solutions to challenges in health care, sports, and emergency service operations have led to the conception of smart textile technology. In health care, these smart textile systems present the potential to aid preventative medicine and early diagnosis through continuous, noninvasive tracking of physical and mental health while promoting proactive involvement of patients in their medical management. In areas such as sports and emergency response, the potential to provide comprehensive and simultaneous physiological insights across multiple body systems is promising. However, it is currently unclear what type of evidence exists surrounding the use of smart textiles for the monitoring of physiological outcome measures across different settings. Objective: This scoping review aimed to systematically survey the existing body of scientific literature surrounding smart textiles in their most prevalent form, the smart shirt, for monitoring physiological outcome measures. Methods: A total of 5 electronic bibliographic databases were systematically searched (Ovid Medical Literature Analysis and Retrieval System Online, Excerpta Medica database, Scopus, Cumulative Index to Nursing and Allied Health Literature, and SPORTDiscus). Publications from the inception of the database to June 24, 2019 were reviewed. Nonindexed literature relevant to this review was also systematically searched. The results were then collated, summarized, and reported. Results: Following the removal of duplicates, 7871 citations were identified. On the basis of title and abstract screening, 7632 citations were excluded, whereas 239 were retrieved and assessed for eligibility. Of these, 101 citations were included in the final analysis. Included studies were categorized into four themes: (1) prototype design, (2) validation, (3) observational, and (4) reviews. Among the 101 analyzed studies, prototype design was the most prevalent theme (50/101, 49.5\%), followed by validation (29/101, 28.7\%), observational studies (21/101, 20.8\%), and reviews (1/101, 0.1\%). Presented prototype designs ranged from those capable of monitoring one physiological metric to those capable of monitoring several simultaneously. In 29 validation studies, 16 distinct smart shirts were validated against reference technology under various conditions and work rates, including rest, submaximal exercise, and maximal exercise. The identified observational studies used smart shirts in clinical, healthy, and occupational populations for aims such as early diagnosis and stress detection. One scoping review was identified, investigating the use of smart shirts for electrocardiograph signal monitoring in cardiac patients. Conclusions: Although smart shirts have been found to be valid and reliable in the monitoring of specific physiological metrics, results were variable for others, demonstrating the need for further systematic validation. Analysis of the results has also demonstrated gaps in knowledge, such as a considerable lag of validation and observational studies in comparison with prototype design and limited investigation using smart shirts in pediatric, elite sports, and emergency service populations. ", doi="10.2196/18092", url="http://mhealth.jmir.org/2020/5/e18092/", url="http://www.ncbi.nlm.nih.gov/pubmed/32348279" } @Article{info:doi/10.2196/15400, author="Wang, Youfa and Min, Jungwon and Khuri, Jacob and Xue, Hong and Xie, Bo and A Kaminsky, Leonard and J Cheskin, Lawrence", title="Effectiveness of Mobile Health Interventions on Diabetes and Obesity Treatment and Management: Systematic Review of Systematic Reviews", journal="JMIR Mhealth Uhealth", year="2020", month="Apr", day="28", volume="8", number="4", pages="e15400", keywords="diabetes mellitus", keywords="obesity", keywords="overweight", keywords="mHealth", keywords="mobile app", keywords="telemedicine", abstract="Background: Diabetes and obesity have become epidemics and costly chronic diseases. The impact of mobile health (mHealth) interventions on diabetes and obesity management is promising; however, studies showed varied results in the efficacy of mHealth interventions. Objective: This review aimed to evaluate the effectiveness of mHealth interventions for diabetes and obesity treatment and management on the basis of evidence reported in reviews and meta-analyses and to provide recommendations for future interventions and research. Methods: We systematically searched the PubMed, IEEE Xplore Digital Library, and Cochrane databases for systematic reviews published between January 1, 2005, and October 1, 2019. We analyzed 17 reviews, which assessed 55,604 original intervention studies, that met the inclusion criteria. Of those, 6 reviews were included in our meta-analysis. Results: The reviews primarily focused on the use of mobile apps and text messaging and the self-monitoring and management function of mHealth programs in patients with diabetes and obesity. All reviews examined changes in biomarkers, and some reviews assessed treatment adherence (n=7) and health behaviors (n=9). Although the effectiveness of mHealth interventions varied widely by study, all reviews concluded that mHealth was a feasible option and had the potential for improving patient health when compared with standard care, especially for glycemic control (?0.3\% to ?0.5\% greater reduction in hemoglobin A1c) and weight reduction (?1.0 kg to ?2.4 kg body weight). Overall, the existing 6 meta-analysis studies showed pooled favorable effects of these mHealth interventions (?0.79, 95\% CI ?1.17 to ?0.42; I2=90.5). Conclusions: mHealth interventions are promising, but there is limited evidence about their effectiveness in glycemic control and weight reduction. Future research to develop evidence-based mHealth strategies should use valid measures and rigorous study designs. To enhance the effectiveness of mHealth interventions, future studies are warranted for the optimal formats and the frequency of contacting patients, better tailoring of messages, and enhancing usability, which places a greater emphasis on maintaining effectiveness over time. ", doi="10.2196/15400", url="http://mhealth.jmir.org/2020/4/e15400/", url="http://www.ncbi.nlm.nih.gov/pubmed/32343253" } @Article{info:doi/10.2196/16085, author="Baker, Jess and Kohlhoff, Jane and Onobrakpor, Se-Inyenede and Woolfenden, Sue and Smith, Rebecca and Knebel, Constanze and Eapen, Valsamma", title="The Acceptability and Effectiveness of Web-Based Developmental Surveillance Programs: Rapid Review", journal="JMIR Mhealth Uhealth", year="2020", month="Apr", day="23", volume="8", number="4", pages="e16085", keywords="public health surveillance", keywords="mass screening", keywords="developmental disabilities", keywords="neurodevelopmental disorders", keywords="review literature as topic", keywords="health care disparities", abstract="Background: Web-based developmental surveillance programs may be an innovative solution to improving the early detection of childhood developmental difficulties, especially within disadvantaged populations. Objective: This review aimed to identify the acceptability and effectiveness of web-based developmental surveillance programs for children aged 0 to 6 years. Methods: A total of 6 databases and gray literature were searched using a Preferred Reporting Items for Systematic Reviews and Meta-Analyses--informed protocol. Data extraction included variables related to health equity. Results: In total, 20 studies were identified. Most papers implemented web-based versions of the Modified Checklist for Autism in Toddlers, Revised with Follow-Up screener for autism spectrum disorder or Parent Evaluation of Developmental Status screeners for broad developmental delay. Caregivers and practitioners indicated a preference for web-based screeners, primarily for user-friendliness, improved follow-up accuracy, time, and training efficiencies. Conclusions: Although evidence is limited as to the necessity of web- versus face-to-face--based developmental screening, there are clear efficiencies in its use. Trial Registration: PROSPERO CRD42019127894; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=127894 ", doi="10.2196/16085", url="http://mhealth.jmir.org/2020/4/e16085/", url="http://www.ncbi.nlm.nih.gov/pubmed/32324149" } @Article{info:doi/10.2196/16055, author="Romare, Charlotte and Sk{\"a}r, Lisa", title="Smart Glasses for Caring Situations in Complex Care Environments: Scoping Review", journal="JMIR Mhealth Uhealth", year="2020", month="Apr", day="20", volume="8", number="4", pages="e16055", keywords="anesthesia department", keywords="critical care", keywords="intensive care units", keywords="scoping review", keywords="smart glasses", abstract="Background: Anesthesia departments and intensive care units represent two advanced, high-tech, and complex care environments. Health care in those environments involves different types of technology to provide safe, high-quality care. Smart glasses have previously been used in different health care settings and have been suggested to assist health care professionals in numerous areas. However, smart glasses in the complex contexts of anesthesia care and intensive care are new and innovative. An overview of existing research related to these contexts is needed before implementing smart glasses into complex care environments. Objective: The aim of this study was to highlight potential benefits and limitations with health care professionals' use of smart glasses in situations occurring in complex care environments. Methods: A scoping review with six steps was conducted to fulfill the objective. Database searches were conducted in PubMed and Scopus; original articles about health care professionals' use of smart glasses in complex care environments and/or situations occurring in those environments were included. The searches yielded a total of 20 articles that were included in the review. Results: Three categories were created during the qualitative content analysis: (1) smart glasses as a versatile tool that offers opportunities and challenges, (2) smart glasses entail positive and negative impacts on health care professionals, and (3) smart glasses' quality of use provides facilities and leaves room for improvement. Smart glasses were found to be both a helpful tool and a hindrance in caring situations that might occur in complex care environments. This review provides an increased understanding about different situations where smart glasses might be used by health care professionals in clinical practice in anesthesia care and intensive care; however, research about smart glasses in clinical complex care environments is limited. Conclusions: Thoughtful implementation and improved hardware are needed to meet health care professionals' needs. New technology brings challenges; more research is required to elucidate how smart glasses affect patient safety, health care professionals, and quality of care in complex care environments. ", doi="10.2196/16055", url="http://mhealth.jmir.org/2020/4/e16055/", url="http://www.ncbi.nlm.nih.gov/pubmed/32310144" } @Article{info:doi/10.2196/15446, author="Cheikh-Moussa, Kamila and Mira, Joaquin Jose and Orozco-Beltran, Domingo", title="Improving Engagement Among Patients With Chronic Cardiometabolic Conditions Using mHealth: Critical Review of Reviews", journal="JMIR Mhealth Uhealth", year="2020", month="Apr", day="8", volume="8", number="4", pages="e15446", keywords="mHealth", keywords="patients", keywords="telemedicine", keywords="engagement", keywords="chronic disease", keywords="cardiovascular disease", keywords="diabetes", keywords="obesity", abstract="Background: The burden imposed by cardiometabolic diseases remains a principal health care system concern. Integration of mobile health (mHealth) interventions is helpful for telemonitoring of these patients, which enables patients to be more active and take part in their treatment, while being more conscious and gaining more control over the outcomes. However, little is known about the degree to which users engage, and the extent to which this interaction matches the usage pattern for which mHealth interventions were designed. Objective: The aim of this study was to describe the characteristics and results of studies on mHealth solutions that measured the effects of interventions with patient engagement in the context of chronic cardiometabolic diseases. Methods: A critical review of systematic reviews was conducted to recover data on interventions focused on the engagement of patients with chronic cardiometabolic diseases using mHealth technologies. Articles (from January 1, 2010) were searched in the Medlars Online International Literature Medline (Medline/Pubmed), Embase, Cochrane Library, PsycINFO, and Scielo databases. Only studies that quantified a measure of engagement by patients with cardiometabolic disease were included for analysis. The Critical Appraisal Skills Programme (CASP) was used to determine included studies considering the quality of the data provided. The Scottish Intercollegiate Guidelines Network (SIGN) checklist was used to assess the quality of the evidence according to the methodology used in the studies reviewed. Engagement was defined as the level of patient implication or participation in self-care interventions. Engagement measures included number of logs to the website or platform, frequency of usage, number of messages exchanged, and number of tasks completed. Results: Initially, 638 papers were retrieved after applying the inclusion and exclusion criteria. Finally, only three systematic reviews measuring engagement were included in the analysis. No reviews applying a meta-analysis approach were found. The three review articles described the results of 10 clinical trials and feasibility studies that quantified engagement and met the inclusion criteria assessed through CASP. The sample size varied between 6 and 270 individuals, who were predominantly men. Cardiac disease was the principal target in the comparison of traditional and mHealth interventions for engagement improvement. The level of patient engagement with mHealth technologies varied between 50\% and 97\%, and technologies incorporating smartphones with a reminder function resulted in the highest level of engagement. Conclusions: mHealth interventions are an effective solution for improving engagement of patients with chronic cardiometabolic diseases. However, there is a need for advanced analysis and higher-quality studies focused on long-term engagement with specific interventions. The use of smartphones with a single app that includes a reminder function appears to result in better improvement in active participation, leading to higher engagement among patients with cardiometabolic diseases. ", doi="10.2196/15446", url="https://mhealth.jmir.org/2020/4/e15446", url="http://www.ncbi.nlm.nih.gov/pubmed/32267239" } @Article{info:doi/10.2196/15549, author="Yang, Yang and Chen, Helen and Qazi, Hammad and Morita, P. Plinio", title="Intervention and Evaluation of Mobile Health Technologies in Management of Patients Undergoing Chronic Dialysis: Scoping Review", journal="JMIR Mhealth Uhealth", year="2020", month="Apr", day="3", volume="8", number="4", pages="e15549", keywords="mobile health", keywords="renal dialysis", keywords="health technology assessment", keywords="patient outcome assessment", abstract="Background: Studies have shown the effectiveness and user acceptance of mobile health (mHealth) technologies in managing patients with chronic kidney disease (CKD). However, incorporating mHealth technology into the standard care of patients with CKD still faces many challenges. To our knowledge, there are no reviews on mHealth interventions and their assessments concerning the management of patients undergoing dialysis. Objective: This study provided a scoping review on existing apps and interventions of mHealth technologies in adult patients undergoing chronic dialysis and identified the gaps in patient outcome assessment of mHealth technologies in the literature. Methods: We systematically searched PubMed (MEDLINE), Scopus, and the Cumulative Index to Nursing and Allied Health Literature databases, as well as gray literature sources. Two keywords, ``mHealth'' and ``dialysis,'' were combined to address the main concepts of the objectives. Inclusion criteria were as follows: (1) mHealth interventions, which are on a smartphone, tablet, or web-based portals that are accessible through mobile devices; and (2) adult patients (age ?18 years) on chronic dialysis. Only English papers published from January 2008 to October 2018 were included. Studies with mHealth apps for other chronic conditions, based on e-consultation or videoconferencing, non-English publications, and review papers were excluded. Results: Of the 1054 papers identified, 22 met the inclusion and exclusion criteria. Most studies (n=20) were randomized controlled trials and cohort studies. These studies were carried out in 7 countries. The main purposes of these mHealth interventions were as follows: nutrition or dietary self-monitoring (n=7), remote biometric monitoring (n=7), web-based portal (n=4), self-monitoring of in-session dialysis-specific information (n=3), and self-monitoring of lifestyle or behavioral change (n=1). The outcomes of the 22 included studies were organized into five categories: (1) patient satisfaction and acceptance, (2) clinical effectiveness, (3) economic assessment, (4) health-related quality of life, and (5) impact on lifestyle or behavioral change. The mHealth interventions showed neutral to positive results in chronic dialysis patient management, reporting no to significant improvement of dialysis-specific measurements and some components of the overall quality of life assessment. Evaluation of these mHealth interventions consistently demonstrated evidence in patients' satisfaction, high level of user acceptance, and reduced use of health resources and cost savings to health care services. However, there is a lack of studies evaluating safety, organizational, sociocultural, ethical, and legal aspects of mHealth technologies. Furthermore, a comprehensive cost-effectiveness and cost-benefit analysis of adopting mHealth technologies was not found in the literature. Conclusions: The gaps identified in this study will inform the creation of health policies and organizational support for mHealth implementation in patients undergoing dialysis. The findings of this review will inform the development of a comprehensive service model that utilizes mHealth technologies for home monitoring and self-management of patients undergoing chronic dialysis. ", doi="10.2196/15549", url="https://mhealth.jmir.org/2020/4/e15549", url="http://www.ncbi.nlm.nih.gov/pubmed/32242823" } @Article{info:doi/10.2196/14897, author="Miralles, Ignacio and Granell, Carlos and D{\'i}az-Sanahuja, Laura and Van Woensel, William and Bret{\'o}n-L{\'o}pez, Juana and Mira, Adriana and Castilla, Diana and Casteleyn, Sven", title="Smartphone Apps for the Treatment of Mental Disorders: Systematic Review", journal="JMIR Mhealth Uhealth", year="2020", month="Apr", day="2", volume="8", number="4", pages="e14897", keywords="mental health", keywords="mental disorders", keywords="treatment", keywords="intervention", keywords="mHealth", keywords="smartphone", keywords="mobile phone", keywords="mobile apps", keywords="systematic review", abstract="Background: Smartphone apps are an increasingly popular means for delivering psychological interventions to patients suffering from a mental disorder. In line with this popularity, there is a need to analyze and summarize the state of the art, both from a psychological and technical perspective. Objective: This study aimed to systematically review the literature on the use of smartphones for psychological interventions. Our systematic review has the following objectives: (1) analyze the coverage of mental disorders in research articles per year; (2) study the types of assessment in research articles per mental disorder per year; (3) map the use of advanced technical features, such as sensors, and novel software features, such as personalization and social media, per mental disorder; (4) provide an overview of smartphone apps per mental disorder; and (5) provide an overview of the key characteristics of empirical assessments with rigorous designs (ie, randomized controlled trials [RCTs]). Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for systematic reviews were followed. We performed searches in Scopus, Web of Science, American Psychological Association PsycNET, and Medical Literature Analysis and Retrieval System Online, covering a period of 6 years (2013-2018). We included papers that described the use of smartphone apps to deliver psychological interventions for known mental disorders. We formed multidisciplinary teams, comprising experts in psychology and computer science, to select and classify articles based on psychological and technical features. Results: We found 158 articles that met the inclusion criteria. We observed an increasing interest in smartphone-based interventions over time. Most research targeted disorders with high prevalence, that is, depressive (31/158,19.6\%) and anxiety disorders (18/158, 11.4\%). Of the total, 72.7\% (115/158) of the papers focused on six mental disorders: depression, anxiety, trauma and stressor-related, substance-related and addiction, schizophrenia spectrum, and other psychotic disorders, or a combination of disorders. More than half of known mental disorders were not or very scarcely (<3\%) represented. An increasing number of studies were dedicated to assessing clinical effects, but RCTs were still a minority (25/158, 15.8\%). From a technical viewpoint, interventions were leveraging the improved modalities (screen and sound) and interactivity of smartphones but only sparingly leveraged their truly novel capabilities, such as sensors, alternative delivery paradigms, and analytical methods. Conclusions: There is a need for designing interventions for the full breadth of mental disorders, rather than primarily focusing on most prevalent disorders. We further contend that an increasingly systematic focus, that is, involving RCTs, is needed to improve the robustness and trustworthiness of assessments. Regarding technical aspects, we argue that further exploration and innovative use of the novel capabilities of smartphones are needed to fully realize their potential for the treatment of mental health disorders. ", doi="10.2196/14897", url="https://mhealth.jmir.org/2020/4/e14897", url="http://www.ncbi.nlm.nih.gov/pubmed/32238332" } @Article{info:doi/10.2196/17776, author="Li, Ran and Liang, Ning and Bu, Fanlong and Hesketh, Therese", title="The Effectiveness of Self-Management of Hypertension in Adults Using Mobile Health: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2020", month="Mar", day="27", volume="8", number="3", pages="e17776", keywords="hypertension", keywords="self-management", keywords="mHealth", keywords="medication adherence", keywords="mobile phone", keywords="health behavior", abstract="Background: Effective treatment of hypertension requires careful self-management. With the ongoing development of mobile technologies and the scarcity of health care resources, mobile health (mHealth)--based self-management has become a useful treatment for hypertension, and its effectiveness has been assessed in many trials. However, there is a paucity of comprehensive summaries of the studies using both qualitative and quantitative methods. Objective: This systematic review aimed to measure the effectiveness of mHealth in improving the self-management of hypertension for adults. The outcome measures were blood pressure (BP), BP control, medication adherence, self-management behavior, and costs. Methods: A systematic search was conducted using 5 electronic databases. The snowballing method was used to scan the reference lists of relevant studies. Only peer-reviewed randomized controlled trials (RCTs) published between January 2010 and September 2019 were included. Data extraction and quality assessment were performed by 3 researchers independently, adhering to the validation guideline and checklist. Both a meta-analysis and a narrative synthesis were carried out. Results: A total of 24 studies with 8933 participants were included. Of these, 23 studies reported the clinical outcome of BP, 12 of these provided systolic blood pressure (SBP) and diastolic blood pressure (DBP) data, and 16 articles focused on change in self-management behavior and medication adherence. All 24 studies were included in the narrative synthesis. According to the meta-analysis, a greater reduction in both SBP and DBP was observed in the mHealth intervention groups compared with control groups, ?3.78 mm Hg (P<.001; 95\% CI ?4.67 to ?2.89) and ?1.57 mm Hg (P<.001; 95\% CI ?2.28 to ?0.86), respectively. Subgroup analyses showed consistent reductions in SBP and DBP across different frequencies of reminders, interactive patterns, intervention functions, and study duration subgroups. A total of 16 studies reported better medication adherence and behavioral change in the intervention groups, while 8 showed no significant change. Six studies included an economic evaluation, which drew inconsistent conclusions. However, potentially long-term financial benefits were mentioned in all economic evaluations. All studies were assessed to be at high risk of bias. Conclusions: This review found that mHealth self-management interventions were effective in BP control. The outcomes of this review showed improvements in self-management behavior and medication adherence. The most successful mHealth intervention combined the feature of tailored messages, interactive communication, and multifaceted functions. Further research with longer duration and cultural adaptation is necessary. With increasing disease burden from hypertension globally, mHealth offers a potentially effective method for self-management and control of BP. mHealth can be easily integrated into existing health care systems. Trial Registration: PROSPERO CRD42019152062; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=152062 ", doi="10.2196/17776", url="http://mhealth.jmir.org/2020/3/e17776/", url="http://www.ncbi.nlm.nih.gov/pubmed/32217503" } @Article{info:doi/10.2196/17046, author="Milne-Ives, Madison and Lam, Ching and De Cock, Caroline and Van Velthoven, Helena Michelle and Meinert, Edward", title="Mobile Apps for Health Behavior Change in Physical Activity, Diet, Drug and Alcohol Use, and Mental Health: Systematic Review", journal="JMIR Mhealth Uhealth", year="2020", month="Mar", day="18", volume="8", number="3", pages="e17046", keywords="telemedicine", keywords="evidence-based medicine", keywords="mobile health", keywords="digital health", keywords="mobile applications", keywords="app", keywords="cell phone", keywords="smartphone", keywords="mobile phone", keywords="health behavior", keywords="intervention", keywords="behavior change", keywords="systematic review", abstract="Background: With a growing focus on patient interaction with health management, mobile apps are increasingly used to deliver behavioral health interventions. The large variation in these mobile health apps---their target patient group, health behavior, and behavioral change strategies---has resulted in a large but incohesive body of literature. Objective: This systematic review aimed to assess the effectiveness of mobile apps in improving health behaviors and outcomes and to examine the inclusion and effectiveness of behavior change techniques (BCTs) in mobile health apps. Methods: PubMed, EMBASE, CINAHL, and Web of Science were systematically searched for articles published between 2014 and 2019 that evaluated mobile apps for health behavior change. Two authors independently screened and selected studies according to the eligibility criteria. Data were extracted and the risk of bias was assessed by one reviewer and validated by a second reviewer. Results: A total of 52 randomized controlled trials met the inclusion criteria and were included in the analysis---37 studies focused on physical activity, diet, or a combination of both, 11 on drug and alcohol use, and 4 on mental health. Participant perceptions were generally positive---only one app was rated as less helpful and satisfactory than the control---and the studies that measured engagement and usability found relatively high study completion rates (mean 83\%; n=18, N=39) and ease-of-use ratings (3 significantly better than control, 9/15 rated >70\%). However, there was little evidence of changed behavior or health outcomes. Conclusions: There was no strong evidence in support of the effectiveness of mobile apps in improving health behaviors or outcomes because few studies found significant differences between the app and control groups. Further research is needed to identify the BCTs that are most effective at promoting behavior change. Improved reporting is necessary to accurately evaluate the mobile health app effectiveness and risk of bias. ", doi="10.2196/17046", url="http://mhealth.jmir.org/2020/3/e17046/", url="http://www.ncbi.nlm.nih.gov/pubmed/32186518" } @Article{info:doi/10.2196/16060, author="Portz, D. Jennifer and Elsbernd, Kira and Plys, Evan and Ford, Lynett Kelsey and Zhang, Xuhong and Gore, Odette M. and Moore, L. Susan and Zhou, Shuo and Bull, Sheana", title="Elements of Social Convoy Theory in Mobile Health for Palliative Care: Scoping Review", journal="JMIR Mhealth Uhealth", year="2020", month="Jan", day="6", volume="8", number="1", pages="e16060", keywords="mHealth", keywords="palliative care", keywords="caregivers", keywords="mobile apps", abstract="Background: Mobile health (mHealth) provides a unique modality for improving access to and awareness of palliative care among patients, families, and caregivers from diverse backgrounds. Some mHealth palliative care apps exist, both commercially available and established by academic researchers. However, the elements of family support and family caregiving tools offered by these early apps is unknown. Objective: The objective of this scoping review was to use social convoy theory to describe the inclusion and functionality of family, social relationships, and caregivers in palliative care mobile apps. Methods: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Review guidelines, a systematic search of palliative care mHealth included (1) research-based mobile apps identified from academic searches published between January 1, 2010, and March 31, 2019 and (2) commercially available apps for app stores in April 2019. Two reviewers independently assessed abstracts, app titles, and descriptions against the inclusion and exclusion criteria. Abstracted data covered app name, research team or developer, palliative care element, target audience, and features for family support and caregiving functionality as defined by social convoy theory. Results: Overall, 10 articles describing 9 individual research-based apps and 22 commercially available apps were identified. Commercially available apps were most commonly designed for both patients and social convoys, whereas the majority of research apps were designed for patient use only. Conclusions: Results suggest there is an emerging presence of apps for patients and social convoys receiving palliative care; however, there are many needs for developers and researchers to address in the future. Although palliative care mHealth is a growing field, additional research is needed for apps that embrace a team approach to information sharing, target family- and caregiver-specific issues, promote access to palliative care, and are comprehensive of palliative needs. ", doi="10.2196/16060", url="https://mhealth.jmir.org/2020/1/e16060", url="http://www.ncbi.nlm.nih.gov/pubmed/31904581" } @Article{info:doi/10.2196/13311, author="Taj, Fawad and Klein, A. Michel C. and van Halteren, Aart", title="Digital Health Behavior Change Technology: Bibliometric and Scoping Review of Two Decades of Research", journal="JMIR Mhealth Uhealth", year="2019", month="Dec", day="13", volume="7", number="12", pages="e13311", keywords="persuasive technology", keywords="digital health behavior", keywords="behavior change systems", keywords="behavior change support systems", keywords="bibliometric analysis", keywords="scoping review", abstract="Background: Research on digital technology to change health behavior has increased enormously in recent decades. Due to the interdisciplinary nature of this topic, knowledge and technologies from different research areas are required. Up to now, it is not clear how the knowledge from those fields is combined in actual applications. A comprehensive analysis that systematically maps and explores the use of knowledge within this emerging interdisciplinary field is required. Objective: This study aims to provide an overview of the research area around the design and development of digital technologies for health behavior change and to explore trends and patterns. Methods: A bibliometric analysis is used to provide an overview of the field, and a scoping review is presented to identify the trends and possible gaps. The study is based on the publications related to persuasive technologies and health behavior change in the last 18 years, as indexed by the Web of Science and Scopus (317 and 314 articles, respectively). In the first part, regional and time-based publishing trends; research fields and keyword co-occurrence networks; influential journals; and collaboration network between influential authors, countries, and institutions are examined. In the second part, the behavioral domains, technological means and theoretical foundations are investigated via a scoping review. Results: The literature reviewed shows a clear and emerging trend after 2001 in technology-based behavior change, which grew exponentially after the introduction of the smartphone around 2009. Authors from the United States, Europe, and Australia have the highest number of publications in the field. The three most active research areas are computer science, public and occupational health, and psychology. The keyword ``mhealth'' was the dominant term and predominantly used together with the term ``physical activity'' and ``ehealth''. A total of three strong clusters of coauthors have been found. Nearly half of the total reported papers were published in three journals. The United States, the United Kingdom, and the Netherlands have the highest degree of author collaboration and a strong institutional network. Mobile phones were most often used as a technology platform, regardless of the targeted behavioral domain. Physical activity and healthy eating were the most frequently targeted behavioral domains. Most articles did not report about the behavior change techniques that were applied. Among the reported behavior change techniques, goal setting and self-management were the most frequently reported. Conclusions: Closer cooperation and interaction between behavioral sciences and technological areas is needed, so that theoretical knowledge and new technological advancements are better connected in actual applications. Eventually, this could result in a larger societal impact, an increase of the effectiveness of digital technologies for health behavioral change, and more insight in the relationship between behavioral change strategies and persuasive technologies' effectiveness. ", doi="10.2196/13311", url="https://mhealth.jmir.org/2019/12/e13311", url="http://www.ncbi.nlm.nih.gov/pubmed/31833836" } @Article{info:doi/10.2196/15122, author="Koo, Mi Bon and Vizer, M. Lisa", title="Examining Mobile Technologies to Support Older Adults With Dementia Through the Lens of Personhood and Human Needs: Scoping Review", journal="JMIR Mhealth Uhealth", year="2019", month="Nov", day="11", volume="7", number="11", pages="e15122", keywords="dementia", keywords="Alzheimer disease", keywords="mobile health", keywords="consumer health informatics", keywords="personhood", keywords="systematic review", keywords="smartphone", keywords="mobile phone", keywords="tablet computers", abstract="Background: With the world's rapidly growing older adult population, there is an increase in the number of people living with dementia. This growth leads to a strain on their caregivers and our health care system and to an increased attention on mitigating strain by using mobile technology to sustain the independence of people with dementia. However, less attention is given to whether these technologies meet the stated and unstated needs of people with dementia. Objective: The aim of this study was to provide an overview of the current research on mobile technologies for people with dementia, considering the current research through the lens of personhood and human needs, and to identify any gaps that represent research opportunities. Methods: We performed a systematic search in Medical Literature Analysis and Retrieval System Online (MEDLINE), Web of Science, PsycINFO, Cumulative Index of Nursing and Allied Health Literature (CINAHL), Excerpta Medica dataBASE (EMBASE), and the Cochrane Central Register of Controlled Trials (CENTRAL) in October 2018. We screened 5560 articles and identified 24 that met our inclusion and exclusion criteria. We then performed thematic analysis to organize the articles by the types of support mobile technologies provide and mapped those types of support to human needs to identify the gaps in support. Results: Articles described research on mobile technologies that support people with dementia to (1) perform daily activities, (2) maintain social interaction, (3) aid memory, (4) engage in leisure activities, (5) track location, and (6) monitor health. At least one type of support mapped to each human need, with most supporting lower-level needs such as physiological and safety needs. Little attention seems to be paid to personhood. Conclusions: Mobile technologies that support daily activities, relationships, memory, leisure activities, health, and safety can partially compensate for decreased function owing to dementia, but the human needs of people with dementia are often not adequately considered. Most technologies support basic physiological and safety needs, whereas many pay little attention to higher-level needs such as self-esteem and agency. Important research opportunities include using person-centered methods to develop technology to meet higher-level needs and to preserve personhood by incorporating human and psychological needs of people with dementia along with ethical considerations. ", doi="10.2196/15122", url="https://mhealth.jmir.org/2019/11/e15122", url="http://www.ncbi.nlm.nih.gov/pubmed/31710305" } @Article{info:doi/10.2196/12612, author="Puigdomenech Puig, Elisa and Robles, Noem{\'i} and Saig{\'i}-Rubi{\'o}, Francesc and Zamora, Alberto and Moharra, Montse and Paluzie, Guillermo and Balfeg{\'o}, Mariona and Cuatrecasas Cambra, Guillem and Garcia-Lorda, Pilar and Carrion, Carme", title="Assessment of the Efficacy, Safety, and Effectiveness of Weight Control and Obesity Management Mobile Health Interventions: Systematic Review", journal="JMIR Mhealth Uhealth", year="2019", month="Oct", day="25", volume="7", number="10", pages="e12612", keywords="mHealth", keywords="obesity", keywords="overweight", keywords="systematic review", keywords="technology assessment", abstract="Background: The use of apps to tackle overweight and obesity by tracking physical and dietary patterns and providing recommendations and motivation strategies to achieve personalized goals has increased over recent years. However, evidence of the efficacy, effectiveness, and safety of these apps is severely lacking. Objective: The aim of this study was to identify efficacy, safety, and effectiveness criteria used to assess weight control, overweight, and obesity management in mobile health (mHealth) interventions through a systematic review. Methods: PubMed, PsycINFO, Scopus, UK Trial Database, ClinicalTrials.gov, and the Cochrane Library were surveyed up to May 2018. All types of clinical studies were considered. A total of 2 independent reviewers assessed quality using Scottish Intercollegiate Guidelines Network (SIGN) criteria. Ratings were used to provide an overall score for each study (low, moderate, or high). Data were synthesized in evidence tables. Results: From 233 potentially relevant publications, only 28 studies were included. Of these, 13 (46\%) were randomized control trials, 11 were single-arm studies (39\%), 3 were nonrandomized controlled trials (11\%), and 1 study was a cluster randomized trial (4\%). The studies were classified as low (15), high (7), and moderate (6) quality according to SIGN criteria. All studies focused on efficacy, with only 1 trial mentioning safety and another 1 effectiveness. In 11 studies, the apps were used as stand-alone interventions, the others were multicomponent studies that included other tools for support such as sensors or websites. The main management tool included in the apps was feedback messaging (24), followed by goal-setting mechanisms (20) and self-monitoring (19). The majority of studies took weight or body mass index loss as the main outcome (22) followed by changes in physical activity (14) and diet (12). Regarding outputs, usability, adherence, and engagement (17) were the most reported, followed by satisfaction (7) and acceptability (4). Conclusions: There is a remarkable heterogeneity among these studies and the majority have methodological limitations that leave considerable room for improvement. Further research is required to identify all relevant criteria for assessing the efficacy of mHealth interventions in the management of overweight and obesity. Trial Registration: PROSPERO CRD42017056761; https://tinyurl.com/y2zhxtjx ", doi="10.2196/12612", url="http://mhealth.jmir.org/2019/10/e12612/", url="http://www.ncbi.nlm.nih.gov/pubmed/31654566" } @Article{info:doi/10.2196/14404, author="Wang, Ziqi and Zhu, Yaxin and Cui, Liyuan and Qu, Bo", title="Electronic Health Interventions to Improve Adherence to Antiretroviral Therapy in People Living With HIV: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2019", month="Oct", day="16", volume="7", number="10", pages="e14404", keywords="HIV", keywords="highly active antiretroviral therapy", keywords="medication adherence", keywords="eHealth", abstract="Background: Electronic health (eHealth) is increasingly used for self-management and service delivery of HIV-related diseases. With the publication of studies increasingly focusing on antiretroviral therapy (ART) adherence, this makes it possible to quantitatively and systematically assess the effectiveness and feasibility of eHealth interventions. Objective: The purpose of this review was to explore the effectiveness of eHealth interventions on improving ART adherence in people living with HIV. The effects of different intervention characteristics, participant characteristics, and study characteristics were also assessed. Methods: We systematically searched MEDLINE (via PubMed), EMBASE, the Cochrane Central Register of Controlled Trials, and 3 conference abstract databases using search terms related to HIV, ART, adherence, and eHealth interventions. We independently screened the studies, extracted the data, and assessed the study quality and then compared the information in pairs. Articles published in English that used randomized controlled trials to assess eHealth interventions to improve ART adherence of people living with HIV were identified. We extracted the data including study characteristics, participant characteristics, intervention characteristics, and outcome measures. The Cochrane risk-of-bias tool was used to assess the risk of bias and study overall quality. Odds ratios, Cohen d, and their 95\% CIs were estimated using random-effects models. We also performed multiple subgroup analyses and sensitivity analyses to define any sources of heterogeneity. Results: Among 3941 articles identified, a total of 19 studies (including 21 trials) met the inclusion criteria. We found 8 trials from high-income countries and 13 trials from low- and middle-income countries. Furthermore, at baseline, the health status of participants in 14 trials was healthy. Of the trials included, 7 of 21 used personality content, 12 of 21 used a 2-way communication strategy, and 7 of 21 used medical content. In the pooled analysis of 3937 participants (mean age: 35 years; 47.16\%, 1857/3937 females), eHealth interventions significantly improved the ART adherence of people living with HIV (pooled Cohen d=0.25; 95\% CI 0.05 to 0.46; P=.01). The interventions were also correlated with improved biochemical outcomes reported by 11 trials (pooled Cohen d=0.25; 95\% CI 0.11 to 0.38; P<.001). The effect was sensitive to sample size (Q=5.56; P=.02) and study duration (Q=8.89; P=.003), but it could not be explained by other moderators. The primary meta-analysis result was stable in the 3 sensitivity analyses. Conclusions: Some of the eHealth interventions may be used as an effective method to increase the ART adherence of people living with HIV. Considering that most of the trials included a small sample size and were conducted for a short duration, these results should be interpreted with caution. Future studies need to determine the features of eHealth interventions to better improve ART adherence along with long-term effectiveness of interventions, effectiveness of real-time adherence monitoring, enhancement of study design, and influences on biochemical outcomes. ", doi="10.2196/14404", url="https://mhealth.jmir.org/2019/10/e14404", url="http://www.ncbi.nlm.nih.gov/pubmed/31621641" } @Article{info:doi/10.2196/14877, author="Hobson, R. Georgina and Caffery, J. Liam and Neuhaus, Maike and Langbecker, H. Danette", title="Mobile Health for First Nations Populations: Systematic Review", journal="JMIR Mhealth Uhealth", year="2019", month="Oct", day="7", volume="7", number="10", pages="e14877", keywords="mHealth", keywords="mobile health", keywords="indigenous", keywords="First Nations", keywords="aboriginal", keywords="humans", keywords="systematic review", abstract="Background: The ubiquitous presence and functionality of mobile devices offers the potential for mobile health (mHealth) to create equitable health opportunities. While mHealth is used among First Nations populations to respond to health challenges, the characteristics, uptake, and effectiveness of these interventions are unclear. Objective: This review aimed to identify the characteristics of mHealth interventions (eg, study locations, health topic, and modality) evaluated with First Nations populations and to summarize the outcomes reported for intervention use, user perspectives including cultural responsiveness, and clinical effectiveness. In addition, the review sought to identify the presence of First Nations expertise in the design and evaluation of mHealth interventions with First Nations populations. Methods: The methods of this systematic review were detailed in a registered protocol with the International Prospective Register of Systematic Reviews (PROSPERO, CRD42019123276). Systematic searches of peer-reviewed, scientific papers were conducted across 7 databases in October 2018. Eligible studies had a primary focus on mHealth interventions with experimental or quasi-experimental design to respond to a health challenge with First Nations people from Canada, Australia, New Zealand, and the United States. Two authors independently screened records for eligibility and assessed risk of bias using the Joanna Briggs Institute checklists. Data were synthesized narratively owing to the mix of study designs, interventions, and outcomes. The review was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Results: Searches yielded 1053 unique records, after review and screening, 13 studies (5 randomized controlled trials and 8 quasi-experimental designs) were included in the final analysis. Studies were conducted in Australia (n=9), the United States (n=2), and New Zealand (n=2). The most common health challenge addressed was mental health and suicide (n=5). Intervention modalities included text messaging (n=5), apps (n=4), multimedia messaging (n=1), tablet software (n=1), or a combination of short messaging service (SMS) and apps (n=1). Results showed mixed engagement with the intervention (n=3); favorable user perspectives, including acceptability and cultural appropriateness (n=6); and mixed outcomes for clinical effectiveness (n=10). A diverse range of risks of bias were identified, the most common of which included a lack of clarity about allocation and blinding protocols and group treatment for randomized controlled trials and a lack of control group and single outcome measures for quasi-experimental designs. First Nations expertise informed all mHealth studies, through authorship (n=8), affiliation with First Nations bodies (n=3), participatory study design (n=5), First Nations reference groups (n=5), or a combination of these. Conclusions: mHealth modalities, including SMS and apps, appear favorable for delivery of health interventions with First Nations populations, particularly in the area of mental health and suicide prevention. Importantly, First Nations expertise was strongly embedded within the studies, augmenting favorable use and user engagement. However, evidence of efficacy is limited. ", doi="10.2196/14877", url="https://mhealth.jmir.org/2019/10/e14877", url="http://www.ncbi.nlm.nih.gov/pubmed/31593537" } @Article{info:doi/10.2196/14275, author="Wali, Sahr and Hussain-Shamsy, Neesha and Ross, Heather and Cafazzo, Joseph", title="Investigating the Use of Mobile Health Interventions in Vulnerable Populations for Cardiovascular Disease Management: Scoping Review", journal="JMIR Mhealth Uhealth", year="2019", month="Oct", day="7", volume="7", number="10", pages="e14275", keywords="mobile health", keywords="health services", keywords="indigenous", keywords="low- and middle-income countries", keywords="cardiovascular disease", keywords="self-care", abstract="Background: Cardiovascular disease (CVD) has grown to become one of the leading causes of mortality worldwide. The advancements of CVD-related treatments have led to a decline in CVD prevalence among individuals in high-income countries (HICs). However, these improvements do not reflect the state of individuals in low- and middle-income countries (LMICs) and vulnerable subgroup populations in HICs, such as the Indigenous. To help minimize the health disparities in these populations, technology-based interventions have been offered as a potential solution, but there is concern regarding if they will be effective, or even needed, as these tools have been designed for use in HICs. Objective: The objective of this study was to explore how mobile health (mHealth) interventions currently assist individuals in Indigenous communities and LMICs with CVD management. Methods: A scoping review guided by the methods outlined by Arksey and O'Malley was conducted. A comprehensive search was completed by 2 reviewers in 5 electronic databases using keywords related to mobile health, cardiovascular disease, self-care, Indigenous communities, and LMICs. Studies were screened over 2 rounds and critically reviewed using a descriptive-analytical narrative method. Descriptive data were categorized into thematic groups reflecting the major findings related to the study objective. Results: We identified a total of 11 original articles and 11 review papers that met the criteria for this scoping review. The majority of the studies included a telemonitoring- and text messaging (short message service, SMS)--related feature associated with the intervention. The use of SMS was the most common approach to effectively promote disease management among individuals in both LMICs and Indigenous communities. However, customizing for cultural considerations within the design of the intervention was highlighted as a pivotal component to encourage CVD management. Specifically, individuals emphasized that the inclusion of collaborative partnerships with community members would strengthen the effectiveness of the intervention by ensuring it was designed with the appropriate context. Conclusions: Technology-based interventions used within Indigenous communities and LMICs have shown their potential to assist individuals with managing their condition. Although the literature available regarding this topic is limited, this review outlines key components to promote the effective use of these tools in the context of these vulnerable populations. ", doi="10.2196/14275", url="https://mhealth.jmir.org/2019/10/e14275", url="http://www.ncbi.nlm.nih.gov/pubmed/31593547" } @Article{info:doi/10.2196/13245, author="Cruz, Marques Fl{\'a}via Oliveira Almeida and Vilela, Alencar Ricardo and Ferreira, Barros Elaine and Melo, Santos Nilce and Reis, Dos Paula Elaine Diniz", title="Evidence on the Use of Mobile Apps During the Treatment of Breast Cancer: Systematic Review", journal="JMIR Mhealth Uhealth", year="2019", month="Aug", day="27", volume="7", number="8", pages="e13245", keywords="mobile applications", keywords="health education", keywords="nursing care", keywords="review", keywords="educational technology", keywords="breast neoplasms", abstract="Background: Cancer is a major cause of morbidity, disability, and mortality worldwide, and breast cancer is the most common cause of death in women. Different modalities of cancer treatment can have adverse effects that reduce the quality of life of patients and lead to treatment interruptions, if not managed properly. The use of mobile technologies has brought innovative possibilities for improving health care. Mobile apps can help individuals manage their own health and well-being and may also promote healthy lifestyles and information access. Objective: The aim of this study was to identify available evidence on the use of mobile apps to provide information and facilitate communication regarding self-care management related to the adverse effects of toxicities owing to breast cancer therapy. Methods: This systematic review includes studies which were identified using a search strategy adapted for each electronic database: CINAHL, Cochrane Library, LILACS, LIVIVO, PubMed, SCOPUS, and Web of Science. In addition, a gray literature search was performed using Google Scholar. All the electronic database searches were conducted on April 17, 2019. Two investigators independently reviewed the titles and abstracts of the studies identified and then read the full text of all selected papers. The quality of the included studies was analyzed by the Cochrane Collaboration Risk of Bias Tool and the Methodological Index for Non-Randomized Studies. Results: A total of 9 studies which met the eligibility criteria---3 randomized clinical trials and 6 nonrandomized studies published in English from 2010 to 2018---were considered for this systematic review; 396 patients with breast cancer, as well as 40 experts in the medical and nursing fields, and 3 software engineers were included. Conclusions: The evidence from the studies included in this systematic review is currently limited but suggests that mobile apps for women with breast cancer might be an acceptable information source that can improve patient well-being; they can also be used to report symptoms and adverse treatment-related effects and promote self-care. There is a need to test more evidence-based apps in future randomized clinical trials. ", doi="10.2196/13245", url="http://mhealth.jmir.org/2019/8/e13245/", url="http://www.ncbi.nlm.nih.gov/pubmed/31456578" } @Article{info:doi/10.2196/12649, author="Trifan, Alina and Oliveira, Maryse and Oliveira, Lu{\'i}s Jos{\'e}", title="Passive Sensing of Health Outcomes Through Smartphones: Systematic Review of Current Solutions and Possible Limitations", journal="JMIR Mhealth Uhealth", year="2019", month="Aug", day="23", volume="7", number="8", pages="e12649", keywords="smartphone", keywords="mobile phone", keywords="mhealth", keywords="digital health", keywords="digital medicine", keywords="digital phenotyping", keywords="health care", keywords="self-management", keywords="systematic review", abstract="Background: Technological advancements, together with the decrease in both price and size of a large variety of sensors, has expanded the role and capabilities of regular mobile phones, turning them into powerful yet ubiquitous monitoring systems. At present, smartphones have the potential to continuously collect information about the users, monitor their activities and behaviors in real time, and provide them with feedback and recommendations. Objective: This systematic review aimed to identify recent scientific studies that explored the passive use of smartphones for generating health- and well-being--related outcomes. In addition, it explores users' engagement and possible challenges in using such self-monitoring systems. Methods: A systematic review was conducted, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, to identify recent publications that explore the use of smartphones as ubiquitous health monitoring systems. We ran reproducible search queries on PubMed, IEEE Xplore, ACM Digital Library, and Scopus online databases and aimed to find answers to the following questions: (1) What is the study focus of the selected papers? (2) What smartphone sensing technologies and data are used to gather health-related input? (3) How are the developed systems validated? and (4) What are the limitations and challenges when using such sensing systems? Results: Our bibliographic research returned 7404 unique publications. Of these, 118 met the predefined inclusion criteria, which considered publication dates from 2014 onward, English language, and relevance for the topic of this review. The selected papers highlight that smartphones are already being used in multiple health-related scenarios. Of those, physical activity (29.6\%; 35/118) and mental health (27.9; 33/118) are 2 of the most studied applications. Accelerometers (57.7\%; 67/118) and global positioning systems (GPS; 40.6\%; 48/118) are 2 of the most used sensors in smartphones for collecting data from which the health status or well-being of its users can be inferred. Conclusions: One relevant outcome of this systematic review is that although smartphones present many advantages for the passive monitoring of users' health and well-being, there is a lack of correlation between smartphone-generated outcomes and clinical knowledge. Moreover, user engagement and motivation are not always modeled as prerequisites, which directly affects user adherence and full validation of such systems. ", doi="10.2196/12649", url="http://mhealth.jmir.org/2019/8/e12649/", url="http://www.ncbi.nlm.nih.gov/pubmed/31444874" } @Article{info:doi/10.2196/13309, author="Sandberg, J. Charlotte E. and Knight, R. Stephen and Qureshi, Uzair Ahmad and Pathak, Samir", title="Using Telemedicine to Diagnose Surgical Site Infections in Low- and Middle-Income Countries: Systematic Review", journal="JMIR Mhealth Uhealth", year="2019", month="Aug", day="19", volume="7", number="8", pages="e13309", keywords="surgical site infection", keywords="wound infection", keywords="developing country", keywords="low- and middle-income countries", keywords="telemedicine", keywords="postoperative", keywords="follow-up", abstract="Background: A high burden of preventable morbidity and mortality due to surgical site infections (SSIs) occurs in low- and middle-income countries (LMICs), and most of these SSIs occur following discharge. There is a high loss to follow-up due to a wide geographical spread of patients, and cost of travel can result in delayed and missed diagnoses. Objective: This review analyzes the literature surrounding the use of telemedicine and assesses the feasibility of using mobile phone technology to both diagnose SSIs remotely in LMICs and to overcome social barriers. Methods: A literature search was performed using Medline, Embase, CINAHL, PubMed, Web of Science, the Cochrane Central Register of Controlled Trials and Google Scholar. Included were English language papers reporting the use of telemedicine for detecting SSIs in comparison to the current practice of direct clinical diagnosis. Papers were excluded if infections were not due to surgical wounds, or if SSIs were not validated with in-person diagnosis. The primary outcome of this review was to review the feasibility of telemedicine for remote SSI detection. Results: A total of 404 articles were screened and three studies were identified that reported on 2082 patients across three countries. All studies assessed the accuracy of remote diagnosis of SSIs using predetermined telephone questionnaires. In total, 44 SSIs were accurately detected using telemedicine and an additional 14 were picked up on clinical follow-up. Conclusions: The use of telemedicine has shown to be a feasible method in remote diagnosis of SSIs. Telemedicine is a useful adjunct for clinical practice in LMICs to decrease loss to postsurgical follow-up. ", doi="10.2196/13309", url="http://mhealth.jmir.org/2019/8/e13309/", url="http://www.ncbi.nlm.nih.gov/pubmed/31429414" } @Article{info:doi/10.2196/14655, author="Hansen, B. William and Scheier, M. Lawrence", title="Specialized Smartphone Intervention Apps: Review of 2014 to 2018 NIH Funded Grants", journal="JMIR Mhealth Uhealth", year="2019", month="Jul", day="29", volume="7", number="7", pages="e14655", keywords="smartphone", keywords="intervention", keywords="funded grants", keywords="mobile phone", abstract="Background: The widespread adoption of smartphones provides researchers with expanded opportunities for developing, testing and implementing interventions. National Institutes of Health (NIH) funds competitive, investigator-initiated grant applications. Funded grants represent the state of the science and therefore are expected to anticipate the progression of research in the near future. Objective: The objective of this paper is to provide an analysis of the kinds of smartphone-based intervention apps funded in NIH research grants during the five-year period between 2014 and 2018. Methods: We queried NIH Reporter to identify candidate funded grants that addressed mHealth and the use of smartphones. From 1524 potential grants, we identified 397 that met the requisites of including an intervention app. Each grant's abstract was analyzed to understand the focus of intervention. The year of funding, type of activity (eg, R01, R34, and so on) and funding were noted. Results: We identified 13 categories of strategies employed in funded smartphone intervention apps. Most grants included either one (35.0\%) or two (39.0\%) intervention approaches. These included artificial intelligence (57 apps), bionic adaptation (33 apps), cognitive and behavioral therapies (68 apps), contingency management (24 apps), education and information (85 apps), enhanced motivation (50 apps), facilitating, reminding and referring (60 apps), gaming and gamification (52 apps), mindfulness training (18 apps), monitoring and feedback (192 apps), norm setting (7 apps), skills training (85 apps) and social support and social networking (59 apps). The most frequently observed grant types included Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) grants (40.8\%) and Research Project?Grants (R01s) (26.2\%). The number of grants funded increased through the five-year period from 60 in 2014 to 112 in 2018. Conclusions: Smartphone intervention apps are increasingly competitive for NIH funding. They reflect a wide diversity of approaches that have significant potential for use in applied settings. ", doi="10.2196/14655", url="http://mhealth.jmir.org/2019/7/e14655/", url="http://www.ncbi.nlm.nih.gov/pubmed/31359866" } @Article{info:doi/10.2196/12042, author="Low, Kee Jac and Manias, Elizabeth", title="Use of Technology-Based Tools to Support Adolescents and Young Adults With Chronic Disease: Systematic Review and Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2019", month="Jul", day="18", volume="7", number="7", pages="e12042", keywords="young adult", keywords="adolescent", keywords="self-management", keywords="transition to adult care", keywords="disease management", keywords="systematic review", abstract="Background: With the large amount of material that is readily available on the internet, there are endless opportunities for electronic health--literate patients to obtain and learn new information. Although novel, a Web- or mobile-based program can be a powerful way to engage adolescents and young adults (AYAs). The ongoing engagement of AYAs with chronic disease is vital not only to empower them but also to ensure a smooth transition from pediatric to adult health care. Objective: This study aimed to evaluate the current evidence on Web- or mobile-based interventions designed for AYAs. Methods: This review was registered with PROSPERO: CRD42018096487. A systematic search of MEDLINE Complete, EMBASE, and CINAHL Complete was conducted on April 10, 2019, for studies that examined the perspectives of transition-age patients about technology-based interventions, the process involved in intervention development, or the evaluation of intervention efficacy. For each study, the comprehensiveness of reporting was appraised. The Downs and Black checklist was used for intervention efficacy trials, the Standards for Reporting Qualitative Research checklist was used for qualitative work, and a 16-item tool developed by Tong et al was used for questionnaire research. Results: The search uncovered 29 relevant studies, which included qualitative studies (n=14), intervention efficacy studies (n=7), questionnaire studies (n=4), mixed qualitative and questionnaire studies (n=2), and a mixed qualitative and pilot randomized controlled trial study (n=1). The reporting comprehensiveness score of questionnaires was rated considerably lower (n=6, 13\%-57\% [2/16-8/14]) than the scores of intervention efficacy trials (n=8, 48\%-85\% [13/27-23/27]) and qualitative research (n=17, 40\%-93\% [8.5/21-19.5/21]). AYAs were receptive to obtaining information via a website or mobile app. An intervention was more likely to be perceived as useful by AYAs when there was a concerted effort to involve AYAs and subject matter experts in the process of intervention design, as opposed to relying solely on the AYAs or the experts alone. The preferred medium of intervention delivery varied greatly for AYAs, ranging from static text to audiovisual materials. However, AYAs considered being concise was the most important aspect. Across different conditions, AYAs were interested in receiving information on diverse topics, such as anxiety and stress management, dealing with insurance, and having social relationships. Patients also requested for disease-specific information, such as weather forecasts and pollen levels for patients with asthma and information related to the pretransplant period for organ transplant recipients. Meta-analyses showed no significant group differences across time on quality of life, self-efficacy, and self-management. Conclusions: Owing to the lack of intervention efficacy trials, no conclusion can be drawn if an intervention delivered via a mobile app is better than that delivered via a website. However, through this systematic review, it is confirmed that AYAs were receptive to receiving medical information electronically. ", doi="10.2196/12042", url="http://mhealth.jmir.org/2019/7/e12042/", url="http://www.ncbi.nlm.nih.gov/pubmed/31322129" } @Article{info:doi/10.2196/13817, author="Vo, VanAnh and Auroy, Lola and Sarradon-Eck, Aline", title="Patients' Perceptions of mHealth Apps: Meta-Ethnographic Review of Qualitative Studies", journal="JMIR Mhealth Uhealth", year="2019", month="Jul", day="10", volume="7", number="7", pages="e13817", keywords="mHealth", keywords="apps", keywords="mobile apps", keywords="qualitative studies", keywords="systematic review", keywords="mobile phone", abstract="Background: Mobile phones and tablets are being increasingly integrated into the daily lives of many people worldwide. Mobile health (mHealth) apps have promising possibilities for optimizing health systems, improving care and health, and reducing health disparities. However, health care apps often seem to be underused after being downloaded. Objective: The aim of this paper is to reach a better understanding of people's perceptions, beliefs, and experience of mHealth apps as well as to determine how highly they appreciate these tools. Methods: A systematic review was carried out on qualitative studies published in English, on patients' perception of mHealth apps between January 2013 and June 2018. Data extracted from these articles were synthesized using a meta-ethnographic approach and an interpretative method. Results: A total of 356 articles were selected for screening, and 43 of them met the inclusion criteria. Most of the articles included populations inhabiting developed countries and were published during the last 2 years, and most of the apps on which they focused were designed to help patients with chronic diseases. In this review, we present the strengths and weaknesses of using mHealth apps from the patients' point of view. The strengths can be categorized into two main aspects: engaging patients in their own health care and increasing patient empowerment. The weaknesses pointed out by the participants focus on four main topics: trustworthiness, appropriateness, personalization, and accessibility of these tools. Conclusions: Although many of the patients included in the studies reviewed considered mHealth apps as a useful complementary tool, some major problems arise in their optimal use, including the need for more closely tailored designs, the cost of these apps, the validity of the information delivered, and security and privacy issues. Many of these issues could be resolved with more support from health providers. In addition, it would be worth developing standards to ensure that these apps provide patients accurate evidence-based information. ", doi="10.2196/13817", url="http://mhealth.jmir.org/2019/7/e13817/", url="http://www.ncbi.nlm.nih.gov/pubmed/31293246" } @Article{info:doi/10.2196/11926, author="McKay, H. Fiona and Wright, Annemarie and Shill, Jane and Stephens, Hugh and Uccellini, Mary", title="Using Health and Well-Being Apps for Behavior Change: A Systematic Search and Rating of Apps", journal="JMIR Mhealth Uhealth", year="2019", month="Jul", day="04", volume="7", number="7", pages="e11926", keywords="smartphone", keywords="mobile apps", keywords="health promotion", keywords="health behavior", keywords="rating", abstract="Background: Smartphones have allowed for the development and use of apps. There is now a proliferation of mobile health interventions for physical activity, healthy eating, smoking and alcohol cessation or reduction, and improved mental well-being. However, the strength or potential of these apps to lead to behavior change remains uncertain. Objective: The aim of this study was to review a large sample of healthy lifestyle apps at a single point in time (June to July 2018) to determine their potential for promoting health-related behavior change with a view to sharing this information with the public. In addition, the study sought to test a wide range of apps using a new scale, the App Behavior Change Scale (ABACUS). Methods: Apps focusing on 5 major modifiable lifestyle behaviors were identified using a priori key search terms across the Australian Apple iTunes and Google Play stores. Lifestyle behavior categories were selected for their impact on health and included smoking, alcohol use, physical activity, nutrition, and mental well-being. Apps were included if they had an average user rating between 3 and 5, if they were updated in the last 18 months, if the description of the app included 2 of 4 behavior change features, and if they were in English. The selected behavior change apps were rated in 2 ways using previously developed rating scales: the Mobile App Rating Scale (MARS) for functionality and the ABACUS for potential to encourage behavior change. Results: The initial search identified 212,352 apps. After applying the filtering criteria, 5018 apps remained. Of these, 344 were classified as behavior change apps and were reviewed and rated. Apps were given an average MARS score of 2.93 out of 5 (SD 0.58, range 1.42-4.16), indicating low-to-moderate functionality. Scores for the ABACUS ranged from 1 to 17, out of 21, with an average score of 7.8 (SD 2.8), indicating a low-to-moderate number of behavior change techniques included in apps. The ability of an app to encourage practice or rehearsal, in addition to daily activities, was the most commonly identified feature across all apps (310/344, 90.1\%), whereas the second most common feature was the ability of the user to easily self-monitor behavior (289/344, 84.0\%). Conclusions: The wide variety of apps included in this 2018 study and the limited number of behavior change techniques found in many apps suggest an opportunity for improvement in app design that will promote sustained and significant lifestyle behavior change and, therefore, better health. The use of the 2 scales for the review and rating of the apps was successful and provided a method that could be replicated and tested in other behavior change areas. ", doi="10.2196/11926", url="https://mhealth.jmir.org/2019/7/e11926/", url="http://www.ncbi.nlm.nih.gov/pubmed/31274112" } @Article{info:doi/10.2196/13641, author="Giebel, Denk Godwin and Gissel, Christian", title="Accuracy of mHealth Devices for Atrial Fibrillation Screening: Systematic Review", journal="JMIR Mhealth Uhealth", year="2019", month="Jun", day="16", volume="7", number="6", pages="e13641", keywords="mHealth", keywords="atrial fibrillation", keywords="wearable", keywords="app", abstract="Background: Mobile health (mHealth) devices can be used for the diagnosis of atrial fibrillation. Early diagnosis allows better treatment and prevention of secondary diseases like stroke. Although there are many different mHealth devices to screen for atrial fibrillation, their accuracy varies due to different technological approaches. Objective: We aimed to systematically review available studies that assessed the accuracy of mHealth devices in screening for atrial fibrillation. The goal of this review was to provide a comprehensive overview of available technologies, specific characteristics, and accuracy of all relevant studies. Methods: PubMed and Web of Science databases were searched from January 2014 until January 2019. Our systematic review was performed according to the Preferred Reporting Items for Systematic Review and Meta-Analyses. We restricted the search by year of publication, language, noninvasive methods, and focus on diagnosis of atrial fibrillation. Articles not including information about the accuracy of devices were excluded. Results: We found 467 relevant studies. After removing duplicates and excluding ineligible records, 22 studies were included. The accuracy of mHealth devices varied among different technologies, their application settings, and study populations. We described and summarized the eligible studies. Conclusions: Our systematic review identifies different technologies for screening for atrial fibrillation with mHealth devices. A specific technology's suitability depends on the underlying form of atrial fibrillation to be diagnosed. With the suitable use of mHealth, early diagnosis and treatment of atrial fibrillation are possible. Successful application of mHealth technologies could contribute to significantly reducing the cost of illness of atrial fibrillation. ", doi="10.2196/13641", url="http://mhealth.jmir.org/2019/6/e13641/", url="http://www.ncbi.nlm.nih.gov/pubmed/31199337" } @Article{info:doi/10.2196/10879, author="Falck, Leandra and Zoller, Marco and Rosemann, Thomas and Mart{\'i}nez-Gonz{\'a}lez, Anani Nahara and Chmiel, Corinne", title="Toward Standardized Monitoring of Patients With Chronic Diseases in Primary Care Using Electronic Medical Records: Systematic Review", journal="JMIR Med Inform", year="2019", month="May", day="24", volume="7", number="2", pages="e10879", keywords="monitoring of chronic diseases", keywords="indicators", keywords="primary care", keywords="systematic review", keywords="electronic medical record", keywords="diabetes mellitus type 2", keywords="arterial hypertension", keywords="asthma", keywords="osteoarthritis", keywords="chronic heart failure", abstract="Background: Long-term care for patients with chronic diseases poses a huge challenge in primary care. In particular, there is a deficit regarding monitoring and structured follow-up. Appropriate electronic medical records (EMRs) could help improving this but, so far, there are no evidence-based specifications concerning the indicators that should be monitored at regular intervals. Objective: The aim was to identify and collect a set of evidence-based indicators that could be used for monitoring chronic conditions at regular intervals in primary care using EMRs. Methods: We searched MEDLINE (Ovid), Embase (Elsevier), the Cochrane Library (Wiley), the reference lists of included studies and relevant reviews, and the content of clinical guidelines. We included primary studies and guidelines reporting about indicators that allow for the assessment of care and help monitor the status and process of disease for five chronic conditions, including type 2 diabetes mellitus, asthma, arterial hypertension, chronic heart failure, and osteoarthritis. Results: The use of the term ``monitoring'' in terms of disease management and long-term care for patients with chronic diseases is not widely used in the literature. Nevertheless, we identified a substantial number of disease-specific indicators that can be used for routine monitoring of chronic diseases in primary care by means of EMRs. Conclusions: To our knowledge, this is the first systematic review summarizing the existing scientific evidence on the standardized long-term monitoring of chronic diseases using EMRs. In a second step, our extensive set of indicators will serve as a generic template for evaluating their usability by means of an adapted Delphi procedure. In a third step, the indicators will be summarized into a user-friendly EMR layout. ", doi="10.2196/10879", url="http://medinform.jmir.org/2019/2/e10879/", url="http://www.ncbi.nlm.nih.gov/pubmed/31127717" } @Article{info:doi/10.2196/11967, author="Romanzini, Possamai Catiana Leila and Romanzini, Marcelo and Batista, Biagi Mariana and Barbosa, Lopes Cynthia Correa and Shigaki, Blasquez Gabriela and Dunton, Genevieve and Mason, Tyler and Ronque, Vaz Enio Ricardo", title="Methodology Used in Ecological Momentary Assessment Studies About Sedentary Behavior in Children, Adolescents, and Adults: Systematic Review Using the Checklist for Reporting Ecological Momentary Assessment Studies", journal="J Med Internet Res", year="2019", month="May", day="15", volume="21", number="5", pages="e11967", keywords="physical activity", keywords="accelerometry", keywords="health behavior", abstract="Background: The use of ecological momentary assessment (EMA) to measure sedentary behavior (SB) in children, adolescents, and adults can increase the understanding of the role of the context of SB in health outcomes. Objective: The aim of this study was to systematically review literature to describe EMA methodology used in studies on SB in youth and adults, verify how many studies adhere to the Methods aspect of the Checklist for Reporting EMA Studies (CREMAS), and detail measures used to assess SB and this associated context. Methods: A systematic literature review was conducted in the PubMed, Scopus, Web of Science, PsycINFO, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and SPORTDiscus databases, covering the entire period of existence of the databases until January 2018. Results: This review presented information about the characteristics and methodology used in 21 articles that utilized EMA to measure SB in youth and adults. There were more studies conducted among youth compared with adults, and studies of youth included more waves and more participants (n=696) than studies with adults (n=97). Most studies (85.7\%) adhered to the Methods aspect of the CREMAS. The main criteria used to measure SB in EMA were self-report (81\%) with only 19\% measuring SB using objective methods (eg, accelerometer). The main equipment to collect objective SB was the ActiGraph, and the cutoff point to define SB was <100 counts/min. Studies most commonly used a 15-min window to compare EMA and accelerometer data. Conclusions: The majority of studies in this review met minimum CREMAS criteria for studies conducted with EMA. Most studies measured SB with EMA self-report (n=17; 81.0\%), and a few studies also used objective methods (n=4; 19\%). The standardization of the 15-min window criteria to compare EMA and accelerometer data would lead to a comparison between these and new studies. New studies using EMA with mobile phones should be conducted as they can be considered an attractive method for capturing information about the specific context of SB activities of young people and adults in real time or very close to it. ", doi="10.2196/11967", url="https://www.jmir.org/2019/5/e11967/", url="http://www.ncbi.nlm.nih.gov/pubmed/31094349" } @Article{info:doi/10.2196/mhealth.8298, author="B{\"o}hm, Birgit and Karwiese, D. Svenja and B{\"o}hm, Harald and Oberhoffer, Renate", title="Effects of Mobile Health Including Wearable Activity Trackers to Increase Physical Activity Outcomes Among Healthy Children and Adolescents: Systematic Review", journal="JMIR Mhealth Uhealth", year="2019", month="Apr", day="30", volume="7", number="4", pages="e8298", keywords="children", keywords="adolescent", keywords="mHealth", keywords="fitness tracker", keywords="physical activity", keywords="physical fitness", abstract="Background: Children and adolescents do not meet the current recommendations on physical activity (PA), and as such, the health-related benefits of regular PA are not achieved. Nowadays, technology-based programs represent an appealing and promising option for children and adolescents to promote PA. Objective: The aim of this review was to systematically evaluate the effects of mobile health (mHealth) and wearable activity trackers on PA-related outcomes in this target group. Methods: Electronic databases such as the Cochrane Central Register of Controlled Trials, PubMed, Scopus, SPORTDiscus, and Web of Science were searched to retrieve English language articles published in peer-reviewed journals from January 2012 to June 2018. Those included were articles that contained descriptions of interventions designed to increase PA among children (aged 6 to 12 years) only, or adolescents (aged 13 to 18 years) only, or articles that include both populations, and also, articles that measured at least 1 PA-related cognitive, psychosocial, or behavioral outcome. The interventions had to be based on mHealth tools (mobile phones, smartphones, tablets, or mobile apps) or wearable activity trackers. Randomized controlled trials (RCTs) and non-RCTs, cohort studies, before-and-after studies, and cross-sectional studies were considered, but only controlled studies with a PA comparison between groups were assessed for methodological quality. Results: In total, 857 articles were identified. Finally, 7 studies (5 with tools of mHealth and 2 with wearable activity trackers) met the inclusion criteria. All studies with tools of mHealth used an RCT design, and 3 were of high methodological quality. Intervention delivery ranged from 4 weeks to 12 months, whereby mainly smartphone apps were used as a tool. Intervention delivery in studies with wearable activity trackers covered a period from 22 sessions during school recess and 8 weeks. Trackers were used as an intervention and evaluation tool. No evidence was found for the effect of mHealth tools, respectively wearable activity trackers, on PA-related outcomes. Conclusions: Given the small number of studies, poor compliance with accelerometers as a measuring instrument for PA, risk of bias, missing RCTs in relation to wearable activity trackers, and the heterogeneity of intervention programs, caution is warranted regarding the comparability of the studies and their effects. There is a clear need for future studies to develop PA interventions grounded on intervention mapping with a high methodological study design for specific target groups to achieve meaningful evidence. ", doi="10.2196/mhealth.8298", url="http://mhealth.jmir.org/2019/4/e8298/", url="http://www.ncbi.nlm.nih.gov/pubmed/31038460" } @Article{info:doi/10.2196/10967, author="Eckert, Martin and Volmerg, S. Julia and Friedrich, M. Christoph", title="Augmented Reality in Medicine: Systematic and Bibliographic Review", journal="JMIR Mhealth Uhealth", year="2019", month="Apr", day="26", volume="7", number="4", pages="e10967", keywords="mixed/augmented reality", keywords="medicine", keywords="mobile computing", keywords="systematic review", keywords="mobile phone", abstract="Background: Augmented reality (AR) is a technology that integrates digital information into the user's real-world environment. It offers a new approach for treatments and education in medicine. AR aids in surgery planning and patient treatment and helps explain complex medical situations to patients and their relatives. Objective: This systematic and bibliographic review offers an overview of the development of apps in AR with a medical use case from March 2012 to June 2017. This work can aid as a guide to the literature and categorizes the publications in the field of AR research. Methods: From March 2012 to June 2017, a total of 1309 publications from PubMed and Scopus databases were manually analyzed and categorized based on a predefined taxonomy. Of the total, 340 duplicates were removed and 631 publications were excluded due to incorrect classification or unavailable technical data. The remaining 338 publications were original research studies on AR. An assessment of the maturity of the projects was conducted on these publications by using the technology readiness level. To provide a comprehensive process of inclusion and exclusion, the authors adopted the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Results: The results showed an increasing trend in the number of publications on AR in medicine. There were no relevant clinical trials on the effect of AR in medicine. Domains that used display technologies seemed to be researched more than other medical fields. The technology readiness level showed that AR technology is following a rough bell curve from levels 4 to 7. Current AR technology is more often applied to treatment scenarios than training scenarios. Conclusions: This work discusses the applicability and future development of augmented- and mixed-reality technologies such as wearable computers and AR devices. It offers an overview of current technology and a base for researchers interested in developing AR apps in medicine. The field of AR is well researched, and there is a positive trend in its application, but its use is still in the early stages in the field of medicine and it is not widely adopted in clinical practice. Clinical studies proving the effectiveness of applied AR technologies are still lacking. ", doi="10.2196/10967", url="http://mhealth.jmir.org/2019/4/e10967/", url="http://www.ncbi.nlm.nih.gov/pubmed/31025950" } @Article{info:doi/10.2196/13250, author="Ali, H. Shahmir and Luo, Rong and Li, Yuan and Liu, Xiangjun and Tang, Chengyao and Zhang, Puhong", title="Application of Mobile Health Technologies Aimed at Salt Reduction: Systematic Review", journal="JMIR Mhealth Uhealth", year="2019", month="Apr", day="17", volume="7", number="4", pages="e13250", keywords="mobile health", keywords="sodium", keywords="diet", keywords="cardiovascular diseases", keywords="systematic review", abstract="Background: High salt consumption has contributed to the rise of noncommunicable diseases around the world. The application of mobile health (mHealth) technologies has witnessed rapid growth in recent years. However, evidence to support mHealth interventions to confront the challenge of salt reduction has not yet been critically reviewed. Objective: The aim of this study was to identify, characterize, and evaluate mHealth interventions aimed at salt reduction across the world. Methods: A systematic search of studies in English or Chinese language published from January 1, 1992 to July 31, 2017 was conducted using 4 English databases (PubMed, MEDLINE, Global Health, and Cochrane) and 3 Chinese databases (Wanfang, China Science and Technology Journal, and China National Knowledge of Infrastructure). All studies directly using mobile technologies in health care with a primary or secondary objective of reducing dietary salt consumption were included. Results: A total of 1609 articles were found using the search strategy, with 11 full articles (8 English and 3 Chinese) being included for data extraction, including 11 interventional studies. Overall, few high-quality interventions were identified. Most interventions were limited by small study population sample sizes, lack of control groups, and short follow-up times, all of which were obstacles in generating long-term scalable approaches. Most interventions employed short message service as a platform for mHealth interventions, whereas some innovative mHealth technologies were also explored. Most interventions had a primary focus of improving awareness of dietary salt consumption. The outcome variables used to measure intervention effectiveness included 24-hour urinary sodium excretion, spot urine sampling, dietary records, and indirect behavior or knowledge indicators targeting salt consumption. Although most interventions displayed positive outcome results, none of them provided reliable evidence to evaluate the effectiveness of salt reduction. Conclusions: Salt reduction in mHealth initiatives remains relatively unexplored; however, studies that did intervene on salt-reduction show the potential of mHealth as an effective intervention method. We provide 3 recommendations for future mHealth interventions in salt reduction---(1) increased use of new, innovative, and interactive mHealth technologies; (2) development of mHealth interventions with primary prevention measures and goals of salt reduction; and (3) large-scale, rigorously designed, and object-targeted clinical trials of mHealth interventions with appropriate quantitative outcome variables, in particular 24-hour urine sodium. ", doi="10.2196/13250", url="http://mhealth.jmir.org/2019/4/e13250/", url="http://www.ncbi.nlm.nih.gov/pubmed/30994467" } @Article{info:doi/10.2196/11244, author="Yang, Qinghua and Van Stee, K. Stephanie", title="The Comparative Effectiveness of Mobile Phone Interventions in Improving Health Outcomes: Meta-Analytic Review", journal="JMIR Mhealth Uhealth", year="2019", month="Apr", day="03", volume="7", number="4", pages="e11244", keywords="meta-analysis", keywords="mobile phones", keywords="mHealth", keywords="intervention study", abstract="Background: As mobile technology continues expanding, researchers have been using mobile phones to conduct health interventions (mobile health---mHealth---interventions). The multiple features of mobile phones offer great opportunities to disseminate large-scale, cost-efficient, and tailored messages to participants. However, the interventions to date have shown mixed results, with a large variance of effect sizes (Cohen d=?0.62 to 1.65). Objective: The study aimed to generate cumulative knowledge that informs mHealth intervention research. The aims were twofold: (1) to calculate an overall effect magnitude for mHealth interventions compared with alternative interventions or conditions, and (2) to analyze potential moderators of mHealth interventions' comparative efficacy. Methods: Comprehensive searches of the Communication \& Mass Media Complete, PsycINFO, Web of Knowledge, Academic Search Premier, PubMed and MEDLINE databases were conducted to identify potentially eligible studies in peer-reviewed journals, conference proceedings, and dissertations and theses. Search queries were formulated using a combination of search terms: ``intervention'' (Title or Abstract) AND ``health'' (Title or Abstract) AND ``*phone*'' OR ``black-berr*'' (OR mHealth OR ``application*'' OR app* OR mobile OR cellular OR ``short messag*'' OR palm* OR iPhone* OR MP3* OR MP4* OR iPod*) (Title or Abstract). Cohen d was computed as the basic unit of analysis, and the variance-weighted analysis was implemented to compute the overall effect size under a random-effects model. Analysis of variance--like and meta-regression models were conducted to analyze categorical and continuous moderators, respectively. Results: The search resulted in 3424 potential studies, the abstracts (and full text, as necessary) of which were reviewed for relevance. Studies were screened in multiple stages using explicit inclusion and exclusion criteria, and citations were evaluated for inclusion of qualified studies. A total of 64 studies were included in the current meta-analysis. Results showed that mHealth interventions are relatively more effective than comparison interventions or conditions, with a small but significant overall weighted effect size (Cohen d=0.31). In addition, the effects of interventions are moderated by theoretical paradigm, 3 engagement types (ie, changing personal environment, reinforcement tracking, social presentation), mobile use type, intervention channel, and length of follow-up. Conclusions: To the best of our knowledge, this is the most comprehensive meta-analysis to date that examined the overall effectiveness of mHealth interventions across health topics and is the first study that statistically tested moderators. Our findings not only shed light on intervention design using mobile phones, but also provide new directions for research in health communication and promotion using new media. Future research scholarship is needed to examine the effectiveness of mHealth interventions across various health issues, especially those that have not yet been investigated (eg, substance use, sexual health), engaging participants using social features on mobile phones, and designing tailored mHealth interventions for diverse subpopulations to maximize effects. ", doi="10.2196/11244", url="https://mhealth.jmir.org/2019/4/e11244/", url="http://www.ncbi.nlm.nih.gov/pubmed/30942695" } @Article{info:doi/10.2196/11215, author="Yang, Sook Yong and Ryu, Wook Gi and Choi, Mona", title="Methodological Strategies for Ecological Momentary Assessment to Evaluate Mood and Stress in Adult Patients Using Mobile Phones: Systematic Review", journal="JMIR Mhealth Uhealth", year="2019", month="Apr", day="01", volume="7", number="4", pages="e11215", keywords="review", keywords="experience sampling method", keywords="ecological momentary assessment", keywords="mobile apps", keywords="mood", keywords="stress", abstract="Background: Ecological momentary assessment (EMA) has utility for measuring psychological properties in daily life. EMA has also allowed researchers to collect data on diverse experiences and symptoms from various subjects. Objective: The aim of this study was to review methodological strategies and useful related information for EMA using mobile phones to capture changes of mood and stress in adult patients seeking health care. Methods: We searched PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase, the Cochrane Library, PsycINFO, and Web of Science. This review included studies published in peer-reviewed journals in English between January 2008 and November 2017 that used basic- or advanced-feature mobile phones to measure momentary mood or stress in adult patients seeking health care in outpatient departments. We excluded studies of smoking and substance addictions and studies of mental disorder patients who had been diagnosed by physicians. Results: We reviewed 12 selected articles that used EMA via mobile phones to measure momentary mood and stress and other related variables from various patients with chronic fatigue syndrome, breast cancer, migraine, HIV, tinnitus, temporomandibular disorder, end-stage kidney disease, and traumatic brain injury. Most of the selected studies (11/12, 92\%) used signal contingency and in 8 of the 12 studies (67\%) alarms were sent at random or semirandom intervals to prompt the momentary measurement. Out of 12 studies, 7 (58\%) used specific apps directly installed on mobile phones, 3 (25\%) used mobile phones to link to Web-based survey programs, and 2 (17\%) used an interactive voice-response system. Conclusions: This study provides researchers with useful information regarding methodological details for utilizing EMA to measure mood and stress in adult patients. This review shows that EMA methods could be effective and reasonable for measuring momentary mood and stress, given that basic- and advanced-feature mobile phones are ubiquitous, familiar, and easy to approach. Therefore, researchers could adopt and utilize EMA methods using mobile phones to measure psychological health outcomes, such as mood and stress, in adult patients. ", doi="10.2196/11215", url="https://mhealth.jmir.org/2019/4/e11215/", url="http://www.ncbi.nlm.nih.gov/pubmed/30932866" } @Article{info:doi/10.2196/12191, author="Ricci-Cabello, Ignacio and Bobrow, Kirsten and Islam, Shariful Sheikh Mohammed and Chow, K. Clara and Maddison, Ralph and Whittaker, Robyn and Farmer, J. Andrew", title="Examining Development Processes for Text Messaging Interventions to Prevent Cardiovascular Disease: Systematic Literature Review", journal="JMIR Mhealth Uhealth", year="2019", month="Mar", day="29", volume="7", number="3", pages="e12191", keywords="systematic review", keywords="cardiovascular disease", keywords="telemedicine", keywords="text messaging", keywords="methods", abstract="Background: Interventions delivered by mobile phones have the potential to prevent cardiovascular disease (CVD) by supporting behavior change toward healthier lifestyles and treatment adherence. To allow replication and adaptation of these interventions across settings, it is important to fully understand how they have been developed. However, the development processes of these interventions have not previously been systematically examined. Objective: This study aimed to systematically describe and compare the development process of text messaging interventions identified in the Text2PreventCVD systematic review. Methods: We extracted data about the development process of the 9 interventions identified in the Text2PreventCVD systematic review. Data extraction, which was guided by frameworks for the development of complex interventions, considered the following development stages: intervention planning, design, development, and pretesting. Following data extraction, we invited the developers of the interventions to contribute to our study by reviewing the accuracy of the extracted data and providing additional data not reported in the available publications. Results: A comprehensive description of the development process was available for 5 interventions. Multiple methodologies were used for the development of each intervention. Intervention planning involved gathering information from stakeholder consultations, literature reviews, examination of relevant theory, and preliminary qualitative research. Intervention design involved the use of behavior change theories and behavior change techniques. Intervention development involved (1) generating message content based on clinical guidelines and expert opinions; (2) conducting literature reviews and primary qualitative research to inform decisions about message frequency, timing, and level of tailoring; and (3) gathering end-user feedback concerning message readability, intervention acceptability, and perceived utility. Intervention pretesting involved pilot studies with samples of 10 to 30 participants receiving messages for a period ranging from 1 to 4 weeks. Conclusions: The development process of the text messaging interventions examined was complex and comprehensive, involving multiple studies to guide decisions about the scope, content, and structure of the interventions. Additional research is needed to establish whether effective messaging systems can be adapted from work already done or whether this level of development is needed for application in other conditions and settings. ", doi="10.2196/12191", url="http://mhealth.jmir.org/2019/3/e12191/", url="http://www.ncbi.nlm.nih.gov/pubmed/30924790" } @Article{info:doi/10.2196/10855, author="Vergani, Laura and Marton, Giulia and Pizzoli, Maria Silvia Francesca and Monzani, Dario and Mazzocco, Ketti and Pravettoni, Gabriella", title="Training Cognitive Functions Using Mobile Apps in Breast Cancer Patients: Systematic Review", journal="JMIR Mhealth Uhealth", year="2019", month="Mar", day="19", volume="7", number="3", pages="e10855", keywords="cognitive impairment", keywords="breast cancer", keywords="cognitive training", keywords="intervention", keywords="mobile-based interventions", abstract="Background: Breast cancer is an invalidating disease and its treatment can bring serious side effects that have a physical and psychological impact. Specifically, cancer treatment generally has a strong impact on cognitive function. In recent years, new technologies and eHealth have had a growing influence on health care and innovative mobile apps can be useful tools to deliver cognitive exercise in the patient's home. Objective: This systematic review gives an overview of the state-of-the-art mobile apps aimed at training cognitive functions to better understand whether these apps could be useful tools to counteract cognitive impairment in breast cancer patients. Methods: We searched in a systematic way all the full-text articles from the PubMed and Embase databases. Results: We found eleven studies using mobile apps to deliver cognitive training. They included a total of 819 participants. App and study characteristics are presented and discussed, including cognitive domains trained (attention, problem solving, memory, cognitive control, executive function, visuospatial function, and language). None of the apps were specifically developed for breast cancer patients. They were generally developed for a specific clinical population. Only 2 apps deal with more than 1 cognitive domain, and only 3 studies focus on the efficacy of the app training intervention. Conclusions: These results highlight the lack of empirical evidence on the efficacy of currently available apps to train cognitive function. Cognitive domains are not well defined across studies. It is noteworthy that no apps are specifically developed for cancer patients, and their applicability to breast cancer should not be taken for granted. Future studies should test the feasibility, usability, and effectiveness of available cognitive training apps in women with breast cancer. Due to the complexity and multidimensionality of cognitive difficulties in this cancer population, it may be useful to design, develop, and implement an ad hoc app targeting cognitive impairment in breast cancer patients. ", doi="10.2196/10855", url="https://mhealth.jmir.org/2019/3/e10855/", url="http://www.ncbi.nlm.nih.gov/pubmed/30888326" } @Article{info:doi/10.2196/12385, author="Lee, Seohyun and Lee, Youngji and Lee, Sangmi and Islam, Shariful Sheikh Mohammed and Kim, Sun-Young", title="Toward Developing a Standardized Core Set of Outcome Measures in Mobile Health Interventions for Tuberculosis Management: Systematic Review", journal="JMIR Mhealth Uhealth", year="2019", month="Feb", day="19", volume="7", number="2", pages="e12385", keywords="mHealth", keywords="tuberculosis", keywords="outcome measures", keywords="evidence synthesis", keywords="low-and middle-income countries", abstract="Background: Tuberculosis (TB) management can be challenging in low- and middle-income countries (LMICs) not only because of its high burden but also the prolonged treatment period involving multiple drugs. With rapid development in mobile technology, mobile health (mHealth) interventions or using a mobile device for TB management has gained popularity. Despite the potential usefulness of mHealth interventions for TB, few studies have quantitatively synthesized evidence on its effectiveness, presumably because of variability in outcome measures reported in the literature. Objective: The aim of this systematic review was to evaluate the outcome measures reported in TB mHealth literature in LMICs. Methods: MEDLINE, EMBASE, and the Cochrane Database of Systematic Reviews were searched to identify mHealth intervention studies for TB (published up to May 2018) that reported any type of outcome measures. The extracted information included the study setting, types of mHealth technology used, target population, study design, and categories of outcome measures. Outcomes were classified into 13 categories including treatment outcome, adherence, process measure, perception, technical outcome, and so on. The qualitative synthesis of evidence focused on the categories of outcome measures reported by the type of mHealth interventions. Results: A total of 27 studies were included for the qualitative synthesis of evidence. The study designs varied widely, ranging from randomized controlled trials to economic evaluations. A total of 12 studies adopted short message service (SMS), whereas 5 studies used SMS in combination with additional technologies or mobile apps. The study populations were also diverse, including patients with TB, patients with TB/HIV, health care workers, and general patients attending a clinic. There was a wide range of variations in the definition of outcome measures across the studies. Among the diverse categories of outcome measures, treatment outcomes have been reported in 14 studies, but only 6 of them measured the outcome according to the standard TB treatment definitions by the World Health Organization. Conclusions: This critical evaluation of outcomes reported in mHealth studies for TB management suggests that substantial variability exists in reporting outcome measures. To overcome the challenges in evidence synthesis for mHealth interventions, this study can provide insights into the development of a core set of outcome measures by intervention type and study design. ", doi="10.2196/12385", url="http://mhealth.jmir.org/2019/2/e12385/", url="http://www.ncbi.nlm.nih.gov/pubmed/30777847" } @Article{info:doi/10.2196/11606, author="Li, Christien Ka Hou and White, Anne Francesca and Tipoe, Timothy and Liu, Tong and Wong, CS Martin and Jesuthasan, Aaron and Baranchuk, Adrian and Tse, Gary and Yan, P. Bryan", title="The Current State of Mobile Phone Apps for Monitoring Heart Rate, Heart Rate Variability, and Atrial Fibrillation: Narrative Review", journal="JMIR Mhealth Uhealth", year="2019", month="Feb", day="15", volume="7", number="2", pages="e11606", keywords="mobile phone apps", keywords="atrial fibrillation", keywords="heart rate", keywords="arrhythmia", keywords="photoplethysmography", keywords="electrocardiography", keywords="mobile health", abstract="Background: Mobile phone apps capable of monitoring arrhythmias and heart rate (HR) are increasingly used for screening, diagnosis, and monitoring of HR and rhythm disorders such as atrial fibrillation (AF). These apps involve either the use of (1) photoplethysmographic recording or (2) a handheld external electrocardiographic recording device attached to the mobile phone or wristband. Objective: This review seeks to explore the current state of mobile phone apps in cardiac rhythmology while highlighting shortcomings for further research. Methods: We conducted a narrative review of the use of mobile phone devices by searching PubMed and EMBASE from their inception to October 2018. Potentially relevant papers were then compared against a checklist for relevance and reviewed independently for inclusion, with focus on 4 allocated topics of (1) mobile phone monitoring, (2) AF, (3) HR, and (4) HR variability (HRV). Results: The findings of this narrative review suggest that there is a role for mobile phone apps in the diagnosis, monitoring, and screening for arrhythmias and HR. Photoplethysmography and handheld electrocardiograph recorders are the 2 main techniques adopted in monitoring HR, HRV, and AF. Conclusions: A number of studies have demonstrated high accuracy of a number of different mobile devices for the detection of AF. However, further studies are warranted to validate their use for large scale AF screening. ", doi="10.2196/11606", url="http://mhealth.jmir.org/2019/2/e11606/", url="http://www.ncbi.nlm.nih.gov/pubmed/30767904" } @Article{info:doi/10.2196/13080, author="Devan, Hemakumar and Farmery, Devin and Peebles, Lucy and Grainger, Rebecca", title="Evaluation of Self-Management Support Functions in Apps for People With Persistent Pain: Systematic Review", journal="JMIR Mhealth Uhealth", year="2019", month="Feb", day="12", volume="7", number="2", pages="e13080", keywords="smartphone", keywords="chronic pain", keywords="culture", keywords="mHealth", keywords="self-management", keywords="technology", abstract="Background: Smartphone apps are a potential mechanism for development of self-management skills in people with persistent pain. However, the inclusion of best-practice content items in available pain management apps fostering core self-management skills for self-management support is not known. Objective: The aim of the study was to evaluate the contents of smartphone apps providing information on pain management strategies for people with persistent pain facilitating self-management support and to appraise the app quality. Methods: A systematic search was performed in the New Zealand App Store and Google Play Store. Apps were included if they were designed for people with persistent pain, provided information on pain self-management strategies, and were available in English. App contents were evaluated using an a priori 14-item self-management support (SMS-14) checklist. App quality was assessed using the 23-item Mobile Apps Rating Scale. Results: Of the 939 apps screened, 19 apps met the inclusion criteria. Meditation and guided relaxation were the most frequently included self-management strategies. Overall, the included apps met a median of 4 (range 1-8) of the SMS-14 checklist. A total of 3 apps (Curable, PainScale-Pain Diary and Coach, and SuperBetter) met the largest number of items (8 out of 14) to foster self-management of pain. Self-monitoring of symptoms (n=11) and self-tailoring of strategies (n=9) were frequently featured functions, whereas a few apps had features facilitating social support and enabling communicating with clinicians. No apps provided information tailored to the cultural needs of the user. The app quality mean scores using Mobile Apps Rating Scale ranged from 2.7 to 4.5 (out of 5.0). Although use of 2 apps (Headspace and SuperBetter) has been shown to improve health outcomes, none of the included apps have been evaluated in people with persistent pain. Conclusions: Of the 3 apps (Curable, PainScale-Pain Diary and Coach, and SuperBetter) that met the largest number of items to support skills in self-management of pain, 2 apps (PainScale-Pain Diary and Coach and SuperBetter) were free, suggesting the potential for using apps as a scalable, wide-reaching intervention to complement face-to-face care. However, none provided culturally tailored information. Although 2 apps (Headspace and SuperBetter) were validated to show improved health outcomes, none were tested in people with persistent pain. Both users and clinicians should be aware of such limitations and make informed choices in using or recommending apps as a self-management tool. For better integration of apps in clinical practice, concerted efforts are required among app developers, clinicians, and people with persistent pain in developing apps and evaluating for clinical efficacy. ", doi="10.2196/13080", url="http://mhealth.jmir.org/2019/2/e13080/", url="http://www.ncbi.nlm.nih.gov/pubmed/30747715" } @Article{info:doi/10.2196/12281, author="Kiss, Nicole and Baguley, James Brenton and Ball, Kylie and Daly, M. Robin and Fraser, F. Steve and Granger, L. Catherine and Ugalde, Anna", title="Technology-Supported Self-Guided Nutrition and Physical Activity Interventions for Adults With Cancer: Systematic Review", journal="JMIR Mhealth Uhealth", year="2019", month="Feb", day="12", volume="7", number="2", pages="e12281", keywords="cancer", keywords="diet", keywords="exercise", keywords="nutrition", keywords="physical activity", keywords="self-guided interventions", keywords="technology", abstract="Background: Nutrition and physical activity interventions are important components of cancer care. With an increasing demand for services, there is a need to consider flexible, easily accessible, and tailored models of care while maintaining optimal outcomes. Objective: This systematic review describes and appraises the efficacy of technology-supported self-guided nutrition and physical activity interventions for people with cancer. Methods: A systematic search of multiple databases from 1973 to July 2018 was conducted for randomized and nonrandomized trials investigating technology-supported self-guided nutrition and physical activity interventions. Risk of bias was assessed using the Cochrane Risk of Bias tool. Outcomes included behavioural, health-related, clinical, health service, or financial measures. Results: Sixteen randomized controlled trials representing 2684 participants were included. Most studies were web-based interventions (n=9) and had a 12-week follow-up duration (n=8). Seven studies assessed dietary behaviour, of which two reported a significant benefit on diet quality or fruit and vegetable intake. Fifteen studies measured physical activity behaviour, of which eight studies reported a significant improvement in muscle strength and moderate-to-vigorous physical activity. Four of the nine studies assessing the health-related quality of life (HRQoL) reported a significant improvement in global HRQoL or a domain subscale. A significant improvement in fatigue was found in four of six studies. Interpretation of findings was influenced by inadequate reporting of intervention description and compliance. Conclusions: This review identified short-term benefits of technology-supported self-guided interventions on the physical activity level and fatigue and some benefit on dietary behaviour and HRQoL in people with cancer. However, current literature demonstrates a lack of evidence for long-term benefit. Trial Registration: PROSPERO CRD42017080346; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=80346 ", doi="10.2196/12281", url="http://mhealth.jmir.org/2019/2/e12281/", url="http://www.ncbi.nlm.nih.gov/pubmed/30747720" } @Article{info:doi/10.2196/11847, author="Lee, M. Alexandra and Chavez, Sarah and Bian, Jiang and Thompson, A. Lindsay and Gurka, J. Matthew and Williamson, G. Victoria and Modave, Fran{\c{c}}ois", title="Efficacy and Effectiveness of Mobile Health Technologies for Facilitating Physical Activity in Adolescents: Scoping Review", journal="JMIR Mhealth Uhealth", year="2019", month="Feb", day="12", volume="7", number="2", pages="e11847", keywords="review", keywords="mobile health", keywords="adolescent", keywords="exercise", abstract="Background: Increasing physical activity (PA) levels in adolescents aged 12 to 18 years is associated with prevention of unhealthy weight gain and improvement in cardiovascular fitness. The widespread availability of mobile health (mHealth) and wearable devices offers self-monitoring and motivational features for increasing PA levels and improving adherence to exercise programs. Objective: The aim of this scoping review was to identify the efficacy or effectiveness of mHealth intervention strategies for facilitating PA among adolescents aged 12 to 18 years. Methods: We conducted a systematic search for peer-reviewed studies published between 2008 and 2018 in the following electronic databases: PubMed, Google Scholar, PsychINFO, or SportDiscus. The search terms used included mHealth or ``mobile health'' or apps, ``physical activity'' or exercise, children or adolescents or teens or ``young adults'' or kids, and efficacy or effectiveness. Articles published outside of the date range (July 2008 to October 2018) and non-English articles were removed before abstract review. Three reviewers assessed all abstracts against the inclusion and exclusion criteria. Any uncertainties or differences in opinion were discussed as a group. The inclusion criteria were that the studies should (1) have an mHealth component, (2) target participants aged between 12 and 18 years, (3) have results on efficacy or effectiveness, and (4) assess PA-related outcomes. Reviews, abstracts only, protocols without results, and short message service text messaging--only interventions were excluded. We also extracted potentially relevant papers from reviews. At least 2 reviewers examined all full articles for fit with the criteria and extracted data for analysis. Data extracted from selected studies included study population, study type, components of PA intervention, and PA outcome results. Results: Overall, 126 articles were initially identified. Reviewers pulled 18 additional articles from excluded review papers. Only 18 articles were passed onto full review, and 16 were kept for analysis. The included studies differed in the sizes of the study populations (11-607 participants), locations of the study sites (7 countries), study setting, and study design. Overall, 5 mHealth intervention categories were identified: website, website+wearable, app, wearable+app, and website+wearable+app. The most common measures reported were subjective weekly PA (4/13) and objective daily moderate-to-vigorous PA (5/13) of the 19 different PA outcomes assessed. Furthermore, 5 of 13 studies with a control or comparison group showed a significant improvement in PA outcomes between the intervention group and the control or comparison group. Of those 5 studies, 3 permitted isolation of mHealth intervention components in the analysis. Conclusions: PA outcomes for adolescents improved over time through mHealth intervention use; however, the lack of consistency in chosen PA outcome measures, paucity of significant outcomes via between-group analyses, and the various study designs that prevent separating the effects of intervention components calls into question their true effect. ", doi="10.2196/11847", url="http://mhealth.jmir.org/2019/2/e11847/", url="http://www.ncbi.nlm.nih.gov/pubmed/30747716" } @Article{info:doi/10.2196/11836, author="Chan, Ling Ko and Chen, Mengtong", title="Effects of Social Media and Mobile Health Apps on Pregnancy Care: Meta-Analysis", journal="JMIR Mhealth Uhealth", year="2019", month="Jan", day="30", volume="7", number="1", pages="e11836", keywords="mHealth", keywords="social media", keywords="pregnancy", keywords="postpartum", keywords="maternal health", abstract="Background: The use of social media and mobile health (mHealth) apps has been increasing in pregnancy care. However, the effectiveness of these interventions is still unclear. Objectives: We conducted a meta-analysis to examine the effectiveness of these interventions with regard to different health outcomes in pregnant and postpartum women and investigate the characteristics and components of interventions that may affect program effectiveness. Method: We performed a comprehensive literature search of major electronic databases and reference sections of related reviews and eligible studies. A random effects model was used to calculate the effect size. Results: Fifteen randomized controlled trial studies published in and before June 2018 that met the inclusion criteria were included in the meta-analysis. The interventions were effective in promoting maternal physical health including weight management, gestational diabetes mellitus control, and asthma control with a moderate to large effect size (d=0.72). Large effect sizes were also found for improving maternal mental health (d=0.84) and knowledge about pregnancy (d=0.80). Weight control interventions using wearable devices were more effective. Conclusion: Social media and mHealth apps have the potential to be widely used in improving maternal well-being. More large-scale clinical trials focusing on different health outcomes are suggested for future studies. ", doi="10.2196/11836", url="https://mhealth.jmir.org/2019/1/e11836/", url="http://www.ncbi.nlm.nih.gov/pubmed/30698533" } @Article{info:doi/10.2196/10899, author="Song, Ting and Qian, Siyu and Yu, Ping", title="Mobile Health Interventions for Self-Control of Unhealthy Alcohol Use: Systematic Review", journal="JMIR Mhealth Uhealth", year="2019", month="Jan", day="29", volume="7", number="1", pages="e10899", keywords="systematic review", keywords="alcohol drinking", keywords="self-control", keywords="mobile health", keywords="mHealth", keywords="treatment outcome", abstract="Background: Unhealthy alcohol use (UAU) is one of the major causes of preventable morbidity, mortality, and associated behavioral risks worldwide. Although mobile health (mHealth) interventions can provide consumers with an effective means for self-control of UAU in a timely, ubiquitous, and cost-effective manner, to date, there is a lack of understanding about different health outcomes brought by such interventions. The core components of these interventions are also unclear. Objective: This study aimed to systematically review and synthesize the research evidence about the efficacy of mHealth interventions on various health outcomes for consumer self-control of UAU and to identify the core components to achieve these outcomes. Methods: We systematically searched 7 electronic interdisciplinary databases: Scopus, PubMed, PubMed Central, CINAHL Plus with full text, MEDLINE with full text, PsycINFO, and PsycARTICLES. Search terms and Medical Subject Headings ``mHealth,'' ``text message,'' ``SMS,'' ``App,'' ``IVR,'' ``self-control,'' ``self-regulation,'' ``alcohol*,'' and ``intervention'' were used individually or in combination to identify peer-reviewed publications in English from 2008 to 2017. We screened titles and abstracts and assessed full-text papers as per inclusion and exclusion criteria. Data were extracted from the included papers according to the Consolidated Standards of Reporting Trials-EHEALTH checklist (V 1.6.1) by 2 authors independently. Data quality was assessed by the Mixed Methods Appraisal Tool. Data synthesis and analyses were conducted following the procedures for qualitative content analysis. Statistical testing was also conducted to test differences among groups of studies. Results: In total, 19 studies were included in the review. Of these 19 studies, 12 (63\%) mHealth interventions brought significant positive outcomes in improving participants' health as measured by behavioral (n=11), physiological (n=1), and cognitive indicators (n=1). No significant health outcome was reported in 6 studies (6/19, 32\%). Surprisingly, a significant negative outcome was reported for the male participants in the intervention arm in 1 study (1/19, 5\%), but no change was found for the female participants. In total, 5 core components reported in the mHealth interventions for consumer self-control of UAU were context, theoretical base, delivery mode, content, and implementation procedure. However, sound evidence is yet to be generated about the role of each component for mHealth success. The health outcomes were similar regardless of types of UAU, deployment setting, with or without nonmobile cointervention, and with or without theory. Conclusions: Most studies reported mHealth interventions for self-control of UAU appeared to be improving behavior, especially the ones delivered by short message service and interactive voice response systems. Further studies are needed to gather sound evidence about the effects of mHealth interventions on improving physiological and cognitive outcomes as well as the optimal design of these interventions, their implementation, and effects in supporting self-control of UAU. ", doi="10.2196/10899", url="http://mhealth.jmir.org/2019/1/e10899/", url="http://www.ncbi.nlm.nih.gov/pubmed/30694200" } @Article{info:doi/10.2196/11942, author="Sezgin, Emre and Lin, Simon", title="Technology-Based Interventions, Assessments, and Solutions for Safe Driving Training for Adolescents: Rapid Review", journal="JMIR Mhealth Uhealth", year="2019", month="Jan", day="24", volume="7", number="1", pages="e11942", keywords="adolescent health", keywords="assessment", keywords="driving safety", keywords="teen driving", keywords="technology-based intervention", abstract="Background: Safe driving training for adolescents aims to prevent injury and promote their well-being. In that regard, information and communication technologies have been used to understand adolescent driving behavior and develop interventions. Objective: The purpose of this review is to explore and discuss existing approaches to technology-based driving interventions, driving assessments, and solutions in the literature. Methods: We searched the Web of Science and PubMed databases following a review protocol to collect relevant peer-reviewed journal articles. Inclusion criteria were (1) being published in the English language, (2) being published in a peer-reviewed journal, (3) testing the driving behavior of teens with technology-based intervention methods, and (4) being published between January 2000 and March 2018. We appraised the articles by reading their abstracts to select studies matching the inclusion criteria and reading the full text of articles for final refinement. Results: Initial keyword searches on technology-based solutions resulted in 828 publications that we refined further by title screening (n=131) and abstract evaluation against inclusion criteria (n=29). Finally, we selected 16 articles that met the inclusion criteria and examined them regarding the use of technology-based interventions, assessments, and solutions. Use of built-in tracking devices and installation of black box devices were widely used methods for capturing driving events. Smartphones were increasingly adapted for data collection, and use of gamification for intervention design was an emerging concept. Visual and audio feedback also were used for intervention. Conclusions: Our findings suggest that social influence is effective in technology-based interventions; parental involvement for promoting safe driving behavior is highly effective. However, the use of smartphones and gamification needs more study regarding their implementation and sustainability. Further developments in technology for predicting teen behavior and programs for behavioral change are needed. ", doi="10.2196/11942", url="http://mhealth.jmir.org/2019/1/e11942/", url="http://www.ncbi.nlm.nih.gov/pubmed/30679149" } @Article{info:doi/10.2196/11312, author="Kankanhalli, Atreyi and Shin, Jieun and Oh, Hyelim", title="Mobile-Based Interventions for Dietary Behavior Change and Health Outcomes: Scoping Review", journal="JMIR Mhealth Uhealth", year="2019", month="Jan", day="21", volume="7", number="1", pages="e11312", keywords="mHealth", keywords="mobile-based intervention", keywords="dietary behavior", keywords="food intake", keywords="behavior change", keywords="health outcomes", abstract="Background: Mobile apps are being widely used for delivering health interventions, with their ubiquitous access and sensing capabilities. One such use is the delivery of interventions for healthy eating behavior. Objective: The aim of this study was to provide a comprehensive view of the literature on the use of mobile interventions for eating behavior change. We synthesized the studies with such interventions and mapped out their input methods, interventions, and outcomes. Methods: We conducted a scoping literature search in PubMed/MEDLINE, Association for Computing Machinery Digital Library, and PsycINFO databases to identify relevant papers published between January 2013 and April 2018. We also hand-searched relevant themes of journals in the Journal of Medical Internet Research and registered protocols. Studies were included if they provided and assessed mobile-based interventions for dietary behavior changes and/or health outcomes. Results: The search resulted in 30 studies that we classified by 3 main aspects: input methods, mobile-based interventions, and dietary behavior changes and health outcomes. First, regarding input methods, 5 studies allowed photo/voice/video inputs of diet information, whereas text input methods were used in the remaining studies. Other than diet information, the content of the input data in the mobile apps included user's demographics, medication, health behaviors, and goals. Second, we identified 6 categories of intervention contents, that is, self-monitoring, feedback, gamification, goal reviews, social support, and educational information. Although all 30 studies included self-monitoring as a key component of their intervention, personalized feedback was a component in 18 studies, gamification was used in 10 studies, goal reviews in 5 studies, social support in 3 studies, and educational information in 2 studies. Finally, we found that 13 studies directly examined the effects of interventions on health outcomes and 12 studies examined the effects on dietary behavior changes, whereas only 5 studies observed the effects both on dietary behavior changes and health outcomes. Regarding the type of studies, although two-thirds of the included studies conducted diverse forms of randomized control trials, the other 10 studies used field studies, surveys, protocols, qualitative interviews, propensity score matching method, and test and reference method. Conclusions: This scoping review identified and classified studies on mobile-based interventions for dietary behavior change as per the input methods, nature of intervention, and outcomes examined. Our findings indicated that dietary behavior changes, although playing a mediating role in improving health outcomes, have not been adequately examined in the literature. Dietary behavior change as a mechanism for the relationship between mobile-based intervention and health outcomes needs to be further investigated. Our review provides guidance for future research in this promising mobile health area. ", doi="10.2196/11312", url="http://mhealth.jmir.org/2019/1/e11312/", url="http://www.ncbi.nlm.nih.gov/pubmed/30664461" } @Article{info:doi/10.2196/11941, author="Pham, Quynh and Graham, Gary and Carrion, Carme and Morita, P. Plinio and Seto, Emily and Stinson, N. Jennifer and Cafazzo, A. Joseph", title="A Library of Analytic Indicators to Evaluate Effective Engagement with Consumer mHealth Apps for Chronic Conditions: Scoping Review", journal="JMIR Mhealth Uhealth", year="2019", month="Jan", day="18", volume="7", number="1", pages="e11941", keywords="analytics", keywords="effective engagement", keywords="engagement", keywords="adherence", keywords="log data", keywords="mobile health", keywords="mobile applications", keywords="chronic disease", keywords="scoping review", abstract="Background: There is mixed evidence to support current ambitions for mobile health (mHealth) apps to improve chronic health and well-being. One proposed explanation for this variable effect is that users do not engage with apps as intended. The application of analytics, defined as the use of data to generate new insights, is an emerging approach to study and interpret engagement with mHealth interventions. Objective: This study aimed to consolidate how analytic indicators of engagement have previously been applied across clinical and technological contexts, to inform how they might be optimally applied in future evaluations. Methods: We conducted a scoping review to catalog the range of analytic indicators being used in evaluations of consumer mHealth apps for chronic conditions. We categorized studies according to app structure and application of engagement data and calculated descriptive data for each category. Chi-square and Fisher exact tests of independence were applied to calculate differences between coded variables. Results: A total of 41 studies met our inclusion criteria. The average mHealth evaluation included for review was a two-group pretest-posttest randomized controlled trial of a hybrid-structured app for mental health self-management, had 103 participants, lasted 5 months, did not provide access to health care provider services, measured 3 analytic indicators of engagement, segmented users based on engagement data, applied engagement data for descriptive analyses, and did not report on attrition. Across the reviewed studies, engagement was measured using the following 7 analytic indicators: the number of measures recorded (76\%, 31/41), the frequency of interactions logged (73\%, 30/41), the number of features accessed (49\%, 20/41), the number of log-ins or sessions logged (46\%, 19/41), the number of modules or lessons started or completed (29\%, 12/41), time spent engaging with the app (27\%, 11/41), and the number or content of pages accessed (17\%, 7/41). Engagement with unstructured apps was mostly measured by the number of features accessed (8/10, P=.04), and engagement with hybrid apps was mostly measured by the number of measures recorded (21/24, P=.03). A total of 24 studies presented, described, or summarized the data generated from applying analytic indicators to measure engagement. The remaining 17 studies used or planned to use these data to infer a relationship between engagement patterns and intended outcomes. Conclusions: Although researchers measured on average 3 indicators in a single study, the majority reported findings descriptively and did not further investigate how engagement with an app contributed to its impact on health and well-being. Researchers are gaining nuanced insights into engagement but are not yet characterizing effective engagement for improved outcomes. Raising the standard of mHealth app efficacy through measuring analytic indicators of engagement may enable greater confidence in the causal impact of apps on improved chronic health and well-being. ", doi="10.2196/11941", url="http://mhealth.jmir.org/2019/1/e11941/", url="http://www.ncbi.nlm.nih.gov/pubmed/30664463" } @Article{info:doi/10.2196/11098, author="Ghanvatkar, Suparna and Kankanhalli, Atreyi and Rajan, Vaibhav", title="User Models for Personalized Physical Activity Interventions: Scoping Review", journal="JMIR Mhealth Uhealth", year="2019", month="Jan", day="16", volume="7", number="1", pages="e11098", keywords="review", keywords="exercise", keywords="physical fitness", keywords="automation", keywords="mobile apps", keywords="web browser", keywords="health communication", keywords="health promotion", abstract="Background: Fitness devices have spurred the development of apps that aim to motivate users, through interventions, to increase their physical activity (PA). Personalization in the interventions is essential as the target users are diverse with respect to their activity levels, requirements, preferences, and behavior. Objective: This review aimed to (1) identify different kinds of personalization in interventions for promoting PA among any type of user group, (2) identify user models used for providing personalization, and (3) identify gaps in the current literature and suggest future research directions. Methods: A scoping review was undertaken by searching the databases PsycINFO, PubMed, Scopus, and Web of Science. The main inclusion criteria were (1) studies that aimed to promote PA; (2) studies that had personalization, with the intention of promoting PA through technology-based interventions; and (3) studies that described user models for personalization. Results: The literature search resulted in 49 eligible studies. Of these, 67\% (33/49) studies focused solely on increasing PA, whereas the remaining studies had other objectives, such as maintaining healthy lifestyle (8 studies), weight loss management (6 studies), and rehabilitation (2 studies). The reviewed studies provide personalization in 6 categories: goal recommendation, activity recommendation, fitness partner recommendation, educational content, motivational content, and intervention timing. With respect to the mode of generation, interventions were found to be semiautomated or automatic. Of these, the automatic interventions were either knowledge-based or data-driven or both. User models in the studies were constructed with parameters from 5 categories: PA profile, demographics, medical data, behavior change technique (BCT) parameters, and contextual information. Only 27 of the eligible studies evaluated the interventions for improvement in PA, and 16 of these concluded that the interventions to increase PA are more effective when they are personalized. Conclusions: This review investigates personalization in the form of recommendations or feedback for increasing PA. On the basis of the review and gaps identified, research directions for improving the efficacy of personalized interventions are proposed. First, data-driven prediction techniques can facilitate effective personalization. Second, use of BCTs in automated interventions, and in combination with PA guidelines, are yet to be explored, and preliminary studies in this direction are promising. Third, systems with automated interventions also need to be suitably adapted to serve specific needs of patients with clinical conditions. Fourth, previous user models focus on single metric evaluations of PA instead of a potentially more effective, holistic, and multidimensional view. Fifth, with the widespread adoption of activity monitoring devices and mobile phones, personalized and dynamic user models can be created using available user data, including users' social profile. Finally, the long-term effects of such interventions as well as the technology medium used for the interventions need to be evaluated rigorously. ", doi="10.2196/11098", url="http://mhealth.jmir.org/2019/1/e11098/", url="http://www.ncbi.nlm.nih.gov/pubmed/30664474" } @Article{info:doi/10.2196/11724, author="Skrabal Ross, Xiomara and Gunn, M. Kate and Patterson, Pandora and Olver, Ian", title="Mobile-Based Oral Chemotherapy Adherence--Enhancing Interventions: Scoping Review", journal="JMIR Mhealth Uhealth", year="2018", month="Dec", day="21", volume="6", number="12", pages="e11724", keywords="medication adherence", keywords="antineoplastic agents", keywords="neoplasms", keywords="cell phone", keywords="text messaging", keywords="mobile apps", keywords="review", keywords="mHealth", abstract="Background: Adherence to oral chemotherapy is crucial to maximize treatment outcomes and avoid health complications in cancer patients. Mobile phones are widely available worldwide, and evidence that this technology can be successfully employed to increase medication adherence for the treatment of other chronic diseases (eg, diabetes) is well established. However, the extent to which there is evidence that mobile phone--based interventions improve adherence to oral chemotherapy is unknown. Objective: This scoping review aims to explore what is known about mobile phone--delivered interventions designed to enhance adherence to oral chemotherapy, to examine the reported findings on the utility of these interventions in increasing oral chemotherapy adherence, and to identify opportunities for development of future interventions. Methods: This study followed Arksey and O'Malley's scoping review methodological framework. Results: The review search yielded 5 studies reporting on 4 interventions with adults (aged >18 years) diagnosed with diverse cancer types. All interventions were considered acceptable, useful, and feasible. The following themes were evident: text messages and mobile apps were the main methods of delivering these interventions, the 2 most commonly employed oral chemotherapy adherence--enhancing strategies were management and reporting of drug-related symptoms and reminders to take medication, the importance of stakeholders' engagement in intervention design, and the overall positive perceptions of delivery features. Areas for future research identified by this review include the need for further studies to evaluate the impact of mobile phone--delivered interventions on adherence to oral chemotherapy as well as the relevance for future studies to incorporate design frameworks and economic evaluations and to explore the moderator effect of high anxiety, poor baseline adherence, and longer time taking prescribed drug on adherence to oral chemotherapy. Conclusions: Despite the increasing body of evidence on the use of mobile phones to deliver medication adherence--enhancing interventions in chronic diseases, literature on the oral chemotherapy context is lacking. This review showed that existing interventions are highly acceptable and useful to cancer patients. The engagement of stakeholders as well as the use of a design framework are important elements in the development of mobile phone--delivered interventions that can be translated into oncology settings. ", doi="10.2196/11724", url="http://mhealth.jmir.org/2018/12/e11724/", url="http://www.ncbi.nlm.nih.gov/pubmed/30578182" } @Article{info:doi/10.2196/10026, author="Richards, Rebecca and Kinnersley, Paul and Brain, Kate and McCutchan, Grace and Staffurth, John and Wood, Fiona", title="Use of Mobile Devices to Help Cancer Patients Meet Their Information Needs in Non-Inpatient Settings: Systematic Review", journal="JMIR Mhealth Uhealth", year="2018", month="Dec", day="14", volume="6", number="12", pages="e10026", keywords="cell phone", keywords="smartphone", keywords="computers, handheld", keywords="cancer", keywords="neoplasms", keywords="patients", keywords="information dissemination", keywords="consumer health information", abstract="Background: The shift from inpatient to outpatient cancer care means that patients are now required to manage their condition at home, away from regular supervision by clinicians. Subsequently, research has consistently reported that many patients with cancer have unmet information needs during their illness. Mobile devices, such as mobile phones and tablet computers, provide an opportunity to deliver information to patients remotely. To date, no systematic reviews have evaluated how mobile devices have been used specifically to help patients meet to their information needs. Objective: A systematic review was conducted to identify studies that describe the use of mobile interventions to enable patients with cancer meet their cancer-related information needs in non-inpatient settings, and to describe the effects and feasibility of these interventions. Methods: MEDLINE, Embase, and PsycINFO databases were searched up until January 2017. Search terms related to ``mobile devices,'' ``information needs,'' and ``cancer'' were used. There were no restrictions on study type in order to be as inclusive as possible. Study participants were patients with cancer undergoing treatment. Interventions had to be delivered by a mobile or handheld device, attempt to meet patients' cancer-related information needs, and be for use in non-inpatient settings. Critical Appraisal Skills Programme checklists were used to assess the methodological quality of included studies. A narrative synthesis was performed and findings were organized by common themes found across studies. Results: The initial search yielded 1020 results. We included 23 articles describing 20 studies. Interventions aimed to improve the monitoring and management of treatment-related symptoms (17/20, 85\%), directly increase patients' knowledge related to their condition (2/20, 10\%), and improve communication of symptoms to clinicians in consultations (1/20, 5\%). Studies focused on adult (17/20; age range 24-87 years) and adolescent (3/20; age range 8-18 years) patients. Sample sizes ranged from 4-125, with 13 studies having 25 participants or fewer. Most studies were conducted in the United Kingdom (12/20, 52\%) or United States (7/20, 30\%). Of the 23 articles included, 12 were of medium quality, 9 of poor quality, and 2 of good quality. Overall, interventions were reported to be acceptable and perceived as useful and easy to use. Few technical problems were encountered. Adherence was generally consistent and high (periods ranged from 5 days to 6 months). However, there was considerable variation in use of intervention components within and between studies. Reported benefits of the interventions included improved symptom management, patient empowerment, and improved clinician-patient communication, although mixed findings were reported for patients' health-related quality of life and anxiety. Conclusions: The current review highlighted that mobile interventions for patients with cancer are only meeting treatment or symptom-related information needs. There were no interventions designed to meet patients' full range of cancer-related information needs, from information on psychological support to how to manage finances during cancer, and the long-term effects of treatment. More comprehensive interventions are required for patients to meet their information needs when managing their condition in non-inpatient settings. Controlled evaluations are needed to further determine the effectiveness of these types of intervention. ", doi="10.2196/10026", url="https://mhealth.jmir.org/2018/12/e10026/", url="http://www.ncbi.nlm.nih.gov/pubmed/30552082" } @Article{info:doi/10.2196/mhealth.9119, author="Hughson, Patricia Jo-anne and Daly, Oliver J. and Woodward-Kron, Robyn and Hajek, John and Story, David", title="The Rise of Pregnancy Apps and the Implications for Culturally and Linguistically Diverse Women: Narrative Review", journal="JMIR Mhealth Uhealth", year="2018", month="Nov", day="16", volume="6", number="11", pages="e189", keywords="culture", keywords="emigrants and immigrants", keywords="health communication", keywords="information-seeking behavior", keywords="literacy", keywords="maternal health", keywords="mHealth", keywords="mobile phone", keywords="pregnancy", keywords="self-care", keywords="vulnerable populations", abstract="Background: Pregnancy apps are a booming global industry, with most pregnant women in high-income countries now using them. From the perspective of health care and health information provision, this is both encouraging and unsettling; the demand indicates a clear direction for the development of future resources, but it also underscores the importance of processes ensuring access, reliability, and quality control. Objective: This review provides an overview of current literature on pregnancy apps and aims at describing (1) the ways in which apps are used by women, in general, and by those of a culturally and linguistically diverse (CALD) background; (2) the utility and quality of information provided; and (3) areas where more research, development, and oversight are needed. Methods: We chose a narrative review methodology for the study and performed a structured literature search including studies published between 2012 and 2017. Searches were performed using MEDLINE, EMBASE, and CINAHL databases. Studies were identified for inclusion using two separate search criteria and strategies: (1) studies on pregnancy apps and pregnant women's use of these apps and (2) studies on CALD pregnant women and their use of technology for accessing information on and services for pregnancy. Overall, we selected 38 studies. Results: We found that pregnancy apps were principally used to access pregnancy health and fetal development information. Data storage capability, Web-based features or personalized tools, and social media features were also popular app features sought by women. Lower rates of the pregnancy app uptake were indicated among lower-income and non-English-speaking women. Preliminary evidence indicates that a combination of technological, health literacy, and language issues may result in lower uptake of pregnancy apps by these groups; however, further investigation is required. A marked limitation of the health app industry is lack of regulation in a commercially dominated field, making it difficult for users to assess the reliability of the information being presented. Health professionals and users alike indicate that given the choice, they would prefer using pregnancy apps that are relevant to their local health care context and come from a trusted source. Evidence indicates a need for greater health professional and institutional engagement in the app development, as well as awareness of and guidance for women's use of these resources. Conclusions: This is the first review of pregnancy app use, types of information provided, and features preferred by pregnant women in general and by those of a CALD background in particular. It indicates the demand for access to accurate information that is relevant to users, their community, and their associated health services. Given the popularity of pregnancy apps, such apps have enormous potential to be used for the provision of accurate, evidence-based health information. ", doi="10.2196/mhealth.9119", url="https://mhealth.jmir.org/2018/11/e189/", url="http://www.ncbi.nlm.nih.gov/pubmed/30446483" } @Article{info:doi/10.2196/10076, author="Eckerstorfer, V. Lisa and Tanzer, K. Norbert and Vogrincic-Haselbacher, Claudia and Kedia, Gayannee and Brohmer, Hilmar and Dinslaken, Isabelle and Corcoran, Katja", title="Key Elements of mHealth Interventions to Successfully Increase Physical Activity: Meta-Regression", journal="JMIR Mhealth Uhealth", year="2018", month="Nov", day="12", volume="6", number="11", pages="e10076", keywords="exercise", keywords="physical activity", keywords="mHealth", keywords="behavior change", keywords="meta-analysis", keywords="meta-regression", abstract="Background: Mobile technology gives researchers unimagined opportunities to design new interventions to increase physical activity. Unfortunately, it is still unclear which elements are useful to initiate and maintain behavior change. Objective: In this meta-analysis, we investigated randomized controlled trials of physical activity interventions that were delivered via mobile phone. We analyzed which elements contributed to intervention success. Methods: After searching four databases and science networks for eligible studies, we entered 50 studies with N=5997 participants into a random-effects meta-analysis, controlling for baseline group differences. We also calculated meta-regressions with the most frequently used behavior change techniques (behavioral goals, general information, self-monitoring, information on where and when, and instructions on how to) as moderators. Results: We found a small overall effect of the Hedges g=0.29, (95\% CI 0.20 to 0.37) which reduced to g=0.22 after correcting for publication bias. In the moderator analyses, behavioral goals and self-monitoring each led to more intervention success. Interventions that used neither behavioral goals nor self-monitoring had a negligible effect of g=0.01, whereas utilizing either technique increased effectiveness by $\Delta$g=0.31, but combining them did not provide additional benefits ($\Delta$g=0.36). Conclusions: Overall, mHealth interventions to increase physical activity have a small to moderate effect. However, including behavioral goals or self-monitoring can lead to greater intervention success. More research is needed to look at more behavior change techniques and their interactions. Reporting interventions in trial registrations and articles need to be structured and thorough to gain accurate insights. This can be achieved by basing the design or reporting of interventions on taxonomies of behavior change. ", doi="10.2196/10076", url="https://mhealth.jmir.org/2018/11/e10076/", url="http://www.ncbi.nlm.nih.gov/pubmed/30425028" } @Article{info:doi/10.2196/publichealth.9015, author="Tom-Aba, Daniel and Nguku, Mboya Patrick and Arinze, Chukwujekwu Chinedu and Krause, Gerard", title="Assessing the Concepts and Designs of 58 Mobile Apps for the Management of the 2014-2015 West Africa Ebola Outbreak: Systematic Review", journal="JMIR Public Health Surveill", year="2018", month="Oct", day="29", volume="4", number="4", pages="e68", keywords="case management", keywords="contact tracing", keywords="Ebola virus disease", keywords="eHealth", keywords="mHealth", keywords="systematic review", keywords="West Africa", abstract="Background: The use of mobile phone information technology (IT) in the health sector has received much attention especially during the 2014-2015 Ebola virus disease (EVD) outbreak. mHealth can be attributed to a major improvement in EVD control, but there lacks an overview of what kinds of tools were available and used based on the functionalities they offer. Objective: We aimed to conduct a systematic review of mHealth tools in the context of the recent EVD outbreak to identify the most promising approaches and guide further mHealth developments for infectious disease control. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we searched for all reports on mHealth tools developed in the context of the 2014-2015 EVD outbreak published between January 1, 2014 and December 31, 2015 on Google Scholar, MEDLINE, CAB Abstracts (Global Health), POPLINE, and Web of Science in any language using the search strategy: (``outbreak'' OR ``epidemic'') AND (``mobile phone'' OR ``smartphone'' OR ``smart phone'' OR ``mobile phone'' OR ``tablet'' OR ``mHealth'') AND (``Ebola'' OR ''EVD'' OR ``VHF'' OR ``Ebola virus disease'' OR ``viral hemorrhagic fever'') AND (``2014'' OR ``2015''). The relevant publications were selected by 2 independent reviewers who applied a standardized data extraction form on the tools' functionalities. Results: We identified 1220 publications through the search strategy, of which 6.31\% (77/1220) were original publications reporting on 58 specific mHealth tools in the context of the EVD outbreak. Of these, 62\% (34/55) offered functionalities for surveillance, 22\% (10/45) for case management, 18\% (7/38) for contact tracing, and 6\% (3/51) for laboratory data management. Only 3 tools, namely Community Care, Sense Ebola Followup, and Surveillance and Outbreak Response Management and Analysis System supported all four of these functionalities. Conclusions: Among the 58 identified tools related to EVD management in 2014 and 2015, only 3 appeared to contain all 4 key functionalities relevant for the response to EVD outbreaks and may be most promising for further development. ", doi="10.2196/publichealth.9015", url="http://publichealth.jmir.org/2018/4/e68/", url="http://www.ncbi.nlm.nih.gov/pubmed/30373727" } @Article{info:doi/10.2196/11231, author="Thurnheer, E. Simon and Gravestock, Isaac and Pichierri, Giuseppe and Steurer, Johann and Burgstaller, M. Jakob", title="Benefits of Mobile Apps in Pain Management: Systematic Review", journal="JMIR Mhealth Uhealth", year="2018", month="Oct", day="22", volume="6", number="10", pages="e11231", keywords="mobile application", keywords="pain", keywords="pain management", keywords="smartphone", keywords="cell phone", keywords="telemedicine", keywords="review", abstract="Background: Pain is a common condition with a significant physical, psychosocial, and economic impact. Due to enormous progress in mobile device technology as well as the increase in smartphone ownership in the general population, mobile apps can be used to monitor patients with pain and support them in pain management. Objective: The aim of this review was to assess the efficacy of smartphone or computer tablet apps in the management of patients with pain. Methods: In December 2017, a literature search was performed in the following databases: MEDLINE, EMBASE, CINAHL, Cochrane, and PsycINFO. In addition, a bibliography search was conducted. We included studies with at least 20 participants per arm that evaluated the effects of apps on smartphones or computer tablets on improvement in pain. Results: A total of 15 studies with 1962 patients met the inclusion criteria. Of these, 4 studies examined the effect of mobile apps on pain management in an in-clinic setting and 11 in an out-clinic setting. The majority of the original studies reported beneficial effects of the use of a pain app. Severity of pain decreased in most studies where patients were using an app compared with patients not using an app. Other outcomes, such as worst pain or quality of life showed improvements in patients using an app. Due to heterogeneity between the original studies---patient characteristics, app content, and study setting---a synthesis of the results by statistical methods was not performed. Conclusions: Apps for pain management may be beneficial for patients, particularly in an out-clinic setting. Studies have shown that pain apps are workable and well liked by patients and health care professionals. There is no doubt that in the near future, mobile technologies will develop further. Medicine could profit from this development as indicated by our results, but there is a need for more scientific inputs. It is desirable to know which elements of apps or additional devices and tools may improve usability and help patients in pain management. ", doi="10.2196/11231", url="http://mhealth.jmir.org/2018/10/e11231/", url="http://www.ncbi.nlm.nih.gov/pubmed/30348633" } @Article{info:doi/10.2196/10799, author="Ludwig, Kim and Arthur, Rosie and Sculthorpe, Nicholas and Fountain, Hollie and Buchan, S. Duncan", title="Text Messaging Interventions for Improvement in Physical Activity and Sedentary Behavior in Youth: Systematic Review", journal="JMIR Mhealth Uhealth", year="2018", month="Sep", day="17", volume="6", number="9", pages="e10799", keywords="review", keywords="exercise", keywords="sedentary lifestyle", keywords="text messaging", keywords="cell phone", keywords="telemedicine", keywords="adolescent", abstract="Background: The use of text messages (short message service, SMS) to change physical activity and sedentary behavior in youth is of interest due to the need for novel, more effective intervention approaches. Previous reviews have examined a variety of technology-based interventions and their impact on different health behaviors, but evidence regarding the impact of just SMS on physical activity and sedentary behavior is lacking. Objective: The aim of this study was to assess the effectiveness and use of theory of SMS interventions for improving physical activity and sedentary behavior in youth. Methods: Authors systematically searched electronic databases from March to November 2017. Citations were sifted using additional reviewers, and a qualitative synthesis of eligible studies was conducted using piloted data extraction forms. To be eligible for inclusion, studies had to be of a randomized controlled or quasi-experimental design, incorporate SMS, involve adolescents between the ages of 10 and 19 years, and assess at least one physical activity or sedentary behavior outcome. Risk of bias was assessed using the Cochrane Collaboration's Risk of Bias tool. Results: A total of 13 studies reporting 11 interventions were included in the qualitative analysis. Studies included interventions that were conducted in schools, online, or face-to-face. Studies were of high heterogeneity with regard to study duration, participant characteristics, intervention content, and outcome measures. Findings were equivocal with regard to intervention effectiveness for physical activity and sedentary behavior. Overall, 7 interventions resulted in an improvement for physical activity and 6 for sedentary behavior. All studies were judged to be of high risk of bias for at least 1 item. Conclusions: Some studies in this review showed promising results for using SMS to improve physical activity and sedentary behavior in youth. High heterogeneity of design and outcome measures precluded data pooling and conclusions as to which specific intervention elements are linked to increased effectiveness cannot be drawn. The authors propose incorporating the following elements in future studies: specific focus on desired health behavior; mixed-methods design; include long-term follow-up; include self-monitoring, goal setting, and feedback; combine SMS with a mobile app; and send 3 or more SMS text messages per week. More rigorous studies are needed to explore the relationship between intervention effectiveness and specific intervention components such as content and delivery. ", doi="10.2196/10799", url="http://mhealth.jmir.org/2018/9/e10799/", url="http://www.ncbi.nlm.nih.gov/pubmed/30224335" } @Article{info:doi/10.2196/mhealth.8554, author="Choi, Jihye and Cho, Youngtae and Woo, Hyekyung", title="mHealth Approaches in Managing Skin Cancer: Systematic Review of Evidence-Based Research Using Integrative Mapping", journal="JMIR Mhealth Uhealth", year="2018", month="Aug", day="02", volume="6", number="8", pages="e164", keywords="skin cancer", keywords="mHealth", keywords="e-Health", keywords="mobile technology", keywords="teledermatology", keywords="melanoma", abstract="Background: mHealth, which encompasses mobile health technologies and interventions, is rapidly evolving in various medical specialties, and its impact is evident in oncology. In particular, mHealth has established itself as a prominent part of dermatology for cancer screening. Intensified research to seek its use and effectiveness in each phase of the skin cancer continuum is needed in this fast-growing field of teledermatology. Objective: The purpose of this review was to describe current trends in research addressing the integration of mHealth and its contributions across the skin cancer continuum. Methods: A systematic review framework was applied to the search using three electronic databases: PubMed, Web of Science, and Embase. We extensively reviewed appropriate studies regarding skin cancer and mobile technology published between 2007 and 2017. Studies of the role and impact of mobile technology in the prevention and management of skin cancer were included. We selected 18 studies adhering to the inclusion and exclusion criteria for analysis. Results: Of the 18 studies, 5 (28\%) evaluated prevention interventions, 6 (33\%) assessed diagnostic accuracy, and 7 (39\%) pertained to feasibility in the context of mHealth approaches for skin cancer care. These studies portray the potential of mobile teledermatology in the prevention and management of skin cancer. However, not all phases of skin cancer involve mHealth, and not all have been addressed by research. Conclusions: This review extends our knowledge not only on the contributions of mHealth technologies, but also on their integration in different phases of skin cancer care. To optimize the effectiveness of mHealth in dermatology, larger numbers of robust, evidence-based studies on teledermatology implementations, distributed evenly across the care continuum, should be conducted so that research can be expanded to systematic reviews. ", doi="10.2196/mhealth.8554", url="http://mhealth.jmir.org/2018/8/e164/", url="http://www.ncbi.nlm.nih.gov/pubmed/30072362" } @Article{info:doi/10.2196/10115, author="Adu, D. Mary and Malabu, H. Usman and Callander, J. Emily and Malau-Aduli, EO Aduli and Malau-Aduli, S. Bunmi", title="Considerations for the Development of Mobile Phone Apps to Support Diabetes Self-Management: Systematic Review", journal="JMIR Mhealth Uhealth", year="2018", month="Jun", day="21", volume="6", number="6", pages="e10115", keywords="mobile phone apps", keywords="diabetes melitus", keywords="self-management", keywords="developmental consideration", keywords="systematic review", abstract="Background: There is increased research interest in the use of mobile phone apps to support diabetes management. However, there are divergent views on what constitute the minimum standards for inclusion in the development of mobile phone apps. Mobile phone apps require an evidence-based approach to development which will consequently impact on their effectiveness. Therefore, comprehensive information on developmental considerations could help designers and researchers to develop innovative and effective patient-centered self-management mobile phone apps for diabetes patients. Objective: This systematic review examined the developmental considerations adopted in trials that engaged mobile phone applications for diabetes self-management. Methods: A comprehensive search strategy was implemented across 5 electronic databases; Medline, Scopus, Social Science Citation Index, the Cochrane Central Register of Controlled Trials and Cumulative Index of Nursing and Allied Health Literature (CINALHL) and supplemented by reference list from identified studies. Study quality was evaluated using the Joanna Briggs Critical appraisal checklist for trials. Information on developmental factors (health behavioral theory, functionality, pilot testing, user and clinical expert involvements, data privacy and app security) were assessed across experimental studies using a template developed for the review. Results: A total of 11 studies (10 randomized controlled trials and 1 quasi-experimental trial) that fitted the inclusion criteria were identified. All the included studies had the functionality of self-monitoring of blood glucose. However, only some of them included functions for data analytics (7/11, 63.6\%), education (6/11, 54.5\%) and reminder (6/11, 54.5\%). There were 5/11(45.5\%) studies with significantly improved glycosylated hemoglobin in the intervention groups where educational functionality was present in the apps used in the 5 trials. Only 1 (1/11, 9.1\%) study considered health behavioral theory and user involvement, while 2 (2/11, 18.1\%) other studies reported the involvement of clinical experts in the development of their apps. There were 4 (4/11, 36.4\%) studies which referred to data security and privacy considerations during their app development while 7 (7/12, 63.6\%) studies provided information on pilot testing of apps before use in the full trial. Overall, none of the studies provided information on all developmental factors assessed in the review. Conclusions: There is a lack of elaborate and detailed information in the literature regarding the factors considered in the development of apps used as interventions for diabetes self-management. Documentation and inclusion of such vital information will foster a transparent and shared decision-making process that will ultimately lead to the development of practical and user-friendly self-management apps that can enhance the quality of life for diabetes patients. ", doi="10.2196/10115", url="http://mhealth.jmir.org/2018/6/e10115/", url="http://www.ncbi.nlm.nih.gov/pubmed/29929949" } @Article{info:doi/10.2196/mhealth.9671, author="Rivera-Romero, Octavio and Olmo, Alberto and Mu{\~n}oz, Roc{\'i}o and Stiefel, Pablo and Miranda, Luisa Mar{\'i}a and Beltr{\'a}n, M. Luis", title="Mobile Health Solutions for Hypertensive Disorders in Pregnancy: Scoping Literature Review", journal="JMIR Mhealth Uhealth", year="2018", month="May", day="30", volume="6", number="5", pages="e130", keywords="pregnancy", keywords="hypertension", keywords="pre-eclampsia", keywords="blood pressure", keywords="telemedicine", abstract="Background: Hypertensive disorders are the most common complications during pregnancy, occurring in 5\% to 11\% of pregnancies; gestational hypertension and preeclampsia are the leading causes of perinatal and maternal morbidity and mortality, especially in low- and middle-income countries (LMIC) where maternal and perinatal mortality ratios are still high. Pregnant women with hypertensive disorders could greatly benefit from mobile health (mHealth) solutions as a novel way to identify and control early symptoms, as shown in an increasing number of publications in the field. Such digital health solutions may overcome access limiting factors and the lack of skilled medical professionals and finances commonly presented in resource-poor environments. Objective: The aim of this study was to conduct a literature review of mHealth solutions used as support in hypertensive disorders during pregnancy, with the objective to identify the most relevant protocols and prototypes that could influence and improve current clinical practice. Methods: A methodological review following a scoping methodology was conducted. Manuscripts published in research journals reporting technical information of mHealth solutions for hypertensive disorders in pregnancy were included, categorizing articles in different groups: Diagnosis and Monitoring, mHealth Decision Support System, Education, and Health Promotion, and seven research questions were posed to study the manuscripts. Results: The search in electronic research databases yielded 327 articles. After removing duplicates, 230 articles were selected for screening. Finally, 11 articles met the inclusion criteria, and data were extracted from them. Very positive results in the improvement of maternal health and acceptability of solutions were found, although most of the studies involved a small number of participants, and none were complete clinical studies. Accordingly, none of the reported prototypes were integrated in the different health care systems. Only 4 studies used sensors for physiological measurements, and only 2 used blood pressure sensors despite the importance of this physiological parameter in the control of hypertension. The reported mHealth solutions have great potential to improve clinical practice in areas lacking skilled medical professionals or with a low health care budget, of special relevance in LMIC, although again, no extensive clinical validation has been carried out in these environments. Conclusions: mHealth solutions hold enormous potential to support hypertensive disorders during pregnancy and improve current clinical practice. Although very positive results have been reported in terms of usability and the improvement of maternal health, rigorous complete clinical trials are still necessary to support integration in health care systems. There is a clear need for simple mHealth solutions specifically developed for resource-poor environments that meet the United Nations Sustainable Development Goal (SDG); of enormous interest in LMIC. ", doi="10.2196/mhealth.9671", url="http://mhealth.jmir.org/2018/5/e130/" } @Article{info:doi/10.2196/mhealth.8639, author="Lam, A. Jeffrey and Dang, Thuy Linh and Phan, Tran Ngoc and Trinh, Thi Hue and Vu, Cong Nguyen and Nguyen, Kieu Cuong", title="Mobile Health Initiatives in Vietnam: Scoping Study", journal="JMIR Mhealth Uhealth", year="2018", month="Apr", day="24", volume="6", number="4", pages="e106", keywords="mHealth", keywords="eHealth", keywords="mobile health", keywords="telemedicine", keywords="Vietnam", keywords="scoping review", abstract="Background: Mobile health (mHealth) offers a promising solution to the multitude of challenges the Vietnamese health system faces, but there is a scarcity of published information on mHealth in Vietnam. Objective: The objectives of this scoping study were (1) to summarize the extent, range, and nature of mHealth initiatives in Vietnam and (2) to examine the opportunities and threats of mHealth utilization in the Vietnamese context. Methods: This scoping study systematically identified and extracted relevant information from 20 past and current mHealth initiatives in Vietnam. The study includes multimodal information sources, including published literature, gray literature (ie, government reports and unpublished literature), conference presentations, Web-based documents, and key informant interviews. Results: We extracted information from 27 records from the electronic search and conducted 14 key informant interviews, allowing us to identify 20 mHealth initiatives in Vietnam. Most of the initiatives were primarily funded by external donors (n=15), while other initiatives were government funded (n=1) or self-funded (n=4). A majority of the initiatives targeted vulnerable and hard-to-reach populations (n=11), aimed to prevent the occurrence of disease (n=12), and used text messaging (short message service, SMS) as part of their intervention (n=14). The study revealed that Vietnamese mHealth implementation has been challenged by factors including features unique to the Vietnamese language (n=4) and sociocultural factors (n=3). Conclusions: The largest threats to the popularity of mHealth initiatives are the absence of government policy, lack of government interest, heavy dependence on foreign funding, and lack of technological infrastructure. Finally, while current mHealth initiatives have already demonstrated promising opportunities for alternative models of funding, such as social entrepreneurship or private business models, sustainable mHealth initiatives outside of those funded by external donors have not yet been undertaken. ", doi="10.2196/mhealth.8639", url="http://mhealth.jmir.org/2018/4/e106/", url="http://www.ncbi.nlm.nih.gov/pubmed/29691214" } @Article{info:doi/10.2196/jmir.8342, author="Elaheebocus, Ally Sheik Mohammad Roushdat and Weal, Mark and Morrison, Leanne and Yardley, Lucy", title="Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review", journal="J Med Internet Res", year="2018", month="Feb", day="22", volume="20", number="2", pages="e20", keywords="systematic review", keywords="social media", keywords="behavior control", keywords="health behavior", keywords="behavioral medicine", keywords="eHealth", abstract="Background: Incorporating social media features into digital behavior change interventions (DBCIs) has the potential to contribute positively to their success. However, the lack of clear design principles to describe and guide the use of these features in behavioral interventions limits cross-study comparisons of their uses and effects. Objective: The aim of this study was to provide a systematic review of DBCIs targeting modifiable behavioral risk factors that have included social media features as part of their intervention infrastructure. A taxonomy of social media features is presented to inform the development, description, and evaluation of behavioral interventions. Methods: Search terms were used in 8 databases to identify DBCIs that incorporated social media features and targeted tobacco smoking, diet and nutrition, physical activities, or alcohol consumption. The screening and review process was performed by 2 independent researchers. Results: A total of 5264 articles were screened, and 143 articles describing a total of 134 studies were retained for full review. The majority of studies (70\%) reported positive outcomes, followed by 28\% finding no effects with regard to their respective objectives and hypothesis, and 2\% of the studies found that their interventions had negative outcomes. Few studies reported on the association between the inclusion of social media features and intervention effect. A taxonomy of social media features used in behavioral interventions has been presented with 36 social media features organized under 7 high-level categories. The taxonomy has been used to guide the analysis of this review. Conclusions: Although social media features are commonly included in DBCIs, there is an acute lack of information with respect to their effect on outcomes and a lack of clear guidance to inform the selection process based on the features' suitability for the different behaviors. The proposed taxonomy along with the set of recommendations included in this review will support future research aimed at isolating and reporting the effects of social media features on DBCIs, cross-study comparisons, and evaluations. ", doi="10.2196/jmir.8342", url="http://www.jmir.org/2018/2/e20/", url="http://www.ncbi.nlm.nih.gov/pubmed/29472174" } @Article{info:doi/10.2196/mhealth.8873, author="Marcolino, Soriano Milena and Oliveira, Queiroz Jo{\~a}o Antonio and D'Agostino, Marcelo and Ribeiro, Luiz Antonio and Alkmim, Moreira Maria Beatriz and Novillo-Ortiz, David", title="The Impact of mHealth Interventions: Systematic Review of Systematic Reviews", journal="JMIR Mhealth Uhealth", year="2018", month="Jan", day="17", volume="6", number="1", pages="e23", keywords="telemedicine", keywords="medical informatics", keywords="mobile phones", abstract="Background: Mobile phone usage has been rapidly increasing worldwide. mHealth could efficiently deliver high-quality health care, but the evidence supporting its current effectiveness is still mixed. Objective: We performed a systematic review of systematic reviews to assess the impact or effectiveness of mobile health (mHealth) interventions in different health conditions and in the processes of health care service delivery. Methods: We used a common search strategy of five major scientific databases, restricting the search by publication date, language, and parameters in methodology and content. Methodological quality was evaluated using the Measurement Tool to Assess Systematic Reviews (AMSTAR) checklist. Results: The searches resulted in a total of 10,689 articles. Of these, 23 systematic reviews (371 studies; more than 79,665 patients) were included. Seventeen reviews included studies performed in low- and middle-income countries. The studies used diverse mHealth interventions, most frequently text messaging (short message service, SMS) applied to different purposes (reminder, alert, education, motivation, prevention). Ten reviews were rated as low quality (AMSTAR score 0-4), seven were rated as moderate quality (AMSTAR score 5-8), and six were categorized as high quality (AMSTAR score 9-11). A beneficial impact of mHealth was observed in chronic disease management, showing improvement in symptoms and peak flow variability in asthma patients, reducing hospitalizations and improving forced expiratory volume in 1 second; improving chronic pulmonary diseases symptoms; improving heart failure symptoms, reducing deaths and hospitalization; improving glycemic control in diabetes patients; improving blood pressure in hypertensive patients; and reducing weight in overweight and obese patients. Studies also showed a positive impact of SMS reminders in improving attendance rates, with a similar impact to phone call reminders at reduced cost, and improved adherence to tuberculosis and human immunodeficiency virus therapy in some scenarios, with evidence of decrease of viral load. Conclusions: Although mHealth is growing in popularity, the evidence for efficacy is still limited. In general, the methodological quality of the studies included in the systematic reviews is low. For some fields, its impact is not evident, the results are mixed, or no long-term studies exist. Exceptions include the moderate quality evidence of improvement in asthma patients, attendance rates, and increased smoking abstinence rates. Most studies were performed in high-income countries, implying that mHealth is still at an early stage of development in low-income countries. ", doi="10.2196/mhealth.8873", url="http://mhealth.jmir.org/2018/1/e23/", url="http://www.ncbi.nlm.nih.gov/pubmed/29343463" } @Article{info:doi/10.2196/mhealth.8998, author="Chen, Huan and Chai, Yanling and Dong, Le and Niu, Wenyi and Zhang, Puhong", title="Effectiveness and Appropriateness of mHealth Interventions for Maternal and Child Health: Systematic Review", journal="JMIR Mhealth Uhealth", year="2018", month="Jan", day="09", volume="6", number="1", pages="e7", keywords="telemedicine", keywords="maternal health", keywords="child health", abstract="Background: The application of mobile health (mHealth) technology in reproductive, maternal, newborn, and child health (RMNCH) is increasing worldwide. However, best practice and the most effective mHealth interventions have not been reviewed systematically. Objective: A systematic review and meta-analysis of studies of mHealth interventions for RMNCH around the world were conducted to investigate their characteristics as well as the features and effectiveness of mHealth interventions. Methods: Studies of mHealth interventions for RMNCH between January 2011 and December 2016 were retrieved from 6 databases (PubMed, EMBASE, Global Health, China National Knowledge Infrastructure, VIP Database for Chinese Technical Periodicals, and Wanfang Data Knowledge Service Medium). Comparable studies were included in a random-effects meta-analysis for both exclusive breastfeeding (EBF) and antenatal checks (ANC). Descriptive analyses were conducted for mHealth studies with a range of study designs. Results: Analyses of 245 studies were included, including 51 randomized controlled trials (RCTs). Results showed that there are increasing numbers of studies on mHealth interventions for RMNCH. Although 2 meta-analysis, one with 2 RCTs on EBF (odds ratio [OR] 2.03, 95\% CI 1.34-3.08, I2=25\%) and the other with 3 RCTs on ANC (OR 1.43, 95\% CI 1.13-1.79, I2=78\%), showed that mHealth interventions are more effective than usual care, almost half (43\%) of RCTs showed negative or unclear results on mHealth interventions. Functions described in mHealth interventions were diverse, and the health stages covered were broad. However, single function or single stage appeared to be dominant among mHealth interventions compared with multiple functions or stages. Conclusions: More rigorous evaluations are needed to draw consistent conclusions and to analyze mHealth products with multiple functions, especially those popular in the app markets. ", doi="10.2196/mhealth.8998", url="http://mhealth.jmir.org/2018/1/e7/", url="http://www.ncbi.nlm.nih.gov/pubmed/29317380" } @Article{info:doi/10.2196/mhealth.8671, author="Dougherty, Bryn and Badawy, M. Sherif", title="Using Google Glass in Nonsurgical Medical Settings: Systematic Review", journal="JMIR Mhealth Uhealth", year="2017", month="Oct", day="19", volume="5", number="10", pages="e159", keywords="Google Glass", keywords="wearable", keywords="wearable device", keywords="head-mounted wearable device", keywords="non-surgical setting", keywords="non-surgical condition", keywords="medical setting", keywords="medical condition", abstract="Background: Wearable technologies provide users hands-free access to computer functions and are becoming increasingly popular on both the consumer market and in various industries. The medical industry has pioneered research and implementation of head-mounted wearable devices, such as Google Glass. Most of this research has focused on surgical interventions; however, other medical fields have begun to explore the potential of this technology to support both patients and clinicians. Objective: Our aim was to systematically evaluate the feasibility, usability, and acceptability of using Google Glass in nonsurgical medical settings and to determine the benefits, limitations, and future directions of its application. Methods: This review covers literature published between January 2013 and May 2017. Searches included PubMed MEDLINE, Embase, INSPEC (Ebsco), Cochrane Central Register of Controlled Trials (CENTRAL), IEEE Explore, Web of Science, Scopus, and Compendex. The search strategy sought all articles on Google Glass. Two reviewers independently screened titles and abstracts, assessed full-text articles, and extracted data from articles that met all predefined criteria. Any disagreements were resolved by discussion or consultation by the senior author. Included studies were original research articles that evaluated the feasibility, usability, or acceptability of Google Glass in nonsurgical medical settings. The preferred reporting results of systematic reviews and meta-analyses (PRISMA) guidelines were followed for reporting of results. Results: Of the 852 records examined, 51 met all predefined criteria, including patient-centered (n=21) and clinician-centered studies (n=30). Patient-centered studies explored the utility of Google Glass in supporting patients with motor impairments (n=8), visual impairments (n=5), developmental and psychiatric disorders (n=2), weight management concerns (n=3), allergies (n=1), or other health concerns (n=2). Clinician-centered studies explored the utility of Google Glass in student training (n=9), disaster relief (n=4), diagnostics (n=2), nursing (n=1), autopsy and postmortem examination (n=1), wound care (n=1), behavioral sciences (n=1), and various medical subspecialties, including, cardiology (n=3), radiology (n=3), neurology (n=1), anesthesiology (n=1), pulmonology (n=1), toxicology (n=1), and dermatology (n=1). Most of the studies were conducted in the United States (40/51, 78\%), did not report specific age information for participants (38/51, 75\%), had sample size <30 participants (29/51, 57\%), and were pilot or feasibility studies (31/51, 61\%). Most patient-centered studies (19/21, 90\%) demonstrated feasibility with high satisfaction and acceptability among participants, despite a few technical challenges with the device. A number of clinician-centered studies (11/30, 37\%) reported low to moderate satisfaction among participants, with the most promising results being in the area of student training. Studies varied in sample size, approach for implementation of Google Glass, and outcomes assessment. Conclusions: The use of Google Glass in nonsurgical medical settings varied. More promising results regarding the feasibility, usability, and acceptability of using Google Glass were seen in patient-centered studies and student training settings. Further research evaluating the efficacy and cost-effectiveness of Google Glass as an intervention to improve important clinical outcomes is warranted. ", doi="10.2196/mhealth.8671", url="http://mhealth.jmir.org/2017/10/e159/", url="http://www.ncbi.nlm.nih.gov/pubmed/29051136" } @Article{info:doi/10.2196/mhealth.7014, author="Moore, Sarah and Tass{\'e}, Anne-Marie and Thorogood, Adrian and Winship, Ingrid and Zawati, Ma'n and Doerr, Megan", title="Consent Processes for Mobile App Mediated Research: Systematic Review", journal="JMIR Mhealth Uhealth", year="2017", month="Aug", day="30", volume="5", number="8", pages="e126", keywords="mHealth, informed consent, smartphone, cell phone, mobile applications, privacy, research ethics", abstract="Background: Since the launch of ResearchKit on the iOS platform in March 2015 and ResearchStack on the Android platform in June 2016, many academic and commercial institutions around the world have adapted these frameworks to develop mobile app-based research studies. These studies cover a wide variety of subject areas including melanoma, cardiomyopathy, and autism. Additionally, these app-based studies target a variety of participant populations, including children and pregnant women. Objective: The aim of this review was to document the variety of self-administered remote informed consent processes used in app-based research studies available between May and September 2016. Remote consent is defined as any consenting process with zero in-person steps, when a participant is able to join a study without ever seeing a member of the research team. This type of review has not been previously conducted. The research community would benefit from a rigorous interrogation of the types of consent taken as part of the seismic shift to entirely mobile meditated research studies. Methods: This review examines both the process of information giving and specific content shared, with special attention to data privacy, aggregation, and sharing. Results: Consistency across some elements of the app-based consent processes was found; for example, informing participants about how data will be curated from the phone. Variations in other elements were identified; for example, where specific information is shared and the level of detail disclosed. Additionally, several novel elements present in eConsent not typically seen in traditional consent for research were highlighted. Conclusions: This review advocates the importance of participant informedness in a novel and largely unregulated research setting. ", doi="10.2196/mhealth.7014", url="http://mhealth.jmir.org/2017/8/e126/", url="http://www.ncbi.nlm.nih.gov/pubmed/28855147" } @Article{info:doi/10.2196/mhealth.7088, author="Killikelly, Clare and He, Zhimin and Reeder, Clare and Wykes, Til", title="Improving Adherence to Web-Based and Mobile Technologies for People With Psychosis: Systematic Review of New Potential Predictors of Adherence", journal="JMIR Mhealth Uhealth", year="2017", month="Jul", day="20", volume="5", number="7", pages="e94", keywords="patient compliance", keywords="schizophrenia spectrum and other psychotic disorders", keywords="mobile phone", keywords="mHealth", abstract="Background: Despite the boom in new technologically based interventions for people with psychosis, recent studies suggest medium to low rates of adherence to these types of interventions. The benefits will be limited if only a minority of service users adhere and engage; if specific predictors of adherence can be identified then technologies can be adapted to increase the service user benefits. Objective: The study aimed to present a systematic review of rates of adherence, dropout, and approaches to analyzing adherence to newly developed mobile and Web-based interventions for people with psychosis. Specific predictors of adherence were also explored. Methods: Using keywords (Internet or online or Web-based or website or mobile) AND (bipolar disorder or manic depression or manic depressive illness or manic-depressive psychosis or psychosis or schizophr* or psychotic), the following databases were searched: OVID including MedLine, EMBASE and PsychInfo, Pubmed and Web of Science. The objectives and inclusion criteria for suitable studies were defined following PICOS (population: people with psychosis; intervention: mobile or Internet-based technology; comparison group: no comparison group specified; outcomes: measures of adherence; study design: randomized controlled trials (RCT), feasibility studies, and observational studies) criteria. In addition to measurement and analysis of adherence, two theoretically proposed predictors of adherence were examined: (1) level of support from a clinician or researcher throughout the study, and (2) level of service user involvement in the app or intervention development. We provide a narrative synthesis of the findings and followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines for reporting systematic reviews. Results: Of the 20 studies that reported a measure of adherence and a rate of dropout, 5 of these conducted statistical analyses to determine predictors of dropout, 6 analyzed the effects of specific adherence predictors (eg, symptom severity or type of technological interface) on the effects of the intervention, 4 administered poststudy feedback questionnaires to assess continued use of the intervention, and 2 studies evaluated the effects of different types of interventions on adherence. Overall, the percentage of participants adhering to interventions ranged from 28-100\% with a mean of 83\%. Adherence was greater in studies with higher levels of social support and service user involvement in the development of the intervention. Studies of shorter duration also had higher rates of adherence. Conclusions: Adherence to mobile and Web-based interventions was robust across most studies. Although 2 studies found specific predictors of nonadherence (male gender and younger age), most did not specifically analyze predictors. The duration of the study may be an important predictor of adherence. Future studies should consider reporting a universal measure of adherence and aim to conduct complex analyses on predictors of adherence such as level of social presence and service user involvement. ", doi="10.2196/mhealth.7088", url="http://mhealth.jmir.org/2017/7/e94/", url="http://www.ncbi.nlm.nih.gov/pubmed/28729235" } @Article{info:doi/10.2196/mhealth.7141, author="Kim, YB Ben and Lee, Joon", title="Smart Devices for Older Adults Managing Chronic Disease: A Scoping Review", journal="JMIR Mhealth Uhealth", year="2017", month="May", day="23", volume="5", number="5", pages="e69", keywords="mobile health", keywords="mHealth", keywords="smartphone", keywords="mobile phone", keywords="tablet", keywords="older adults", keywords="seniors", keywords="chronic disease", keywords="chronic disease management", keywords="scoping review", abstract="Background: The emergence of smartphones and tablets featuring vastly advancing functionalities (eg, sensors, computing power, interactivity) has transformed the way mHealth interventions support chronic disease management for older adults. Baby boomers have begun to widely adopt smart devices and have expressed their desire to incorporate technologies into their chronic care. Although smart devices are actively used in research, little is known about the extent, characteristics, and range of smart device-based interventions. Objective: We conducted a scoping review to (1) understand the nature, extent, and range of smart device-based research activities, (2) identify the limitations of the current research and knowledge gap, and (3) recommend future research directions. Methods: We used the Arksey and O'Malley framework to conduct a scoping review. We identified relevant studies from MEDLINE, Embase, CINAHL, and Web of Science databases using search terms related to mobile health, chronic disease, and older adults. Selected studies used smart devices, sampled older adults, and were published in 2010 or after. The exclusion criteria were sole reliance on text messaging (short message service, SMS) or interactive voice response, validation of an electronic version of a questionnaire, postoperative monitoring, and evaluation of usability. We reviewed references. We charted quantitative data and analyzed qualitative studies using thematic synthesis. To collate and summarize the data, we used the chronic care model. Results: A total of 51 articles met the eligibility criteria. Research activity increased steeply in 2014 (17/51, 33\%) and preexperimental design predominated (16/50, 32\%). Diabetes (16/46, 35\%) and heart failure management (9/46, 20\%) were most frequently studied. We identified diversity and heterogeneity in the collection of biometrics and patient-reported outcome measures within and between chronic diseases. Across studies, we found 8 self-management supporting strategies and 4 distinct communication channels for supporting the decision-making process. In particular, self-monitoring (38/40, 95\%), automated feedback (15/40, 38\%), and patient education (13/40, 38\%) were commonly used as self-management support strategies. Of the 23 studies that implemented decision support strategies, clinical decision making was delegated to patients in 10 studies (43\%). The impact on patient outcomes was consistent with studies that used cellular phones. Patients with heart failure and asthma reported improved quality of life. Qualitative analysis yielded 2 themes of facilitating technology adoption for older adults and 3 themes of barriers. Conclusions: Limitations of current research included a lack of gerontological focus, dominance of preexperimental design, narrow research scope, inadequate support for participants, and insufficient evidence for clinical outcome. Recommendations for future research include generating evidence for smart device-based programs, using patient-generated data for advanced data mining techniques, validating patient decision support systems, and expanding mHealth practice through innovative technologies. ", doi="10.2196/mhealth.7141", url="http://mhealth.jmir.org/2017/5/e69/", url="http://www.ncbi.nlm.nih.gov/pubmed/28536089" } @Article{info:doi/10.2196/jmir.7428, author="Gibson, G. Dustin and Pereira, Amanda and Farrenkopf, A. Brooke and Labrique, B. Alain and Pariyo, W. George and Hyder, A. Adnan", title="Mobile Phone Surveys for Collecting Population-Level Estimates in Low- and Middle-Income Countries: A Literature Review", journal="J Med Internet Res", year="2017", month="May", day="05", volume="19", number="5", pages="e139", keywords="survey methodology", keywords="cellular phone", keywords="interactive voice response", keywords="short messages service", keywords="computer-assisted telephone interview", keywords="mobile phone surveys", abstract="Background: National and subnational level surveys are important for monitoring disease burden, prioritizing resource allocation, and evaluating public health policies. As mobile phone access and ownership become more common globally, mobile phone surveys (MPSs) offer an opportunity to supplement traditional public health household surveys. Objective: The objective of this study was to systematically review the current landscape of MPSs to collect population-level estimates in low- and middle-income countries (LMICs). Methods: Primary and gray literature from 7 online databases were systematically searched for studies that deployed MPSs to collect population-level estimates. Titles and abstracts were screened on primary inclusion and exclusion criteria by two research assistants. Articles that met primary screening requirements were read in full and screened for secondary eligibility criteria. Articles included in review were grouped into the following three categories by their survey modality: (1) interactive voice response (IVR), (2) short message service (SMS), and (3) human operator or computer-assisted telephone interviews (CATI). Data were abstracted by two research assistants. The conduct and reporting of the review conformed to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Results: A total of 6625 articles were identified through the literature review. Overall, 11 articles were identified that contained 19 MPS (CATI, IVR, or SMS) surveys to collect population-level estimates across a range of topics. MPSs were used in Latin America (n=8), the Middle East (n=1), South Asia (n=2), and sub-Saharan Africa (n=8). Nine articles presented results for 10 CATI surveys (10/19, 53\%). Two articles discussed the findings of 6 IVR surveys (6/19, 32\%). Three SMS surveys were identified from 2 articles (3/19, 16\%). Approximately 63\% (12/19) of MPS were delivered to mobile phone numbers collected from previously administered household surveys. The majority of MPS (11/19, 58\%) were panel surveys where a cohort of participants, who often were provided a mobile phone upon a face-to-face enrollment, were surveyed multiple times. Conclusions: Very few reports of population-level MPS were identified. Of the MPS that were identified, the majority of surveys were conducted using CATI. Due to the limited number of identified IVR and SMS surveys, the relative advantages and disadvantages among the three survey modalities cannot be adequately assessed. The majority of MPS were sent to mobile phone numbers that were collected from a previously administered household survey. There is limited evidence on whether a random digit dialing (RDD) approach or a simple random sample of mobile network provided list of numbers can produce a population representative survey. ", doi="10.2196/jmir.7428", url="http://www.jmir.org/2017/5/e139/", url="http://www.ncbi.nlm.nih.gov/pubmed/28476725" } @Article{info:doi/10.2196/mhealth.6309, author="Bonoto, Cezar Br{\'a}ulio and de Ara{\'u}jo, Eloisa V{\^a}nia and God{\'o}i, Piassi Isabella and de Lemos, Pires L{\'i}via Lovato and Godman, Brian and Bennie, Marion and Diniz, Mauricio Leonardo and Junior, Guerra Augusto Afonso", title="Efficacy of Mobile Apps to Support the Care of Patients With Diabetes Mellitus: A Systematic Review and Meta-Analysis of Randomized Controlled Trials", journal="JMIR Mhealth Uhealth", year="2017", month="Mar", day="01", volume="5", number="3", pages="e4", keywords="diabetes mellitus", keywords="self-care", keywords="mobile applications", keywords="telemedicine", abstract="Background: Diabetes Mellitus (DM) is a chronic disease that is considered a global public health problem. Education and self-monitoring by diabetic patients help to optimize and make possible a satisfactory metabolic control enabling improved management and reduced morbidity and mortality. The global growth in the use of mobile phones makes them a powerful platform to help provide tailored health, delivered conveniently to patients through health apps. Objective: The aim of our study was to evaluate the efficacy of mobile apps through a systematic review and meta-analysis to assist DM patients in treatment. Methods: We conducted searches in the electronic databases MEDLINE (Pubmed), Cochrane Register of Controlled Trials (CENTRAL), and LILACS (Latin American and Caribbean Health Sciences Literature), including manual search in references of publications that included systematic reviews, specialized journals, and gray literature. We considered eligible randomized controlled trials (RCTs) conducted after 2008 with participants of all ages, patients with DM, and users of apps to help manage the disease. The meta-analysis of glycated hemoglobin (HbA1c) was performed in Review Manager software version 5.3. Results: The literature search identified 1236 publications. Of these, 13 studies were included that evaluated 1263 patients. In 6 RCTs, there were a statistical significant reduction (P<.05) of HbA1c at the end of studies in the intervention group. The HbA1c data were evaluated by meta-analysis with the following results (mean difference, MD ?0.44; CI: ?0.59 to ?0.29; P<.001; I{\texttwosuperior}=32\%).The evaluation favored the treatment in patients who used apps without significant heterogeneity. Conclusions: The use of apps by diabetic patients could help improve the control of HbA1c. In addition, the apps seem to strengthen the perception of self-care by contributing better information and health education to patients. Patients also become more self-confident to deal with their diabetes, mainly by reducing their fear of not knowing how to deal with potential hypoglycemic episodes that may occur. ", doi="10.2196/mhealth.6309", url="http://mhealth.jmir.org/2017/3/e4/", url="http://www.ncbi.nlm.nih.gov/pubmed/28249834" } @Article{info:doi/10.2196/mhealth.5720, author="Pham, Quynh and Wiljer, David and Cafazzo, A. Joseph", title="Beyond the Randomized Controlled Trial: A Review of Alternatives in mHealth Clinical Trial Methods", journal="JMIR Mhealth Uhealth", year="2016", month="Sep", day="09", volume="4", number="3", pages="e107", keywords="mobile health", keywords="mobile applications", keywords="smartphones", keywords="medical informatics", keywords="research design", keywords="clinical trials", abstract="Background: Randomized controlled trials (RCTs) have long been considered the primary research study design capable of eliciting causal relationships between health interventions and consequent outcomes. However, with a prolonged duration from recruitment to publication, high-cost trial implementation, and a rigid trial protocol, RCTs are perceived as an impractical evaluation methodology for most mHealth apps. Objective: Given the recent development of alternative evaluation methodologies and tools to automate mHealth research, we sought to determine the breadth of these methods and the extent that they were being used in clinical trials. Methods: We conducted a review of the ClinicalTrials.gov registry to identify and examine current clinical trials involving mHealth apps and retrieved relevant trials registered between November 2014 and November 2015. Results: Of the 137 trials identified, 71 were found to meet inclusion criteria. The majority used a randomized controlled trial design (80\%, 57/71). Study designs included 36 two-group pretest-posttest control group comparisons (51\%, 36/71), 16 posttest-only control group comparisons (23\%, 16/71), 7 one-group pretest-posttest designs (10\%, 7/71), 2 one-shot case study designs (3\%, 2/71), and 2 static-group comparisons (3\%, 2/71). A total of 17 trials included a qualitative component to their methodology (24\%, 17/71). Complete trial data collection required 20 months on average to complete (mean 21, SD 12). For trials with a total duration of 2 years or more (31\%, 22/71), the average time from recruitment to complete data collection (mean 35 months, SD 10) was 2 years longer than the average time required to collect primary data (mean 11, SD 8). Trials had a moderate sample size of 112 participants. Two trials were conducted online (3\%, 2/71) and 7 trials collected data continuously (10\%, 7/68). Onsite study implementation was heavily favored (97\%, 69/71). Trials with four data collection points had a longer study duration than trials with two data collection points: F4,56=3.2, P=.021, $\eta$2=0.18. Single-blinded trials had a longer data collection period compared to open trials: F2,58=3.8, P=.028, $\eta$2=0.12. Academic sponsorship was the most common form of trial funding (73\%, 52/71). Trials with academic sponsorship had a longer study duration compared to industry sponsorship: F2,61=3.7, P=.030, $\eta$2=0.11. Combined, data collection frequency, study masking, sample size, and study sponsorship accounted for 32.6\% of the variance in study duration: F4,55=6.6, P<.01, adjusted r2=.33. Only 7 trials had been completed at the time this retrospective review was conducted (10\%, 7/71). Conclusions: mHealth evaluation methodology has not deviated from common methods, despite the need for more relevant and timely evaluations. There is a need for clinical evaluation to keep pace with the level of innovation of mHealth if it is to have meaningful impact in informing payers, providers, policy makers, and patients. ", doi="10.2196/mhealth.5720", url="http://mhealth.jmir.org/2016/3/e107/", url="http://www.ncbi.nlm.nih.gov/pubmed/27613084" } @Article{info:doi/10.2196/mhealth.5127, author="Matthew-Maich, Nancy and Harris, Lauren and Ploeg, Jenny and Markle-Reid, Maureen and Valaitis, Ruta and Ibrahim, Sarah and Gafni, Amiram and Isaacs, Sandra", title="Designing, Implementing, and Evaluating Mobile Health Technologies for Managing Chronic Conditions in Older Adults: A Scoping Review", journal="JMIR mHealth uHealth", year="2016", month="Jun", day="09", volume="4", number="2", pages="e29", keywords="Telemedicine", keywords="Mobile health", keywords="Health Plan Implementations", keywords="Evaluation Studies as Topic", keywords="Design", keywords="mHealth Innovations", keywords="Frail Elderly", keywords="Older Adults", keywords="Multiple Chronic Conditions", keywords="Home Care Services", keywords="Scoping Review", keywords="Communication", keywords="Information Communication Technologies", abstract="Background: The current landscape of a rapidly aging population accompanied by multiple chronic conditions presents numerous challenges to optimally support the complex needs of this group. Mobile health (mHealth) technologies have shown promise in supporting older persons to manage chronic conditions; however, there remains a dearth of evidence-informed guidance to develop such innovations. Objectives: The purpose of this study was to conduct a scoping review of current practices and recommendations for designing, implementing, and evaluating mHealth technologies to support the management of chronic conditions in community-dwelling older adults. Methods: A 5-stage scoping review methodology was used to map the relevant literature published between January 2005 and March 2015 as follows: (1) identified the research question, (2) identified relevant studies, (3) selected relevant studies for review, (4) charted data from selected literature, and (5) summarized and reported results. Electronic searches were conducted in 5 databases. In addition, hand searches of reference lists and a key journal were completed. Inclusion criteria were research and nonresearch papers focused on mHealth technologies designed for use by community-living older adults with at least one chronic condition, or health care providers or informal caregivers providing care in the home and community setting. Two reviewers independently identified articles for review and extracted data. Results: We identified 42 articles that met the inclusion criteria. Of these, described innovations focused on older adults with specific chronic conditions (n=17), chronic conditions in general (n=6), or older adults in general or those receiving homecare services (n=18). Most of the mHealth solutions described were designed for use by both patients and health care providers or health care providers only. Thematic categories identified included the following: (1) practices and considerations when designing mHealth technologies; (2) factors that support/hinder feasibility, acceptability, and usability of mHealth technologies; and (3) approaches or methods for evaluating mHealth technologies. Conclusions: There is limited yet increasing use of mHealth technologies in home health care for older adults. A user-centered, collaborative, interdisciplinary approach to enhance feasibility, acceptability, and usability of mHealth innovations is imperative. Creating teams with the required pools of expertise and insight regarding needs is critical. The cyclical, iterative process of developing mHealth innovations needs to be viewed as a whole with supportive theoretical frameworks. Many barriers to implementation and sustainability have limited the number of successful, evidence-based mHealth solutions beyond the pilot or feasibility stage. The science of implementation of mHealth technologies in home-based care for older adults and self-management of chronic conditions are important areas for further research. Additionally, changing needs as cohorts and technologies advance are important considerations. Lessons learned from the data and important implications for practice, policy, and research are discussed to inform the future development of innovations. ", doi="10.2196/mhealth.5127", url="http://mhealth.jmir.org/2016/2/e29/", url="http://www.ncbi.nlm.nih.gov/pubmed/27282195" } @Article{info:doi/10.2196/mhealth.3216, author="Nhavoto, Ant{\'o}nio Jos{\'e} and Gr{\"o}nlund, {\AA}ke", title="Mobile Technologies and Geographic Information Systems to Improve Health Care Systems: A Literature Review", journal="JMIR mHealth uHealth", year="2014", month="May", day="08", volume="2", number="2", pages="e21", keywords="health care", keywords="eHealth", keywords="mobile technology", keywords="mobile phone", keywords="SMS", keywords="text messaging", keywords="geographic information system", keywords="GIS", abstract="Background: A growing body of research has employed mobile technologies and geographic information systems (GIS) for enhancing health care and health information systems, but there is yet a lack of studies of how these two types of systems are integrated together into the information infrastructure of an organization so as to provide a basis for data analysis and decision support. Integration of data and technical systems across the organization is necessary for efficient large-scale implementation. Objective: The aim of this paper is to identify how mobile technologies and GIS applications have been used, independently as well as in combination, for improving health care. Methods: The electronic databases PubMed, BioMed Central, Wiley Online Library, Scopus, Science Direct, and Web of Science were searched to retrieve English language articles published in international academic journals after 2005. Only articles addressing the use of mobile or GIS technologies and that met a prespecified keyword strategy were selected for review. Results: A total of 271 articles were selected, among which 220 concerned mobile technologies and 51 GIS. Most articles concern developed countries (198/271, 73.1\%), and in particular the United States (81/271, 29.9\%), United Kingdom (31/271, 11.4\%), and Canada (14/271, 5.2\%). Applications of mobile technologies can be categorized by six themes: treatment and disease management, data collection and disease surveillance, health support systems, health promotion and disease prevention, communication between patients and health care providers or among providers, and medical education. GIS applications can be categorized by four themes: disease surveillance, health support systems, health promotion and disease prevention, and communication to or between health care providers. Mobile applications typically focus on using text messaging (short message service, SMS) for communication between patients and health care providers, most prominently reminders and advice to patients. These applications generally have modest benefits and may be appropriate for implementation. Integration of health data using GIS technology also exhibit modest benefits such as improved understanding of the interplay of psychological, social, environmental, area-level, and sociodemographic influences on physical activity. The studies evaluated showed promising results in helping patients treating different illnesses and managing their condition effectively. However, most studies use small sample sizes and short intervention periods, which means limited clinical or statistical significance. Conclusions: A vast majority of the papers report positive results, including retention rate, benefits for patients, and economic gains for the health care provider. However, implementation issues are little discussed, which means the reasons for the scarcity of large-scale implementations, which might be expected given the overwhelmingly positive results, are yet unclear. There is also little combination between GIS and mobile technologies. In order for health care processes to be effective they must integrate different kinds of existing technologies and data. Further research and development is necessary to provide integration and better understand implementation issues. ", doi="10.2196/mhealth.3216", url="http://mhealth.jmir.org/2014/2/e21/", url="http://www.ncbi.nlm.nih.gov/pubmed/25099368" } @Article{info:doi/10.2196/mhealth.2688, author="Goel, Sonu and Bhatnagar, Nidhi and Sharma, Deepak and Singh, Amarjeet", title="Bridging the Human Resource Gap in Primary Health Care Delivery Systems of Developing Countries With mHealth: Narrative Literature Review", journal="JMIR Mhealth Uhealth", year="2013", month="Dec", day="03", volume="1", number="2", pages="e25", keywords="mHealth", keywords="human resource", keywords="health", keywords="developing countries", keywords="projects", abstract="Background: Mobile health (mHealth) has the potential to solve human resource issues in the health care sector. mHealth is of particular interest in developing countries, where widespread mobile networks and access to devices are connecting people like never before. Objective: The aim of this paper was to review published and unpublished literature, field projects, and pilot studies on mHealth usage in overcoming shortage of human health resources in developing countries. Methods: A narrative literature review was undertaken using an iterative approach in extracting literature focused on mHealth and human health resources of low-income countries, especially India. The present review has undertaken comprehensive coverage of the work on related field projects that have been either published, accepted for publication, or pilot tested. Results: This review presented the use of mHealth across various dimensions of primary health care, including data collection, disease surveillance, health education, supervision, monitoring, and feedback. Field studies of fast, error-free data collection and transmission using mHealth were also documented. New apps for supervision, monitoring, and utilization of innovative health education tools were documented in the current review. Practical limitations of mHealth and challenges set forth in developing countries included issues of data security, cost constraints, health provider privacy, and technical barriers. Conclusions: In the present review, we have documented a few mHealth projects that contribute to the proficient use of human resources. These projects pave the path for the efficient utilization of mHealth, offering solutions to emerging human resource challenges and simultaneously revamping the health care delivery in resource-limited settings. ", doi="10.2196/mhealth.2688", url="http://mhealth.jmir.org/2013/2/e25/", url="http://www.ncbi.nlm.nih.gov/pubmed/25099436" }