%0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e17281 %T Prescribing Behavior Change: Opportunities and Challenges for Clinicians to Embrace Digital and Mobile Health %A Agarwal,Anish %A Patel,Mitesh %+ Department of Emergency Medicine, University of Pennsylvania, Blockley Hall, Room 428, 423 Guardian Drive, Philadelphia, PA, 19146, United States, 1 610 304 2318, anish.agarwal@pennmedicine.upenn.edu %K digital health %K behavior change %K mobile health %K patient-centered data collection %D 2020 %7 4.8.2020 %9 Viewpoint %J JMIR Mhealth Uhealth %G English %X Individual behaviors impact physical and mental health. Everyday behaviors such as physical activity, diet, sleep, and tobacco use have been associated with a range of acute and chronic medical conditions. Educating, motivating, and promoting sustained healthy behaviors can be challenging for clinical providers attempting to manage their patients’ health. The ubiquity and integration of mobile and digital health devices (eg, wearable step counters, smartphone-based apps) allow for individuals to generate and record enormous amounts of patient-generated health data. Research studies have begun to reveal how mobile and digital devices offer promise in motivating individual behavior change but they have not had consistent results. In this viewpoint, we discuss the potential synergy of digital health modalities and behavioral strategies as an approach for clinicians to prescribe, motivate, monitor, and sustain healthy behaviors. We discuss the strengths, challenges, and opportunities for the future of promoting health behaviors. %M 32749997 %R 10.2196/17281 %U https://mhealth.jmir.org/2020/8/e17281 %U https://doi.org/10.2196/17281 %U http://www.ncbi.nlm.nih.gov/pubmed/32749997 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e15779 %T 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 %A Liu,Kaifeng %A Xie,Zhenzhen %A Or,Calvin Kalun %+ Department of Industrial and Manufacturing Systems Engineering, University of Hong Kong, Room 8-7, 8/f., Haking Wong Building,, University of Hong Kong, Hong Kong, Hong Kong, 852 39172587, klor@hku.hk %K mobile app %K type 2 diabetes %K hypertension %K self-care %D 2020 %7 4.8.2020 %9 Review %J JMIR Mhealth Uhealth %G English %X 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. %M 32459654 %R 10.2196/15779 %U http://mhealth.jmir.org/2020/8/e15779/ %U https://doi.org/10.2196/15779 %U http://www.ncbi.nlm.nih.gov/pubmed/32459654 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e13179 %T Communication Technology Use by Caregivers of Adolescents With Mental Health Issues: Systematic Review %A Jansen,Ronelle %A Reid,Marianne %+ School of Nursing, Faculty of Health Science, University of the Free State, 205 Nelson Mandela Drive, Bloemfontein, 9301, South Africa, 27 825544731, jansenro@ufs.ac.za %K caregiver %K communication technology %K adolescent %K mental health issues %K systematic review %K self-efficacy, knowledge %K parental skills %K IMBP %D 2020 %7 19.8.2020 %9 Review %J JMIR Mhealth Uhealth %G English %X 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. %M 32663143 %R 10.2196/13179 %U http://mhealth.jmir.org/2020/8/e13179/ %U https://doi.org/10.2196/13179 %U http://www.ncbi.nlm.nih.gov/pubmed/32663143 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e15947 %T Complementing Human Behavior Assessment by Leveraging Personal Ubiquitous Devices and Social Links: An Evaluation of the Peer-Ceived Momentary Assessment Method %A Berrocal,Allan %A Concepcion,Waldo %A De Dominicis,Stefano %A Wac,Katarzyna %+ Quality of Life Technologies Lab, Department of Computer Science, University of Geneva, Route de Drize 7, Carouge, 1227, Switzerland, 41 222790242, wac@stanford.edu %K peer-ceived momentary assessment %K PeerMA %K ecological momentary assessment %K EMA %K human state assessment %K behavior modeling %K human-smartphone interaction %K digital health %K well-being %K mobile phone %D 2020 %7 7.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Ecological momentary assessment (EMA) enables individuals to self-report their subjective momentary physical and emotional states. However, certain conditions, including routine observable behaviors (eg, moods, medication adherence) as well as behaviors that may suggest declines in physical or mental health (eg, memory losses, compulsive disorders) cannot be easily and reliably measured via self-reports. Objective: This study aims to examine a method complementary to EMA, denoted as peer-ceived momentary assessment (PeerMA), which enables the involvement of peers (eg, family members, friends) to report their perception of the individual’s subjective physical and emotional states. In this paper, we aim to report the feasibility results and identified human factors influencing the acceptance and reliability of the PeerMA Methods: We conducted two studies of 4 weeks each, collecting self-reports from 20 participants about their stress, fatigue, anxiety, and well-being, in addition to collecting peer-reported perceptions from 27 of their peers. Results: Preliminary results showed that some of the peers reported daily assessments for stress, fatigue, anxiety, and well-being statistically equal to those reported by the participant. We also showed how pairing assessments of participants and peers in time enables a qualitative and quantitative exploration of unique research questions not possible with EMA-only based assessments. We reported on the usability and implementation aspects based on the participants’ experience to guide the use of the PeerMA to complement the information obtained via self-reports for observable behaviors and physical and emotional states among healthy individuals. Conclusions: It is possible to leverage the PeerMA method as a complement to EMA to assess constructs that fall in the realm of observable behaviors and states in healthy individuals. %M 32763876 %R 10.2196/15947 %U https://mhealth.jmir.org/2020/8/e15947 %U https://doi.org/10.2196/15947 %U http://www.ncbi.nlm.nih.gov/pubmed/32763876 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e17754 %T Sensory-Discriminative Three-Dimensional Body Pain Mobile App Measures Versus Traditional Pain Measurement With a Visual Analog Scale: Validation Study %A Kaciroti,Niko %A DosSantos,Marcos Fabio %A Moura,Brenda %A Bellile,Emily Light %A Nascimento,Thiago Dias %A Maslowski,Eric %A Danciu,Theodora E %A Donnell,Adam %A DaSilva,Alexandre F %+ Headache & Orofacial Pain Effort (H.O.P.E.), Department of Biologic and Materials Sciences, School of Dentistry, University of Michigan, 1011 N. University Ave., Room 1014A,, Ann Arbor, MI, 48109-1078, United States, 1 (734) 615 3807, adasilva@umich.edu %K pain measurement %K chronic pain %K migraine %K visual analog scale %K facial pain %D 2020 %7 19.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: To quantify pain severity in patients and the efficacy treatments, researchers and clinicians apply tools such as the traditional visual analog scale (VAS) that leads to inaccurate interpretation of the main sensory pain. Objective: This study aimed to validate the pain measurements of a neuroscience-based 3D body pain mobile app called GeoPain. Methods: Patients with temporomandibular disorder (TMD) were assessed using GeoPain measures in comparison to VAS and positive and negative affect schedule (PANAS), pain and mood scales, respectively. Principal component analysis (PCA), scatter score analysis, Pearson methods, and effect size were used to determine the correlation between GeoPain and VAS measures. Results: The PCA resulted in two main orthogonal components: first principal component (PC1) and second principal component (PC2). PC1 comprises a combination score of all GeoPain measures, which had a high internal consistency and clustered together in TMD pain. PC2 included VAS and PANAS. All loading coefficients for GeoPain measures in PC1 were above 0.70, with low loadings for VAS and PANAS. Meanwhile, PC2 was dominated by a VAS and PANAS coefficient >0.4. Repeated measure analysis revealed a strong correlation between the VAS and mood scores from PANAS over time, which might be related to the subjectivity of the VAS measure, whereas sensory-discriminative GeoPain measures, not VAS, demonstrated an association between chronicity and TMD pain in locations spread away from the most commonly reported area or pain epicenter (P=.01). Analysis using VAS did not detect an association at baseline between TMD and chronic pain. The long-term reliability (lag >1 day) was consistently high for the pain area and intensity number summation (PAINS) with lag autocorrelations averaging between 0.7 and 0.8, and greater than the autocorrelations for VAS averaging between 0.3 and 0.6. The combination of higher reliability for PAINS and its objectivity, displayed by the lack of association with PANAS as compared with VAS, indicated that PAINS has better sensitivity and reliability for measuring treatment effect over time for sensory-discriminative pain. The effect sizes for PAINS were larger than those for VAS, consequently requiring smaller sample sizes to assess the analgesic efficacy of treatment if PAINS was used versus VAS. The PAINS effect size was 0.51 SD for both facial sides and 0.60 SD for the right side versus 0.35 SD for VAS. Therefore, the sample size required to detect such effect sizes with 80% power would be n=125 per group for VAS, but as low as n=44 per group for PAINS, which is almost a third of the sample size needed by VAS. Conclusions: GeoPain demonstrates precision and reliability as a 3D mobile interface for measuring and analyzing sensory-discriminative aspects of subregional pain in terms of its severity and response to treatment, without being influenced by mood variations from patients. %M 32124732 %R 10.2196/17754 %U https://mhealth.jmir.org/2020/8/e17754 %U https://doi.org/10.2196/17754 %U http://www.ncbi.nlm.nih.gov/pubmed/32124732 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e15284 %T Comparing a Mobile Phone Automated System With a Paper and Email Data Collection System: Substudy Within a Randomized Controlled Trial %A Bond,Diana M %A Hammond,Jeremy %A Shand,Antonia W %A Nassar,Natasha %+ Sydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Level 2, Charles Perkins Centre D17, Sydney, 2006, Australia, 61 2 9036 7006, diana.bond@sydney.edu.au %K mobile phones %K text messaging %K data collection methods %K clinical trial %K breastfeeding %K maternal health %D 2020 %7 25.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Traditional data collection methods using paper and email are increasingly being replaced by data collection using mobile phones, although there is limited evidence evaluating the impact of mobile phone technology as part of an automated research management system on data collection and health outcomes. Objective: The aim of this study is to compare a web-based mobile phone automated system (MPAS) with a more traditional delivery and data collection system combining paper and email data collection (PEDC) in a cohort of breastfeeding women. Methods: We conducted a substudy of a randomized controlled trial in Sydney, Australia, which included women with uncomplicated term births who intended to breastfeed. Women were recruited within 72 hours of giving birth. A quasi-randomized number of women were recruited using the PEDC system, and the remainder were recruited using the MPAS. The outcomes assessed included the effectiveness of data collection, impact on study outcomes, response rate, acceptability, and cost analysis between the MPAS and PEDC methods. Results: Women were recruited between April 2015 and December 2016. The analysis included 555 women: 471 using the MPAS and 84 using the PEDC. There were no differences in clinical outcomes between the 2 groups. At the end of the 8-week treatment phase, the MPAS group showed an increased response rate compared with the PEDC group (56% vs 37%; P<.001), which was also seen at the 2-, 6-, and 12-month follow-ups. At the 2-month follow-up, the MPAS participants also showed an increased rate of self-reported treatment compliance (70% vs 56%; P<.001) and a higher recommendation rate for future use (95% vs 64%; P<.001) as compared with the PEDC group. The cost analysis between the 2 groups was comparable. Conclusions: MPAS is an effective and acceptable method for improving the overall management, treatment compliance, and methodological quality of clinical research to ensure the validity and reliability of findings. %M 32763873 %R 10.2196/15284 %U http://mhealth.jmir.org/2020/8/e15284/ %U https://doi.org/10.2196/15284 %U http://www.ncbi.nlm.nih.gov/pubmed/32763873 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e17193 %T Evaluating a Theoretically Informed and Cocreated Mobile Health Educational Intervention for First-Time Hearing Aid Users: Qualitative Interview Study %A Maidment,David W %A Heyes,Rachel %A Gomez,Rachel %A Coulson,Neil S %A Wharrad,Heather %A Ferguson,Melanie A %+ School of Sport, Exercise and Health Sciences, Loughborough University, Epinal Way, Loughborough, LE11 3TU, United Kingdom, 44 1509225439, D.W.Maidment@lboro.ac.uk %K hearing loss %K hearing aids %K telemedicine %K behavioral medicine %K qualitative research %K mobile phone %D 2020 %7 5.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Adults living with hearing loss have highly variable knowledge of hearing aids, resulting in suboptimal use or nonuse. This issue can be addressed by the provision of high-quality educational resources. Objective: This study aims to assess the everyday experiences of first-time hearing aid users when using a newly developed, theoretically informed cocreated mobile health (mHealth) educational intervention called m2Hear. This intervention aims to deliver greater opportunities for individualization and interactivity compared with our previously developed multimedia intervention, C2Hear. Methods: A total of 16 first-time hearing aid users trialed m2Hear for a period of 10-weeks in their everyday lives, after which individual semistructured interviews were completed. The data were analyzed using an established deductive thematic analysis procedure underpinned by the Capability, Opportunity, Motivation-Behavior model. The model stipulates that to engage in a target behavior, an individual must have physical and psychological capability, physical and social opportunity, and automatic and reflective motivation. Results: Capability—m2Hear was viewed as a concise and comprehensive resource, suitable for a range of digital literacy skills. It was stated that m2Hear could be conveniently reused to provide useful reminders that facilitate knowledge of hearing aids and communication. Opportunity—m2Hear was simple and straightforward to use, enabling greater individualization and independence. The availability of m2Hear via mobile technologies also improved accessibility. Motivation—m2Hear provided greater support and reassurance, improving confidence and empowering users to self-manage their hearing loss. Conclusions: Overall, this qualitative study suggests that m2Hear supports first-time hearing aid users to successfully self-manage their hearing loss postfitting. Furthermore, this study demonstrates the utility of employing a combined theoretical and ecologically valid approach in the development of mHealth educational resources to meet the individual self-management needs of adults living with hearing loss. Trial Registration: ClinicalTrials.gov NCT03136718; https://clinicaltrials.gov/ct2/show/NCT03136718 %M 32755885 %R 10.2196/17193 %U https://mhealth.jmir.org/2020/8/e17193 %U https://doi.org/10.2196/17193 %U http://www.ncbi.nlm.nih.gov/pubmed/32755885 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e17709 %T Influence of Personality on mHealth Use in Patients with Diabetes: Prospective Pilot Study %A Su,Jingyuan %A Dugas,Michelle %A Guo,Xitong %A Gao,Guodong (Gordon) %+ eHealth Research Institute, School of Management, Harbin Institute of Technology, 92 West Dazhi Street, Nangang District, Harbin, , China, 86 451 86414022, xitongguo@hit.edu.cn %K mHealth %K diabetes %K adoption %K active utilization %K personality traits %K app %D 2020 %7 10.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Mobile technology for health (mHealth) interventions are increasingly being used to help improve self-management among patients with diabetes; however, these interventions have not been adopted by a large number of patients and often have high dropout rates. Patient personality characteristics may play a critical role in app adoption and active utilization, but few studies have focused on addressing this question. Objective: This study aims to address a gap in understanding of the relationship between personality traits and mHealth treatment for patients with diabetes. We tested the role of the five-factor model of personality traits (openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism) in mHealth adoption preference and active utilization. Methods: We developed an mHealth app (DiaSocial) aimed to encourage diabetes self-management. We recruited 98 patients with diabetes—each patient freely chose whether to receive the standard care or the mHealth app intervention. Patient demographic information and patient personality characteristics were assessed at baseline. App usage data were collected to measure user utilization of the app. Patient health outcomes were assessed with lab measures of glycated hemoglobin (HbA1c level). Logistic regression models and linear regression were employed to explore factors predicting the relationship between mHealth use (adoption and active utilization) and changes in health outcome. Results: Of 98 study participants, 46 (47%) downloaded and used the app. Relatively younger patients with diabetes were 9% more likely to try and use the app (P=.02, odds ratio [OR] 0.91, 95% CI 0.85-0.98) than older patients with diabetes were. Extraversion was negatively associated with adoption of the mHealth app (P=.04, OR 0.71, 95% CI 0.51-0.98), and openness to experience was positively associated with adoption of the app (P=.03, OR 1.73, 95% CI 1.07-2.80). Gender (P=.43, OR 0.66, 95% CI 0.23-1.88), education (senior: P=.99, OR 1.00, 95% CI 0.32-3.11; higher: P=.21, OR 2.51, 95% CI 0.59-10.66), and baseline HbA1c level (P=.36, OR 0.79, 95% CI 0.47-1.31) were not associated with app adoption. Among those who adopted the app, a low education level (senior versus primary P=.003; higher versus primary P=.03) and a high level of openness to experience (P=.048, OR 2.01, 95% CI 1.01-4.00) were associated with active app utilization. Active users showed a significantly greater decrease in HbA1c level than other users (ΔHbA1c=−0.64, P=.05). Conclusions: This is one of the first studies to investigate how different personality traits influence the adoption and active utilization of an mHealth app among patients with diabetes. The research findings suggest that personality is a factor that should be considered when trying to identify patients who would benefit the most from apps for diabetes management. %M 32773382 %R 10.2196/17709 %U https://mhealth.jmir.org/2020/8/e17709 %U https://doi.org/10.2196/17709 %U http://www.ncbi.nlm.nih.gov/pubmed/32773382 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e19487 %T User Perceptions of Virtual Hospital Apps in China: Systematic Search %A Wang,Yuan %A Liu,Yuqiao %A Shi,Yancui %A Yu,Yanjun %A Yang,Jucheng %+ College of Artificial Intelligence, Tianjin University of Science and Technology, Room 316, Building 8, No 9, 13th Avenue, Binhai New District, Tianjin, China, 86 15602118875, jcyang@tust.edu.cn %K mobile apps %K mHealth %K remote consultation %K China %K app review analysis %K user intent %D 2020 %7 12.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Virtual hospital apps are mobile apps that offer functionalities of online consultation, medical guidance, health community forums, referrals, outpatient appointments or virtual hospital-to-home care services. With an increasing number of online medical and health care consulting services, virtual hospital apps have made health care more accessible and fairer for all, especially in China. However, they have occurred without control or regulation. User evaluation can provide directions to help apps optimize identification, lower risks, and guarantee service quality. Objective: We aimed to conduct a systematic search for virtual hospital apps in China. To get a global view, virtual hospital apps were assessed and characterized by means of quantitative analysis. To get a local view, we conducted a content feedback analysis to explore user requirements, expectations, and preferences. Methods: A search was conducted of the most popular Apple and Android app stores in China. We characterized and verified virtual hospital apps and grouped apps according to quantification analysis. We then crawled apps and paid attention to corresponding reviews to incorporate users’ involvement, and then performed aspect-based content labeling and analysis using an inductive approach. Results: A total of 239 apps were identified in the virtual hospital app markets in China, and 2686 informative corresponding reviews were analyzed. The evidence showed that usefulness and ease of use were vital facts for engagement. Users were likely to trust a consulting service with a high number of downloads. Furthermore, users expected frequently used apps with more optimization to improve virtual service. We characterized apps according to 4 key features: (1) app functionalities, including online doctor consultation, in-app purchases, tailored education, and community forums; (2) security and privacy, including user data management and user privacy; (3) health management, including health tracking, reminders, and notifications; and (4) technical aspects, including user interface and equipment connection. Conclusions: Virtual hospitals relying on the mobile internet are growing rapidly. A large number of virtual hospital apps are available and accessible to a growing number of people. Evidence from this systematic search can help various types of virtual hospital models enhance virtual health care experiences, go beyond offline hospitals, and continuously meet the needs of individual end users. %M 32687480 %R 10.2196/19487 %U http://mhealth.jmir.org/2020/8/e19487/ %U https://doi.org/10.2196/19487 %U http://www.ncbi.nlm.nih.gov/pubmed/32687480 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e15866 %T Designing an Information and Communications Technology Tool With and for Victims of Violence and Their Case Managers in San Francisco: Human-Centered Design Study %A Patel,Devika %A Sarlati,Siavash %A Martin-Tuite,Patrick %A Feler,Joshua %A Chehab,Lara %A Texada,Michael %A Marquez,Ruben %A Orellana,F Julia %A Henderson,Terrell L %A Nwabuo,Adaobi %A Plevin,Rebecca %A Dicker,Rochelle Ami %A Juillard,Catherine %A Sammann,Amanda %+ Department of Surgery, University of California, San Francisco, 1001 Potrero Ave, San Francisco, CA, 94110, United States, 1 (628) 206 3764, devika.patel@ucsf.edu %K human-centered design %K violence intervention %K information and communications technology %D 2020 %7 24.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Violence is a public health problem. Hospital-based violence intervention programs such as the San Francisco Wraparound Project (WAP) have been shown to reduce future violent injury. The WAP model employs culturally competent case managers who recruit and enroll violently injured patients as clients. Client acceptance of the WAP intervention is variable, and program success depends on streamlined, timely communication and access to resources. High rates of smartphone usage in populations who are at risk for violent reinjury create an opportunity to design a tailored information and communications technology (ICT) tool to support hospital-based violence intervention programs. Objective: Current evidence shows that ICT tools developed in the health care space may not be successful in engaging vulnerable populations. The goal of this study was to use human-centered design methodology to identify the unique communication needs of the clients and case managers at WAP to design a mobile ICT. Methods: We conducted 15 semi-structured interviews with users: clients, their friends and families, case managers, and other stakeholders in violence intervention and prevention. We used a human-centered design and general inductive approach to thematic analysis to identify themes in the qualitative data, which were extrapolated to insight statements and then reframed into design opportunities. Wireframes of potential mobile ICT app screens were developed to depict these opportunities. Results: Thematic analysis revealed four main insights that were characterized by the opposing needs of our users. (1) A successful relationship is both professional and personal. Clients need this around the clock, but case managers can only support this while on the clock. (2) Communications need to feel personal, but they do not always need to be personalized. (3) Healing is a journey of skill development and lifestyle changes that must be acknowledged, monitored, and rewarded. (4) Social networks need to provide peer support for healing rather than peer pressure to propagate violence. These insights resulted in the following associated design opportunities: (1) Maximize personal connection while controlling access, (2) allow case managers to personalize automated client interactions, (3) hold clients accountable to progress and reward achievements, and (4) build a connected, yet confidential community. Conclusions: Human-centered design enabled us to identify unique insights and design opportunities that may inform the design of a novel and tailored mobile ICT tool for the WAP community. %M 32831179 %R 10.2196/15866 %U http://mhealth.jmir.org/2020/8/e15866/ %U https://doi.org/10.2196/15866 %U http://www.ncbi.nlm.nih.gov/pubmed/32831179 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e17408 %T Mobile App for Symptom Management and Associated Quality of Life During Systemic Treatment in Early Stage Breast Cancer: Nonrandomized Controlled Prospective Cohort Study %A Grašič Kuhar,Cvetka %A Gortnar Cepeda,Tjaša %A Kovač,Timotej %A Kukar,Matjaž %A Ružić Gorenjec,Nina %+ Department of Medical Oncology, Institute of Oncology Ljubljana, Zaloška 2, Ljubljana, SI-1000, Slovenia, 386 1 5879 287, cgrasic@onko-i.si %K breast cancer %K systemic therapy %K mobile application %K patient-reported outcome %K quality of life %D 2020 %7 4.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Providing patients with cancer who are undergoing systemic therapy with useful information about symptom management is essential to prevent unnecessary deterioration of quality of life. Objective: The aim was to evaluate whether use of an app for symptom management was associated with any change in patient quality of life or use of health resources. Methods: Outpatients with early stage breast cancer receiving systemic therapy were recruited at the Institute of Oncology in Ljubljana, Slovenia. Patients who received systemic therapy between December 2017 and March 2018 (control group) and between April 2018 and September 2018 (intervention group) were eligible. All patients received standard care, but only those in the intervention group were asked to use mPRO Mamma, an Android-based smartphone app, in addition. The app supported daily tracking of 50 symptoms, allowed users to grade their symptom severity (as mild, moderate, or severe), and also provided in-depth descriptions and recommendations based on reported symptom level. Patient-reported outcomes in both groups were assessed through the European Organisation for Research and Treatment of Cancer (EORTC) core (C-30) and breast cancer (BR-23) questionnaires, as well as a questionnaire about health resources use. The primary outcomes were the difference in the global quality of life between groups and the difference in summary score of the EORTC C-30 questionnaire between groups after 3 time periods (the first week of treatment, the first treatment cycle, and the entire treatment). The secondary outcome was the use of health resources (doctor visits and hospitalizations) in each time period. Other scales were used for exploratory analysis. Results: The mean difference between the intervention group (n=46) and the control group (n=45) in global quality of life (adjusted for baseline and type of surgery) after the first week was 10.1 (95% CI 1.8 to 18.5, P=.02). The intervention group summary scores were significantly higher than those of the control group after the first week (adjusted mean difference: 8.9, 95% CI 3.1 to 14.7, P=.003) and at the end of treatment (adjusted mean difference: 10.6, 95% CI 3.9 to 17.3, P=.002). Use of health resources was not statistically significant between the groups in either the first week (P=.12) or the first treatment cycle (P=.13). Exploratory analysis findings demonstrated clinically important improvements (indicated by EORTC C-30 or BR-23 scale scores)—social, physical, role, and cognitive function were improved while pain, appetite loss, and systemic therapy side effects were reduced. Conclusions: Use of the app enabled patients undergoing systemic therapy for early stage breast cancer to better cope with symptoms which was demonstrated by a better global quality of life and summary score after the first week and by a better summary score at the end of treatment in the intervention group compared to those of the control group, but no change in the use of health resources was demonstrated. %M 32427567 %R 10.2196/17408 %U https://mhealth.jmir.org/2020/8/e17408 %U https://doi.org/10.2196/17408 %U http://www.ncbi.nlm.nih.gov/pubmed/32427567 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e18999 %T Developing a Heart Transplantation Self-Management Support Mobile Health App in Taiwan: Qualitative Study %A Chen,Yi-Wen %A Wei,Jeng %A Chen,Hwei-Ling %A Cheng,Ching-Hui %A Hou,I-Ching %+ School of Nursing, National Yang-Ming University, Nursing Building Room 407, Number 155, Section 2, Linong Street, Beitou District, Taipei, Taiwan, 886 28267000 ext 7315, evita@ym.edu.tw %K heart transplantation %K mobile health app %K self-management %D 2020 %7 19.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Heart transplantation (HTx) is the most effective treatment for end-stage heart failure patients. After transplantation, patients face physiological, psychological, social, and other health care problems. Mobile health (mHealth) apps can change the delivery of conventional health care to ubiquitous care and improve health care quality. However, a dearth of mHealth apps exists for patients with HTx worldwide, including in Taiwan. Objective: The aim of this study was to investigate the information needed and to develop a preliminary framework for an mHealth app for post-HTx patients. Methods: A qualitative approach with individual in-depth interviews was conducted at a heart center in the regional hospital of northern Taiwan from June to November 2017. Patients that had undergone HTx and their health professionals were recruited for purposeful sampling. A semistructured interview guideline was used for individual interviews and transcribed. Thematic analysis was used for data analysis. Results: A total of 21 subjects, including 17 patients and 4 health professionals, were recruited for the study. The following five major themes were identified: reminding, querying, experience sharing, diet, and expert consulting. Minor themes included a desire to use the app with artificial intelligence and integration with professional management. Conclusions: An intelligent mHealth app that addresses the five main themes and integrates the processes of using a mobile app could facilitate HTx self-management for Taiwanese patients. %M 32812883 %R 10.2196/18999 %U http://mhealth.jmir.org/2020/8/e18999/ %U https://doi.org/10.2196/18999 %U http://www.ncbi.nlm.nih.gov/pubmed/32812883 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e18506 %T Beneficial Features of a mHealth Asthma App for Children and Caregivers: Qualitative Study %A Iio,Misa %A Miyaji,Yumiko %A Yamamoto-Hanada,Kiwako %A Narita,Masami %A Nagata,Mayumi %A Ohya,Yukihiro %+ College of Nursing, Kanto Gakuin University, 1-50-1 Mutsuurahigashi, Kanazawa-ku, Yokohama, 236-8503, Japan, 81 45 786 5641, misaiio@kanto-gakuin.ac.jp %K children %K caregivers %K asthma %K mobile app %K proposed beneficial features %D 2020 %7 24.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: mHealth and uHealth apps are available for children with asthma and their caregivers. However, previous studies on mHealth apps for children older than 7 years old with asthma are limited, and most studies on asthma apps do not consider interactions involving communication between children and caregivers. Therefore, a prototype mHealth child asthma app was developed for children and their caregivers, with features of tailored feedback messages in continuing self-management and interactions between children and caregivers. Objective: The aim of this study was to identify the beneficial features of a prototype mHealth app developed for children with asthma and their caregivers. Methods: Children diagnosed with persistent asthma by allergy specialists at the National Center for Child Health and Development were recruited. The features of a prototype mHealth app for children with asthma and their caregivers were investigated using semistructured interviews after they tried the app. Data were analyzed using thematic analysis. Content-characteristic words were named and grouped together as categories to explore themes. Results: We recruited 27 children with asthma aged 2 to 12 years and 26 their caregivers. Findings on the good aspects of the app for children older than 7 years old and caregivers suggested 4 themes (confirmation of asthma knowledge, child-caregiver interaction, design of the app, and child’s interest), and 6 categories were identified. Findings on the good aspects of app for children 7 to 12 years old and caregivers suggested 5 themes (new knowledge, manga as a Japanese-style comic, child’s interest, trigger of self-management, and design and operability), and 11 categories were identified. Findings on the beneficial features of app suggested 6 themes (asthma knowledge, elements for continuous, universal design, notification, monitoring, and functions), and 12 categories were identified. Conclusions: Children with asthma and their caregivers perceived that the good aspects of the app were learning asthma knowledge with fun, including manga; interaction between child and caregiver; and easy-to-read design, such as colors. They wanted not only the asthma knowledge but also the universal design and enhanced elements, monitoring, and notification functions of the app. %M 32831181 %R 10.2196/18506 %U http://mhealth.jmir.org/2020/8/e18506/ %U https://doi.org/10.2196/18506 %U http://www.ncbi.nlm.nih.gov/pubmed/32831181 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e19962 %T Predicting Early Warning Signs of Psychotic Relapse From Passive Sensing Data: An Approach Using Encoder-Decoder Neural Networks %A Adler,Daniel A %A Ben-Zeev,Dror %A Tseng,Vincent W-S %A Kane,John M %A Brian,Rachel %A Campbell,Andrew T %A Hauser,Marta %A Scherer,Emily A %A Choudhury,Tanzeem %+ Cornell Tech, 2 W Loop Rd, New York, NY, 10044, United States, 1 2155953769, daa243@cornell.edu %K psychotic disorders %K schizophrenia %K mHealth %K mental health %K mobile health %K smartphone applications %K machine learning %K passive sensing %K digital biomarkers %K digital phenotyping %K artificial intelligence %K deep learning %K mobile phone %D 2020 %7 31.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Schizophrenia spectrum disorders (SSDs) are chronic conditions, but the severity of symptomatic experiences and functional impairments vacillate over the course of illness. Developing unobtrusive remote monitoring systems to detect early warning signs of impending symptomatic relapses would allow clinicians to intervene before the patient’s condition worsens. Objective: In this study, we aim to create the first models, exclusively using passive sensing data from a smartphone, to predict behavioral anomalies that could indicate early warning signs of a psychotic relapse. Methods: Data used to train and test the models were collected during the CrossCheck study. Hourly features derived from smartphone passive sensing data were extracted from 60 patients with SSDs (42 nonrelapse and 18 relapse >1 time throughout the study) and used to train models and test performance. We trained 2 types of encoder-decoder neural network models and a clustering-based local outlier factor model to predict behavioral anomalies that occurred within the 30-day period before a participant's date of relapse (the near relapse period). Models were trained to recreate participant behavior on days of relative health (DRH, outside of the near relapse period), following which a threshold to the recreation error was applied to predict anomalies. The neural network model architecture and the percentage of relapse participant data used to train all models were varied. Results: A total of 20,137 days of collected data were analyzed, with 726 days of data (0.037%) within any 30-day near relapse period. The best performing model used a fully connected neural network autoencoder architecture and achieved a median sensitivity of 0.25 (IQR 0.15-1.00) and specificity of 0.88 (IQR 0.14-0.96; a median 108% increase in behavioral anomalies near relapse). We conducted a post hoc analysis using the best performing model to identify behavioral features that had a medium-to-large effect (Cohen d>0.5) in distinguishing anomalies near relapse from DRH among 4 participants who relapsed multiple times throughout the study. Qualitative validation using clinical notes collected during the original CrossCheck study showed that the identified features from our analysis were presented to clinicians during relapse events. Conclusions: Our proposed method predicted a higher rate of anomalies in patients with SSDs within the 30-day near relapse period and can be used to uncover individual-level behaviors that change before relapse. This approach will enable technologists and clinicians to build unobtrusive digital mental health tools that can predict incipient relapse in SSDs. %M 32865506 %R 10.2196/19962 %U https://mhealth.jmir.org/2020/8/e19962 %U https://doi.org/10.2196/19962 %U http://www.ncbi.nlm.nih.gov/pubmed/32865506 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e15338 %T Monitoring Occupational Sitting, Standing, and Stepping in Office Employees With the W@W-App and the MetaWearC Sensor: Validation Study %A Bort-Roig,Judit %A Chirveches-Pérez,Emilia %A Garcia-Cuyàs,Francesc %A Dowd,Kieran P %A Puig-Ribera,Anna %+ Sport and Physical Activity Research Group, Centre for Health and Social Care Research, University of Vic-Central University of Catalonia, Miquel Martí i Pol, 1, Vic, 08500, Spain, 34 938863342, annam.puig@uvic.cat %K validity %K self-monitoring %K sedentary behavior %K physical activity %K smartphone %K mobile phone %K device-based measure %D 2020 %7 4.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Replacing occupational sitting time with active tasks has several proposed health benefits for office employees. Mobile phones and motion sensors can provide objective information in real time on occupational sitting behavior. However, the validity and feasibility of using mobile health (mHealth) devices to quantify and modify occupational sedentary time is unclear. Objective: The aim of this study is to validate the new Walk@Work-Application (W@W-App)—including an external motion sensor (MetaWearC) attached to the thigh—for measuring occupational sitting, standing, and stepping in free-living conditions against the activPAL3M, the current gold-standard, device-based measure for postural behaviors. Methods: In total, 20 office workers (16 [80%] females; mean age 39.5, SD 8.1 years) downloaded the W@W-App to their mobile phones, wore a MetaWearC sensor attached to their thigh using a tailored band, and wore the activPAL3M for 3-8 consecutive working hours. Differences between both measures were examined using paired-samples t tests and Wilcoxon signed-rank tests. Agreement between measures was examined using concordance correlation coefficients (CCCs), 95% CIs, Bland-Altman plots (mean bias, 95% limits of agreement [LoA]), and equivalence testing techniques. Results: The median recording time for the W@W-App+MetaWearC and the activPAL3M was 237.5 (SD 132.8) minutes and 240.0 (SD 127.5) minutes, respectively (P<.001). No significant differences between sitting (P=.53), standing (P=.12), and stepping times (P=.61) were identified. The CCC identified substantial agreement between both measures for sitting (CCC=0.98, 95% CI 0.96-0.99), moderate agreement for standing (CCC=0.93, 95% CI 0.81-0.97), and poor agreement for stepping (CCC=0.74, 95% CI 0.47-0.88). Bland-Altman plots indicated that sitting time (mean bias –1.66 minutes, 95% LoA –30.37 to 20.05) and standing time (mean bias –4.85 minutes, 95% LoA –31.31 to 21.62) were underreported. For stepping time, a positive mean bias of 1.15 minutes (95% LoA –15.11 to 17.41) was identified. Equivalence testing demonstrated that the estimates obtained from the W@W-App+MetaWearC and the activPAL3M were considered equivalent for all variables excluding stepping time. Conclusions: The W@W-App+MetaWearC is a low-cost tool with acceptable levels of accuracy that can objectively quantify occupational sitting, standing, stationary, and upright times in real time. Due to the availability of real-time feedback for users, this tool can positively influence occupational sitting behaviors in future interventions. Trial Registration: ClinicalTrials.gov NCT04092738; https://clinicaltrials.gov/ct2/show/NCT04092738 %M 32459625 %R 10.2196/15338 %U https://mhealth.jmir.org/2020/8/e15338 %U https://doi.org/10.2196/15338 %U http://www.ncbi.nlm.nih.gov/pubmed/32459625 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e15156 %T Rams Have Heart, a Mobile App Tracking Activity and Fruit and Vegetable Consumption to Support the Cardiovascular Health of College Students: Development and Usability Study %A Krzyzanowski,Michelle C %A Kizakevich,Paul N %A Duren-Winfield,Vanessa %A Eckhoff,Randall %A Hampton,Joel %A Blackman Carr,Loneke T %A McCauley,Georgia %A Roberson,Kristina B %A Onsomu,Elijah O %A Williams,John %A Price,Amanda Alise %+ RTI International, 3040 Conwallis Rd, Research Triangle Park, NC, 27709, United States, 1 919 485 5648, mkrzyzanowski@rti.org %K exercise %K cardiovascular disease %K diary %K diet %K mHealth %K mobile phone %D 2020 %7 5.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: With the increasing use of mobile devices to access the internet and as the main computing system of apps, there is a growing market for mobile health apps to provide self-care advice. Their effectiveness with regard to diet and fitness tracking, for example, needs to be examined. The majority of American adults fail to meet daily recommendations for healthy behavior. Testing user engagement with an app in a controlled environment can provide insight into what is effective and not effective in an app focused on improving diet and exercise. Objective: We developed Rams Have Heart, a mobile app, to support a cardiovascular disease (CVD) intervention course. The app tracks healthy behaviors, including fruit and vegetable consumption and physical activity, throughout the day. This paper aimed to present its functionality and evaluated adherence among the African American college student population. Methods: We developed the app using the Personal Health Informatics and Intervention Toolkit, a software framework. Rams Have Heart integrates self-reported health screening with health education, diary tracking, and user feedback modules to acquire data and assess progress. The parent study, conducted at a historically black college and university-designated institution in southeastern United States, consisted of a semester-long intervention administered as an academic course in the fall, for 3 consecutive years. Changes were made after the cohort 1 pilot study, so results only include cohorts 2 and 3, comprising a total of 115 students (n=55 intervention participants and n=54 control participants) aged from 17 to 24 years. Data collected over the study period were transferred using the secure Hypertext Transfer Protocol Secure protocol and stored in a secure Structured Query Language server database accessible only to authorized persons. SAS software was used to analyze the overall app usage and the specific results collected. Results: Of the 55 students in the intervention group, 27 (49%) students in cohort 2 and 25 (45%) in cohort 3 used the Rams Have Heart app at least once. Over the course of the fall semester, app participation dropped off gradually until exam week when most students no longer participated. The average fruit and vegetable intake increased slightly, and activity levels decreased over the study period. Conclusions: Rams Have Heart was developed to allow daily tracking of fruit and vegetable intake and physical activity to support a CVD risk intervention for a student demographic susceptible to obesity, heart disease, and type 2 diabetes. We conducted an analysis of app usage, function, and user results. Although a mobile app provides privacy and flexibility for user participation in a research study, Rams Have Heart did not improve compliance or user outcomes. Health-oriented research studies relying on apps in support of user goals need further evaluation. %M 32755883 %R 10.2196/15156 %U https://mhealth.jmir.org/2020/8/e15156 %U https://doi.org/10.2196/15156 %U http://www.ncbi.nlm.nih.gov/pubmed/32755883 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e19380 %T User Perception of a Smartphone App to Promote Physical Activity Through Active Transportation: Inductive Qualitative Content Analysis Within the Smart City Active Mobile Phone Intervention (SCAMPI) Study %A Lindqvist,Anna-Karin %A Rutberg,Stina %A Söderström,Emmie %A Ek,Anna %A Alexandrou,Christina %A Maddison,Ralph %A Löf,Marie %+ Division of Health, Medicine and Rehabilitation, Department of Health Sciences, Luleå University of Technology, Luleå, 971 87, Sweden, 46 0725390660, anna-karin.lindqvist@ltu.se %K behavior change %K smartphone intervention %K physical activity %K user perception %K active transportation %K mobile app %K inductive qualitative content analysis %K mobile health %K social cognitive theory %K mHealth %D 2020 %7 5.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Physical inactivity is globally recognized as a major risk factor for morbidity, particularly the incidence of noncommunicable diseases. Increasing physical activity (PA) is therefore a public health priority. Engaging in active transportation (AT) is a viable approach for promoting daily PA levels. Mobile health interventions enable the promotion of AT to a larger population. The Smart City Active Mobile Phone Intervention (SCAMPI) study was a randomized controlled trial designed to evaluate the ability of a behavior change program delivered via a smartphone app to motivate participants to increase their PA by engaging in AT. Objective: This qualitative study aims to examine the acceptance and user experience of the app promoting AT that was used in the SCAMPI trial (the TRavelVU Plus app). Methods: A total of 17 residents of Stockholm County (13 women; age range 25-61 years) who completed the 3-month app-based behavioral change program (delivered through the TRavelVU Plus app) in the SCAMPI randomized controlled trial during 2018 agreed to participate in a semistructured telephone-based interview. These participants were well representative of the whole intervention group (n=127) in terms of baseline characteristics such as age, sex, and area of residence. The interviews were audiorecorded, transcribed verbatim, and analyzed using an inductive qualitative content analysis. Results: The content analysis revealed 2 themes and 4 subcategories. The first theme, “main motivators: monitoring and messages,” highlighted that monitoring AT and being able to set weekly goals using the app were the primary motivators reported by study participants. The second theme, “acceptable but modifiable,” reflects that the app was well accepted and effectively encouraged many participants to use more AT. Nevertheless, there were functions in the app that require modification. For example, while the semiautomated travel tracking feature was appreciated, participants found it time-consuming and unreliable at times. Conclusions: This study contributes novel insight into adults’ experiences of using a mobile app to promote the use of AT. The results showed that the app was well accepted and that self-monitoring and goal setting were the main motivators to engage in more AT. The semiautomated tracking of AT was appreciated; however, it was also reported to be energy- and time-consuming when it failed to work. Thus, this feature should be improved going forward. Trial Registration: ClinicalTrials.gov NCT03086837; https://clinicaltrials.gov/ct2/show/NCT03086837 International Registered Report Identifier (IRRID): RR2-10.1186/s12889-018-5658-4 %M 32755889 %R 10.2196/19380 %U https://mhealth.jmir.org/2020/8/e19380 %U https://doi.org/10.2196/19380 %U http://www.ncbi.nlm.nih.gov/pubmed/32755889 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e16696 %T Effects of a Novel Contextual Just-In-Time Mobile App Intervention (LowSalt4Life) on Sodium Intake in Adults With Hypertension: Pilot Randomized Controlled Trial %A Dorsch,Michael P %A Cornellier,Maria L %A Poggi,Armella D %A Bilgen,Feriha %A Chen,Peiyu %A Wu,Cindy %A An,Lawrence C %A Hummel,Scott L %+ University of Michigan College of Pharmacy, 428 Church Street, Ann Arbor, MI, 48109, United States, 1 734 647 1452, mdorsch@med.umich.edu %K hypertension %K sodium intake %K geofencing %K mHealth %D 2020 %7 10.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: High dietary sodium intake is a significant public health problem in the United States. High sodium consumption is associated with high blood pressure and high risk of cardiovascular disease. Objective: The aim of this study was to evaluate the effect of a just-in-time adaptive mobile app intervention, namely, LowSalt4Life, on reducing sodium intake in adults with hypertension. Methods: In this study, 50 participants aged ≥18 years who were under treatment for hypertension were randomized (1:1, stratified by gender) into 2 groups, namely, the App group (LowSalt4Life intervention) and the No App group (usual dietary advice) in a single-center, prospective, open-label randomized controlled trial for 8 weeks. The primary endpoint was the change in the 24-hour urinary sodium excretion estimated from spot urine by using the Kawasaki equation, which was analyzed using unpaired two-sided t tests. Secondary outcomes included the change in the sodium intake measured by the food frequency questionnaire (FFQ), the 24-hour urinary sodium excretion, blood pressure levels, and the self-reported confidence in following a low-sodium diet. Results: From baseline to week 8, there was a significant reduction in the Kawasaki-estimated 24-hour urinary sodium excretion calculated from spot urine in the App group compared to that in the No App group (–462 [SD 1220] mg vs 381 [SD 1460] mg, respectively; P=.03). The change in the 24-hour urinary sodium excretion was –637 (SD 1524) mg in the App group and –322 (SD 1485) mg in the No App group (P=.47). The changes in the estimated sodium intake as measured by 24-hour dietary recall and by FFQ in the App group were –1537 (SD 2693) mg and –1553 (SD 1764) mg while those in the No App group were –233 (SD 2150) mg and –515 (SD 1081) mg, respectively (P=.07 and P=.01, respectively). The systolic blood pressure change from baseline to week 8 in the App group was –7.5 mmHg while that in the No App group was –0.7 mmHg (P=.12), but the self-confidence in following a low-sodium diet was not significantly different between the 2 groups. Conclusions: This study shows that a contextual just-in-time mobile app intervention resulted in a greater reduction in the dietary sodium intake in adults with hypertension than that in the control group over a 8-week period, as measured by the estimated 24-hour urinary sodium excretion from spot urine and FFQ. The intervention group did not show a significant difference from the control group in the self-confidence in following a low sodium diet and in the 24-hour urinary sodium excretion or dietary intake of sodium as measured by the 24-hour dietary recall. A larger clinical trial is warranted to further elucidate the effects of the LowSalt4Life intervention on sodium intake and blood pressure levels in adults with hypertension. Trial Registration: ClinicalTrials.gov NCT03099343; https://clinicaltrials.gov/ct2/show/NCT03099343 International Registered Report Identifier (IRRID): RR2-10.2196/11282 %M 32663139 %R 10.2196/16696 %U http://mhealth.jmir.org/2020/8/e16696/ %U https://doi.org/10.2196/16696 %U http://www.ncbi.nlm.nih.gov/pubmed/32663139 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e17755 %T Mobile App Use for Insomnia Self-Management in Urban Community-Dwelling Older Korean Adults: Retrospective Intervention Study %A Chung,Kyungmi %A Kim,Seoyoung %A Lee,Eun %A Park,Jin Young %+ Department of Psychiatry, Yonsei University College of Medicine, Yongin Severance Hospital, Yonsei University Health System, Department of Psychiatry, Yongin Severance Hospital, 363, Dongbaekjukjeon-daero, Giheung-gu, Yongin, 16995, Republic of Korea, 82 2 2228 0972, empathy@yuhs.ac %K sleep hygiene %K cognitive behavioral therapy %K sleep initiation and maintenance disorders %K telemedicine %K mobile apps %K treatment adherence and compliance %K health education %K health services for the aged %K community mental health services %K health care quality, access, and evaluation %D 2020 %7 24.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: As an evidence-based psychotherapy for treating insomnia, cognitive behavioral therapy for insomnia (CBT-I), which helps people with sleep problems to change their unhelpful sleep-related beliefs and habits, has been well-established in older adults. Recently, the utilization of mobile CBT-I apps has been getting attention from mental health professionals and researchers; however, whether mobile CBT-I apps are usable among older users has yet to be determined. Objective: The aims of this study were to explore the relationships between subjective sleep quality and subjective memory complaints and depressive symptoms; to explore the relationship between perceived difficulty in mobile app use and usability of the mobile phone–based self-help CBT-I app, named MIND MORE, in urban community-dwelling Korean older adults; to compare changes in subjective sleep quality from pre-intervention to post-intervention, during which they used the mobile app over a 1-week intervention period; and evaluate adherence to the app. Methods: During the 2-hour training program delivered on 1 day titled “Overcoming insomnia without medication: How to use the ‘MIND MORE’ mobile app for systematic self-management of insomnia” (pre-intervention), 41 attendants were asked to gain hands-on experience with the app facilitated by therapists and volunteer workers. They were then asked to complete questionnaires on sociodemographic characteristics, subjective evaluation of mental health status (ie, depression, memory loss and impairment, and sleep problems), and app usability. For the 1-week home-based self-help CBT-I using the app (post-intervention), 9 of the 41 program attendants, who had already signed up for the pre-intervention, were guided to complete the given questionnaires on subjective evaluation of sleep quality after the 1-week intervention, specifically 8 days after the training program ended. Results: Due to missing data, 40 of 41 attendants were included in the data analysis. The main findings of this study were as follows. First, poor subjective sleep quality was associated with higher ratings of depressive symptoms (40/40; ρ=.60, P<.001) and memory complaints (40/40; ρ=.46, P=.003) at baseline. Second, significant improvements in subjective sleep quality from pre-intervention to post-intervention were observed in the older adults who used the MIND MORE app only for the 1-week intervention period (9/9; t8=3.74, P=.006). Third, apart from the program attendants who did not have a smartphone (2/40) or withdrew from their MIND MORE membership (3/40), those who attended the 1-day sleep education program adhered to the app from at least 2 weeks (13/35, 37%) to 8 weeks (2/35, 6%) without any further contact. Conclusions: This study provides empirical evidence that the newly developed MIND MORE app not only is usable among older users but also could improve subjective sleep quality after a 1-week self-help intervention period. %M 32831177 %R 10.2196/17755 %U http://mhealth.jmir.org/2020/8/e17755/ %U https://doi.org/10.2196/17755 %U http://www.ncbi.nlm.nih.gov/pubmed/32831177 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e19529 %T Mobile Fotonovelas Within a Text Message Outreach: An Innovative Tool to Build Health Literacy and Influence Behaviors in Response to the COVID-19 Pandemic %A Brar Prayaga,Rena %A Prayaga,Ram S %+ mPulse Mobile, Inc, 16530 Ventura Blvd, Suite 500, Encino, CA, 91436, United States, 1 888 678 5735, rena@mpulsemobile.com %K text messaging %K SMS %K mobile fotonovelas %K COVID-19 %K social isolation %K social support %K health behaviors %K health literacy %K health plans %D 2020 %7 10.8.2020 %9 Viewpoint %J JMIR Mhealth Uhealth %G English %X With all 50 US states reporting cases of coronavirus disease (COVID-19), people around the country are adapting and stepping up to the challenges of the pandemic; however, they are also frightened, anxious, and confused about what they can do to avoid exposure to the disease. Usual habits have been interrupted as a result of the crisis, and consumers are open to suggestions and strategies to help them change long-standing attitudes and behaviors. In response, a novel and innovative mobile communication capability was developed to present health messages in English and Spanish with links to fotonovelas (visual stories) that are accessible, easy to understand across literacy levels, and compelling to a diverse audience. While SMS text message outreach has been used to build health literacy and provide social support, few studies have explored the benefits of SMS text messaging combined with visual stories to influence health behaviors and build knowledge and self-efficacy. In particular, this approach can be used to provide vital information, resources, empathy, and support to the most vulnerable populations. This also allows providers and health plans to quickly reach out to their patients and members without any additional resource demands at a time when the health care system is severely overburdened. %M 32716894 %R 10.2196/19529 %U http://mhealth.jmir.org/2020/8/e19529/ %U https://doi.org/10.2196/19529 %U http://www.ncbi.nlm.nih.gov/pubmed/32716894 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e18793 %T A Tailored Motivational Messages Library for a Mobile Health Sleep Behavior Change Support System to Promote Continuous Positive Airway Pressure Use Among Patients With Obstructive Sleep Apnea: Development, Content Validation, and Testing %A Alismail,Sarah %A Olfman,Lorne %+ Claremont Graduate University, 150 E 10th St, Claremont, CA, , United States, 1 909 621 8000, sarah.alismail@cgu.edu %K obstructive sleep apnea %K mHealth %K tailored messages %K CPAP therapy %K extended parallel process model %D 2020 %7 12.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Continuous positive airway pressure (CPAP) therapy is the most effective treatment for obstructive sleep apnea (OSA). Despite the reported benefits of CPAP therapy in treating OSA, its effectiveness is reduced by less-than-optimal adherence or use. Up to 50% of patients who accept CPAP therapy fail to adhere to it. As a lack of commitment to CPAP therapy is one of the most significant factors that hinder OSA treatment effectiveness, patient motivation and education are critical to help alleviate the problem of poor CPAP adherence or use. Objective: This study aims to support the development of mobile health interventions or information systems solutions to promote CPAP adherence and use among patients with OSA through development, content validation, and testing of tailored motivational messages. Methods: In phase 1, an initial library of 60 messages was developed to promote CPAP use among patients with OSA. In phase 2, draft messages were evaluated for content validation testing for relevance and clarity by research and clinical experts. In phase 3, patients with OSA (N=24) were recruited through a Qualtrics panel to rate the perceived persuasiveness of the messages in terms of threat and efficacy perceptions, as per their computed extended parallel process model (EPPM) response states. The average score of the ratings was calculated for each message. The messages were sorted according to their average (from highest to lowest) to select the best 12 messages for each tailored set based on the potential responses from the EPPM. Results: In phase 1, 60 messages were developed based on the existing literature and a review of existing materials. In phase 2, the enumerated content validity of the messages was established through the use of the content validity index for items. A total of 57 messages were found to have acceptable content relevance and clarity. In phase 3, patients with OSA perceived the final library of 48 messages to be persuasive. Conclusions: After the process of content validation and testing, the final library of messages met the criteria for clarity, relevance, and perceived persuasiveness. This study emphasizes the importance of developing and validating the content of motivational messages, grounded in EPPM theory, across the 4 possible response states in terms of high or low efficacy and threat perceptions. %M 32784176 %R 10.2196/18793 %U https://mhealth.jmir.org/2020/8/e18793 %U https://doi.org/10.2196/18793 %U http://www.ncbi.nlm.nih.gov/pubmed/32784176 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e17191 %T Two-Way Text Messaging to Support Self-Care and Delivery of an Online Sexual Health Service: Mixed Methods Evaluation %A Shanks,Sarah %A Morelli,Alessandra %A Ardines,Elena %A Holdsworth,Gillian %A Baraitser,Paula %+ SH:24, 35a Westminster Bridge Road, London, SE1 7JB, United Kingdom, 1 02076202250, sshanks@nhs.net %K SMS %K text message %K digital health %K sexual health %K self-care %K mobile phone %D 2020 %7 20.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Digital health care is increasingly used to improve health service accessibility and reduce costs. Remote health care requires a significant self-management role for service users, and this generates information provision and support needs that should be reflected in service planning. SMS text messaging offers a convenient and low-cost method of communication and is increasingly used across digital health care services to provide remote support. Objective: The aim of this study was to quantify the number of messages generated through user interaction with a two-way SMS text messaging support service within an online sexual health service and to thematically explore the content of the messages and type of support required to facilitate self-management. Methods: The content of all SMS text messages received by an online sexual health service was analyzed from April 4, 2018, to July 5, 2018. Messages were classified as being either administrative or clinical in nature and service or user initiated. For those messages that were both clinical and user initiated, a qualitative thematic analysis was completed to fully describe the content of the interactions. Results: A total of 267 actionable messages were generated per 1000 orders requested through the service. Of the 8562 messages, 5447 (63.62%) messages were administrative and 3115 (36.38%) were clinical. Overall, 4306 of the 8562 messages (50.29%) responded to service-generated queries reflecting the public health and clinical responsibilities of an online provider, and 4256 (49.71%) were user-generated queries, demonstrating a willingness by users to proactively engage with a two-way SMS text messaging support service. Of the 3115 clinical messages, 968 (31.08%) clinical messages were user initiated and shared personal and complex clinical information, including requests for help with the self-testing process and personalized clinical advice relating to symptoms and treatment. Conclusions: This study demonstrates the willingness of users of an online sexual health service to engage with two-way SMS text messaging and provides insight into the quantity and nature of the support required to facilitate service delivery and self-care. Further work is required to understand the range of clinical problems that can be managed within this medium. %M 32815820 %R 10.2196/17191 %U http://mhealth.jmir.org/2020/8/e17191/ %U https://doi.org/10.2196/17191 %U http://www.ncbi.nlm.nih.gov/pubmed/32815820 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e16180 %T Characteristics of Neuropsychiatric Mobile Health Trials: Cross-Sectional Analysis of Studies Registered on ClinicalTrials.gov %A Minen,Mia Tova %A Reichel,Julia Frederica %A Pemmireddy,Pallavi %A Loder,Elizabeth %A Torous,John %+ NYU Langone Health, 222 E 41st Street,, New York, NY, 10017, United States, 1 2122637744, minenmd@gmail.com %K smartphones %K mobile phones %K apps %K mental health %K regulation %K stroke %K migraine %K major depressive disorder %K Alzheimer disease %K anxiety disorders %K alcohol use disorders %K opioid use disorders %K epilepsy %K schizophrenia %D 2020 %7 4.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The development of mobile health (mHealth) technologies is progressing at a faster pace than that of the science to evaluate their validity and efficacy. Under the International Committee of Journal Medical Editors (ICMJE) guidelines, clinical trials that prospectively assign people to interventions should be registered with a database before the initiation of the study. Objective: The aim of this study was to better understand the smartphone mHealth trials for high-burden neuropsychiatric conditions registered on ClinicalTrials.gov through November 2018, including the number, types, and characteristics of the studies being conducted; the frequency and timing of any outcome changes; and the reporting of results. Methods: We conducted a systematic search of ClinicalTrials.gov for the top 10 most disabling neuropsychiatric conditions and prespecified terms related to mHealth. According to the 2016 World Health Organization Global Burden of Disease Study, the top 10 most disabling neuropsychiatric conditions are (1) stroke, (2) migraine, (3) major depressive disorder, (4) Alzheimer disease and other dementias, (5) anxiety disorders, (6) alcohol use disorders, (7) opioid use disorders, (8) epilepsy, (9) schizophrenia, and (10) other mental and substance use disorders. There were no date, location, or status restrictions. Results: Our search identified 135 studies. A total of 28.9% (39/135) of studies evaluated interventions for major depressive disorder, 14.1% (19/135) of studies evaluated interventions for alcohol use disorders, 12.6% (17/135) of studies evaluated interventions for stroke, 11.1% (15/135) of studies evaluated interventions for schizophrenia, 8.1% (11/135) of studies evaluated interventions for anxiety disorders, 8.1% (11/135) of studies evaluated interventions for other mental and substance use disorders, 7.4% (10/135) of studies evaluated interventions for opioid use disorders, 3.7% (5/135) of studies evaluated interventions for Alzheimer disease or other dementias, 3.0% (4/135) of studies evaluated interventions for epilepsy, and 3.0% (4/135) of studies evaluated interventions for migraine. The studies were first registered in 2008; more than half of the studies were registered from 2016 to 2018. A total of 18.5% (25/135) of trials had results reported in some publicly accessible location. Across all the studies, the mean estimated enrollment (reported by the study) was 1078, although the median was only 100. In addition, across all the studies, the actual reported enrollment was lower, with a mean of 249 and a median of 80. Only about a quarter of the studies (35/135, 25.9%) were funded by the National Institutes of Health. Conclusions: Despite the increasing use of health-based technologies, this analysis of ClinicalTrials.gov suggests that only a few apps for high-burden neuropsychiatric conditions are being clinically evaluated in trials. %M 32749230 %R 10.2196/16180 %U https://mhealth.jmir.org/2020/8/e16180 %U https://doi.org/10.2196/16180 %U http://www.ncbi.nlm.nih.gov/pubmed/32749230 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e19433 %T Developing a Mobile App (iGAM) to Promote Gingival Health by Professional Monitoring of Dental Selfies: User-Centered Design Approach %A Tobias,Guy %A Spanier,Assaf B %+ Department of Community Dentistry, Faculty of Dental Medicine, The Hebrew University - Hadassah School of Dental Medicine, Ein Kerem, Jerusalem, 91120, Israel, 972 527052333, guy.tobias@mail.huji.ac.il %K mHealth %K telemedicine %K public health %K oral health promotion %K gum health %K flow of information %K COVID-19 %D 2020 %7 14.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Dental visits are unpleasant; sometimes, patients only seek treatment when they are in intolerable pain. Recently, the novel coronavirus (COVID-19) pandemic has highlighted the need for remote communication when patients and dentists cannot meet in person. Gingivitis is very common and characterized by red, swollen, bleeding gums. Gingivitis heals within 10 days of professional care and with daily, thorough oral hygiene practices. If left untreated, however, its progress may lead to teeth becoming mobile or lost. Of the many medical apps currently available, none monitor gingivitis. Objective: This study aimed to present a characterization and development model of a mobile health (mHealth) app called iGAM, which focuses on periodontal health and improves the information flow between dentists and patients. Methods: A focus group discussed the potential of an app to monitor gingivitis, and 3 semistructured in-depth interviews were conducted on the use of apps for monitoring gum infections. We used a qualitative design process based on the Agile approach, which incorporated the following 5 steps: (1) user story, (2) use cases, (3) functional requirements, (4) nonfunctional requirements, and (5) Agile software development cycles. In a pilot study with 18 participants aged 18-45 years and with different levels of health literacy, participants were given a toothbrush, toothpaste, mouthwash, toothpicks, and dental floss. After installing iGAM, they were asked to photograph their gums weekly for 4 weeks. Results: All participants in the focus group believed in the potential of a mobile app to monitor gingivitis and reduce its severity. Concerns about security and privacy issues were discussed. From the interviews, 2 themes were derived: (1) “what's in it for me?” and (2) the need for a take-home message. The 5 cycles of development highlighted the importance of communication between dentists, app developers, and the pilot group. Qualitative analysis of the data from the pilot study showed difficulty with: (1) the camera, which was alleviated with the provision of mouth openers, and (2) the operation of the phone, which was alleviated by changing the app to be fully automated, with a weekly reminder and an instructions document. Final interviews showed satisfaction. Conclusions: iGAM is the first mHealth app for monitoring gingivitis using self-photography. iGAM facilitates the information flow between dentists and patients between checkups and may be useful when face-to-face consultations are not possible (such as during the COVID-19 pandemic). %M 32795985 %R 10.2196/19433 %U http://mhealth.jmir.org/2020/8/e19433/ %U https://doi.org/10.2196/19433 %U http://www.ncbi.nlm.nih.gov/pubmed/32795985 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e16862 %T Using Natural Language Processing and Sentiment Analysis to Augment Traditional User-Centered Design: Development and Usability Study %A Petersen,Curtis Lee %A Halter,Ryan %A Kotz,David %A Loeb,Lorie %A Cook,Summer %A Pidgeon,Dawna %A Christensen,Brock C %A Batsis,John A %+ The Dartmouth Institute for Health Policy, Dartmouth, 1 Medical Drive, Williamson Translational Research Building, Level 5, Lebanon, NH, 03756, United States, 1 603 653 9500, john.batsis@gmail.com %K aged adults %K sarcopenia %K remote sensing technology %K telemedicine %K mobile phone %D 2020 %7 7.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Sarcopenia, defined as the age-associated loss of muscle mass and strength, can be effectively mitigated through resistance-based physical activity. With compliance at approximately 40% for home-based exercise prescriptions, implementing a remote sensing system would help patients and clinicians to better understand treatment progress and increase compliance. The inclusion of end users in the development of mobile apps for remote-sensing systems can ensure that they are both user friendly and facilitate compliance. With advancements in natural language processing (NLP), there is potential for these methods to be used with data collected through the user-centered design process. Objective: This study aims to develop a mobile app for a novel device through a user-centered design process with both older adults and clinicians while exploring whether data collected through this process can be used in NLP and sentiment analysis Methods: Through a user-centered design process, we conducted semistructured interviews during the development of a geriatric-friendly Bluetooth-connected resistance exercise band app. We interviewed patients and clinicians at weeks 0, 5, and 10 of the app development. Each semistructured interview consisted of heuristic evaluations, cognitive walkthroughs, and observations. We used the Bing sentiment library for a sentiment analysis of interview transcripts and then applied NLP-based latent Dirichlet allocation (LDA) topic modeling to identify differences and similarities in patient and clinician participant interviews. Sentiment was defined as the sum of positive and negative words (each word with a +1 or −1 value). To assess utility, we used quantitative assessment questionnaires—System Usability Scale (SUS) and Usefulness, Satisfaction, and Ease of use (USE). Finally, we used multivariate linear models—adjusting for age, sex, subject group (clinician vs patient), and development—to explore the association between sentiment analysis and SUS and USE outcomes. Results: The mean age of the 22 participants was 68 (SD 14) years, and 17 (77%) were female. The overall mean SUS and USE scores were 66.4 (SD 13.6) and 41.3 (SD 15.2), respectively. Both patients and clinicians provided valuable insights into the needs of older adults when designing and building an app. The mean positive-negative sentiment per sentence was 0.19 (SD 0.21) and 0.47 (SD 0.21) for patient and clinician interviews, respectively. We found a positive association with positive sentiment in an interview and SUS score (ß=1.38; 95% CI 0.37 to 2.39; P=.01). There was no significant association between sentiment and the USE score. The LDA analysis found no overlap between patients and clinicians in the 8 identified topics. Conclusions: Involving patients and clinicians allowed us to design and build an app that is user friendly for older adults while supporting compliance. This is the first analysis using NLP and usability questionnaires in the quantification of user-centered design of technology for older adults. %M 32540843 %R 10.2196/16862 %U https://mhealth.jmir.org/2020/8/e16862 %U https://doi.org/10.2196/16862 %U http://www.ncbi.nlm.nih.gov/pubmed/32540843 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e18392 %T The Association Between App-Administered Depression Assessments and Suicidal Ideation in User Comments: Retrospective Observational Study %A DeForte,Shelly %A Huang,Yungui %A Bourgeois,Tran %A Hussain,Syed-Amad %A Lin,Simon %+ Abigail Wexner Research Institute, Nationwide Children's Hospital, 700 Children's Drive, Columbus, OH, 43215, United States, 1 202 318 1627, simon.lin@nationwidechildrens.org %K mobile health %K mHealth %K depression %K qualitative research %K mental health %D 2020 %7 4.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Many people use apps to help understand and manage their depression symptoms. App-administered questionnaires for the symptoms of depression, such as the Patient Health Questionnaire-9, are easy to score and implement in an app, but may not be accompanied by essential resources and access needed to provide proper support and avoid potential harm. Objective: Our primary goal was to evaluate the differences in risks and helpfulness associated with using an app to self-diagnose depression, comparing assessment-only apps with multifeatured apps. We also investigated whether, what, and how additional app features may mitigate potential risks. Methods: In this retrospective observational study, we identified apps in the Google Play store that provided a depression assessment as a feature and had at least five user comments. We separated apps into two categories based on those having only a depression assessment versus those that offered additional supportive features. We conducted theoretical thematic analyses over the user reviews, with thematic coding indicating the helpfulness of the app, the presence of suicidal ideation, and how and why the apps were used. We compared the results across the two categories of apps and analyzed the differences using chi-square statistical tests. Results: We evaluated 6 apps; 3 provided only a depression assessment (assessment only), and 3 provided features in addition to self-assessment (multifeatured). User comments for assessment-only apps indicated significantly more suicidal ideation or self-harm (n=31, 9.4%) compared to comments for multifeatured apps (n=48, 2.3%; X21=43.88, P<.001). Users of multifeatured apps were over three times more likely than assessment-only app users to comment in favor of the app’s helpfulness, likely due to features like mood tracking, journaling, and informational resources (n=56, 17% vs n=1223, 59% respectively; X21=200.36, P<.001). The number of users under the age of 18 years was significantly higher among assessment-only app users (n=40, 12%) than multifeatured app users (n=9, 0.04%; X21=189.09, P<.001). Conclusions: Apps that diagnose depression by self-assessment without context or other supportive features are more likely to be used by those under 18 years of age and more likely to be associated with increased user distress and potential harm. Depression self-assessments in apps should be implemented with caution and accompanied by evidence-based capabilities that establish proper context, increase self-empowerment, and encourage users to seek clinical diagnostics and outside help. %M 32663158 %R 10.2196/18392 %U https://mhealth.jmir.org/2020/8/e18392 %U https://doi.org/10.2196/18392 %U http://www.ncbi.nlm.nih.gov/pubmed/32663158 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e19807 %T Quality of Psychoeducational Apps for Military Members With Mild Traumatic Brain Injury: An Evaluation Utilizing the Mobile Application Rating Scale %A Jones,Chelsea %A O'Toole,Kaitlin %A Jones,Kevin %A Brémault-Phillips,Suzette %+ Heroes in Mind, Advocacy and Research Consortium (HiMARC), Faculty of Rehabilitation Medicine, University of Alberta, 8205 - 114 Street NW, Edmonton, AB, T6G 2G4, Canada, 1 780 492 0404, cweiman@ualberta.ca %K psychoeducation %K mTBI %K military %K app %K smartphone %K mHealth, concussion %K Mobile App Rating Scale %K MARS %K mobile phone %D 2020 %7 18.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Military personnel have an elevated risk of sustaining mild traumatic brain injuries (mTBI) and postconcussion symptoms (PCS). Smartphone apps that provide psychoeducation may assist those with mTBI or PCS to overcome unique barriers that military personnel experience with stigma and access to health care resources. Objective: This study aims to (1) use the Mobile Application Rating Scale (MARS) to evaluate smartphone apps purporting to provide psychoeducation for those who have sustained an mTBI or a PCS; (2) explore the relevance, utility, and effectiveness of these apps in facilitating symptom management and overall recovery from mTBI and PCS among military personnel; and (3) discuss considerations pertinent to health care professionals and patients with mTBI when considering the use of mobile health (mHealth), including apps for mTBI psychoeducation. Methods: A five-step systematic search for smartphone apps for military members with mTBI or PCS was conducted on January 31, 2020. Cost-free apps meeting the inclusion criteria were evaluated using the MARS and compared with evidence-based best practice management protocols for mTBI and PCS. Results: The search yielded a total of 347 smartphone apps. After applying the inclusion and exclusion criteria, 13 apps were subjected to evaluation. Two apps were endorsed by the US Department of Veterans Affairs and the US Department of Defense; all the others (n=11) were developed for civilians. When compared with evidence-based best practice resources, the apps provided various levels of psychoeducational content. There are multiple considerations that health care professionals and those who sustain an mTBI or a PCS have to consider when choosing to use mHealth and selecting a specific app for mTBI psychoeducation. These may include factors such as the app platform, developer, internet requirement, cost, frequency of updates, language, additional features, acknowledgment of mental health, accessibility, military specificity, and privacy and security of data. Conclusions: Psychoeducational interventions have a good evidence base as a treatment for mTBI and PCS. The use of apps for this purpose may be clinically effective, cost-effective, confidential, user friendly, and accessible. However, more research is needed to explore the effectiveness, usability, safety, security, and accessibility of apps designed for mTBI management. %M 32808937 %R 10.2196/19807 %U http://mhealth.jmir.org/2020/8/e19807/ %U https://doi.org/10.2196/19807 %U http://www.ncbi.nlm.nih.gov/pubmed/32808937 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e21767 %T Smartphone and Mobile Health Apps for Tinnitus: Systematic Identification, Analysis, and Assessment %A Mehdi,Muntazir %A Stach,Michael %A Riha,Constanze %A Neff,Patrick %A Dode,Albi %A Pryss,Rüdiger %A Schlee,Winfried %A Reichert,Manfred %A Hauck,Franz J %+ Institute of Distributed Systems, Ulm University, Albert-Einstein-Allee 11, Ulm, 89081, Germany, 49 731 50 24140, franz.hauck@uni-ulm.de %K Health care %K Mobile Health %K Smartphone Apps %K Mobile Apps %K Tinnitus %K App Quality Assessment and Evaluation %K MARS %D 2020 %7 18.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Modern smartphones contain sophisticated high-end hardware features, offering high computational capabilities at extremely manageable costs and have undoubtedly become an integral part in users' daily life. Additionally, smartphones offer a well-established ecosystem that is easily discoverable and accessible via the marketplaces of differing mobile platforms, thus encouraging the development of many smartphone apps. Such apps are not exclusively used for entertainment purposes but are also commonplace in health care and medical use. A variety of those health and medical apps exist within the context of tinnitus, a phantom sound perception in the absence of any physical external source. Objective: In this paper, we shed light on existing smartphone apps addressing tinnitus by providing an up-to-date overview. Methods: Based on PRISMA guidelines, we systematically searched and identified existing smartphone apps on the most prominent app markets, namely Google Play Store and Apple App Store. In addition, we applied the Mobile App Rating Scale (MARS) to evaluate and assess the apps in terms of their general quality and in-depth user experience. Results: Our systematic search and screening of smartphone apps yielded a total of 34 apps (34 Android apps, 26 iOS apps). The mean MARS scores (out of 5) ranged between 2.65-4.60. The Tinnitus Peace smartphone app had the lowest score (mean 2.65, SD 0.20), and Sanvello—Stress and Anxiety Help had the highest MARS score (mean 4.60, SD 0.10). The interrater agreement was substantial (Fleiss κ=0.74), the internal consistency was excellent (Cronbach α=.95), and the interrater reliability was found to be both high and excellent—Guttman λ6=0.94 and intraclass correlation, ICC(2,k) 0.94 (95% CI 0.91-0.97), respectively. Conclusions: This work demonstrated that there exists a plethora of smartphone apps for tinnitus. All of the apps received MARS scores higher than 2, suggesting that they all have some technical functional value. However, nearly all identified apps were lacking in terms of scientific evidence, suggesting the need for stringent clinical validation of smartphone apps in future. To the best of our knowledge, this work is the first to systematically identify and evaluate smartphone apps within the context of tinnitus. %M 32808939 %R 10.2196/21767 %U http://mhealth.jmir.org/2020/8/e21767/ %U https://doi.org/10.2196/21767 %U http://www.ncbi.nlm.nih.gov/pubmed/32808939 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e14739 %T mHealth Interventions to Promote Anti-Retroviral Adherence in HIV: Narrative Review %A Lee,Stephen B %A Valerius,Joanne %+ Department of Medicine, Division of Infectious Diseases, University of Saskatchewan College of Medicine, Regina General Hospital, Unit 4E, Regina, SK, S4P 0W5, Canada, 1 306 766 4247, leestephenz@gmail.com %K mHealth %K HIV %K antiretroviral %K adherence %K mobile phone %D 2020 %7 28.8.2020 %9 Review %J JMIR Mhealth Uhealth %G English %X Background: Antiretrovirals (ARVs) are key in the management of HIV. Although no cure exists, ARVs help patients live healthy lives and prevent transmission to others. Adherence to complex regimens is paramount to outcomes and in avoiding the emergence of drug-resistant viruses. The goal of therapy is to reach an undetectable viral load. However, adherence is a common problem, stemming from issues such as mental health, chaotic home situations, and busy work schedules. Mobile health (mHealth) represents a new approach in improving medication adherence, and multiple studies have been performed in this area. Objective: This study aims to review the current implementation of mHealth in the management of HIV among different groups of patients. Methods: We used PubMed, Academic Search Elite, and 1 journal database with various search terms to review the current implementation of mHealth in HIV care. Results: Titles and abstracts were screened, and 61 papers were identified and fully reviewed. The literature was divided into lower- and higher-income nations, as defined by the United Nations. A total of 20 studies with quantitative results were identified, with 10 being text- and SMS-based interventions (the majority of these being in lower-income countries) and 8 being smartphone-based apps (primarily in higher-income countries). The majority of these studies determined whether there was an effect on adherence or biochemical parameters (viral load and CD4 count). Various qualitative studies have also been conducted, and many have focused on determining the specific design of interventions that were successful (frequency of messaging, types of messages, etc) as well as priorities for patients with regard to mHealth interventions. Conclusions: There seems to be a role of mHealth in the management of HIV in lower-income nations; however, the optimal design of an intervention needs to be delineated. In higher-income countries, where the 2 significant risk factors were injection drugs and men who have sex with men, the benefit was less clear, and more research is needed. %M 32568720 %R 10.2196/14739 %U https://mhealth.jmir.org/2020/8/e14739 %U https://doi.org/10.2196/14739 %U http://www.ncbi.nlm.nih.gov/pubmed/32568720 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e19661 %T Mobile Health Usage, Preferences, Barriers, and eHealth Literacy in Rheumatology: Patient Survey Study %A Knitza,Johannes %A Simon,David %A Lambrecht,Antonia %A Raab,Christina %A Tascilar,Koray %A Hagen,Melanie %A Kleyer,Arnd %A Bayat,Sara %A Derungs,Adrian %A Amft,Oliver %A Schett,Georg %A Hueber,Axel J %+ Department of Internal Medicine 3 – Rheumatology and Immunology, Friedrich-Alexander University Erlangen-Nürnberg, Ulmenweg 18, Erlangen, 91054, Germany, 49 913185 ext 35000, johannes.knitza@uk-erlangen.de %K mobile applications %K eHealth %K rheumatology %K mHealth %K eHEALS %K telemedicine %D 2020 %7 12.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Mobile health (mHealth) defines the support and practice of health care using mobile devices and promises to improve the current treatment situation of patients with chronic diseases. Little is known about mHealth usage and digital preferences of patients with chronic rheumatic diseases. Objective: The aim of the study was to explore mHealth usage, preferences, barriers, and eHealth literacy reported by German patients with rheumatic diseases. Methods: Between December 2018 and January 2019, patients (recruited consecutively) with rheumatoid arthritis, psoriatic arthritis, and axial spondyloarthritis were asked to complete a paper-based survey. The survey included questions on sociodemographics, health characteristics, mHealth usage, eHealth literacy using eHealth Literacy Scale (eHEALS), and communication and information preferences. Results: Of the patients (N=193) who completed the survey, 176 patients (91.2%) regularly used a smartphone, and 89 patients (46.1%) regularly used social media. Patients (132/193, 68.4%) believed that using medical apps could be beneficial for their own health. Out of 193 patients, only 8 (4.1%) were currently using medical apps, and only 22 patients (11.4%) stated that they knew useful rheumatology websites/mobile apps. Nearly all patients (188/193, 97.4%) would agree to share their mobile app data for research purposes. Out of 193 patients, 129 (66.8%) would regularly enter data using an app, and 146 patients (75.6%) would welcome official mobile app recommendations from the national rheumatology society. The preferred duration for data entry was not more than 15 minutes (110/193, 57.0%), and the preferred frequency was weekly (59/193, 30.6%). Medication information was the most desired app feature (150/193, 77.7%). Internet was the most frequently utilized source of information (144/193, 74.6%). The mean eHealth literacy was low (26.3/40) and was positively correlated with younger age, app use, belief in benefit of using medical apps, and current internet use to obtain health information. Conclusions: Patients with rheumatic diseases are very eager to use mHealth technologies to better understand their chronic diseases. This open-mindedness is counterbalanced by low mHealth usage and competency. Personalized mHealth solutions and clear implementation recommendations are needed to realize the full potential of mHealth in rheumatology. %M 32678796 %R 10.2196/19661 %U http://mhealth.jmir.org/2020/8/e19661/ %U https://doi.org/10.2196/19661 %U http://www.ncbi.nlm.nih.gov/pubmed/32678796 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e17271 %T User Experiences With and Recommendations for Mobile Health Technology for Hypertensive Disorders of Pregnancy: Mixed Methods Study %A Jongsma,Karin Rolanda %A van den Heuvel,Josephus F M %A Rake,Jasmijn %A Bredenoord,Annelien L %A Bekker,Mireille N %+ Department of Medical Humanities, University Medical Center Utrecht, Utrecht University, PO Box 85500, Utrecht, 3508 GA, Netherlands, 31 88 75 51351, k.r.jongsma@umcutrecht.nl %K mobile health %K hypertension %K telemonitoring %K ethics %K high-risk pregnancy %K preeclampsia %K digital health %D 2020 %7 4.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Hypertensive disorders of pregnancy (HDP) are a primary cause of adverse maternal and neonatal outcomes worldwide. For women at risk of hypertensive complications, guidelines recommend frequent surveillance of blood pressure and signs of preeclampsia. Clinic visits range from every 2 weeks to several times a week. Given the wide ubiquity of smartphones and computers in most countries and a growing attention for self-management, digital technologies, including mobile health (mHealth), constitute a promising component of monitoring (self-measured) blood pressure during pregnancy. Currently, little is known about the experiences of women using such platforms and how mHealth can be aligned with their needs and preferences. Objective: The objectives were twofold: (1) to explore the experiences of Dutch women who had an increased risk of HDP with a blended care approach (mHealth combined with face-to-face care) for remote self-monitoring of blood pressure and preeclampsia symptoms and (2) to formulate recommendations for the use and integration of mHealth in clinical care. Methods: Alongside a prospective blended care study (SAFE@home study) that monitors pregnant women at increased risk of HPD with mHealth technology, a mixed methods study was conducted, including questionnaires (n=52) and interviews (n=11). Results were analyzed thematically. Results: Of the 4 themes, 2 themes were related to the technologies themselves (expectations, usability), and 2 themes were related to the interaction and use of mHealth (autonomy and responsibilities of patients, responsibilities of health care professionals). First, the digital platform met the expectations of patients, which contributed to user satisfaction. Second, the platform was considered user-friendly, and patients favored different moments and frequencies for measuring their blood pressure. Third, patient autonomy was mentioned in terms of increased insight about their own condition and being able to influence clinical decision making. Fourth, clinical expertise of health care professionals was considered essential to interpret the data, which translates to subsequent responsibilities for clinical management. Data from the questionnaires and interviews corresponded. Conclusions: Blended care using an mHealth tool to monitor blood pressure in pregnancy was positively evaluated by its users. Insights from participants led to 7 recommendations for designing and implementing similar interventions and to enhance future, morally sound use of digital technologies in clinical care. %M 32749225 %R 10.2196/17271 %U https://mhealth.jmir.org/2020/8/e17271 %U https://doi.org/10.2196/17271 %U http://www.ncbi.nlm.nih.gov/pubmed/32749225 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e19531 %T Use of Tablets and Smartphones to Support Medical Decision Making in US Adults: Cross-Sectional Study %A Langford,Aisha %A Orellana,Kerli %A Kalinowski,Jolaade %A Aird,Carolyn %A Buderer,Nancy %+ Department of Population Health, NYU Langone Health, 30 E 30th Street, Room 611, New York, NY, 10016, United States, 1 646 501 2914, aisha.langford@nyulangone.org %K smartphone %K mHealth %K eHealth %K mobile phone %K cell phone %K tablets %K ownership %K decision making %K health communication %K telemedicine %K monitoring %K physiologic %K surveys and questionnaires %D 2020 %7 12.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Tablet and smartphone ownership have increased among US adults over the past decade. However, the degree to which people use mobile devices to help them make medical decisions remains unclear. Objective: The objective of this study is to explore factors associated with self-reported use of tablets or smartphones to support medical decision making in a nationally representative sample of US adults. Methods: Cross-sectional data from participants in the 2018 Health Information National Trends Survey (HINTS 5, Cycle 2) were evaluated. There were 3504 responses in the full HINTS 5 Cycle 2 data set; 2321 remained after eliminating respondents who did not have complete data for all the variables of interest. The primary outcome was use of a tablet or smartphone to help make a decision about how to treat an illness or condition. Sociodemographic factors including gender, race/ethnicity, and education were evaluated. Additionally, mobile health (mHealth)- and electronic health (eHealth)-related factors were evaluated including (1) the presence of health and wellness apps on a tablet or smartphone, (2) use of electronic devices other than tablets and smartphones to monitor health (eg, Fitbit, blood glucose monitor, and blood pressure monitor), and (3) whether people shared health information from an electronic monitoring device or smartphone with a health professional within the last 12 months. Descriptive and inferential statistics were conducted using SAS version 9.4. Weighted population estimates and standard errors, univariate odds ratios, and 95% CIs were calculated, comparing respondents who used tablets or smartphones to help make medical decisions (n=944) with those who did not (n=1377), separately for each factor. Factors of interest with a P value of <.10 were included in a subsequent multivariable logistic regression model. Results: Compared with women, men had lower odds of reporting that a tablet or smartphone helped them make a medical decision. Respondents aged 75 and older also had lower odds of using a tablet or smartphone compared with younger respondents aged 18-34. By contrast, those who had health and wellness apps on tablets or smartphones, used other electronic devices to monitor health, and shared information from devices or smartphones with health care professionals had higher odds of reporting that tablets or smartphones helped them make a medical decision, compared with those who did not. Conclusions: A limitation of this research is that information was not available regarding the specific health condition for which a tablet or smartphone helped people make a decision or the type of decision made (eg, surgery, medication changes). In US adults, mHealth and eHealth use, and also certain sociodemographic factors are associated with using tablets or smartphones to support medical decision making. Findings from this study may inform future mHealth and other digital health interventions designed to support medical decision making. %M 32784181 %R 10.2196/19531 %U https://mhealth.jmir.org/2020/8/e19531 %U https://doi.org/10.2196/19531 %U http://www.ncbi.nlm.nih.gov/pubmed/32784181 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e18370 %T Wearable Device Heart Rate and Activity Data in an Unsupervised Approach to Personalized Sleep Monitoring: Algorithm Validation %A Liu,Jiaxing %A Zhao,Yang %A Lai,Boya %A Wang,Hailiang %A Tsui,Kwok Leung %+ Centre for Systems Informatics Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, 999077, China (Hong Kong), 852 34425792, yang.zhao@my.cityu.edu.hk %K sleep/wake identification %K hidden Markov model %K personalized health %K unsupervised learning %K sleep %K physical activity %K wearables %K heart rate %D 2020 %7 5.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The proliferation of wearable devices that collect activity and heart rate data has facilitated new ways to measure sleeping and waking durations unobtrusively and longitudinally. Most existing sleep/wake identification algorithms are based on activity only and are trained on expensive and laboriously annotated polysomnography (PSG). Heart rate can also be reflective of sleep/wake transitions, which has motivated its investigation herein in an unsupervised algorithm. Moreover, it is necessary to develop a personalized approach to deal with interindividual variance in sleep/wake patterns. Objective: We aimed to develop an unsupervised personalized sleep/wake identification algorithm using multifaceted data to explore the benefits of incorporating both heart rate and activity level in these types of algorithms and to compare this approach’s output with that of an existing commercial wearable device’s algorithms. Methods: In this study, a total of 14 community-dwelling older adults wore wearable devices (Fitbit Alta; Fitbit Inc) 24 hours a day and 7 days a week over period of 3 months during which their heart rate and activity data were collected. After preprocessing the data, a model was developed to distinguish sleep/wake states based on each individual’s data. We proposed the use of hidden Markov models and compared different modeling schemes. With the best model selected, sleep/wake patterns were characterized by estimated parameters in hidden Markov models, and sleep/wake states were identified. Results: When applying our proposed algorithm on a daily basis, we found there were significant differences in estimated parameters between weekday models and weekend models for some participants. Conclusions: Our unsupervised approach can be effectively implemented based on an individual’s multifaceted sleep-related data from a commercial wearable device. A personalized model is shown to be necessary given the interindividual variability in estimated parameters. %M 32755887 %R 10.2196/18370 %U https://mhealth.jmir.org/2020/8/e18370 %U https://doi.org/10.2196/18370 %U http://www.ncbi.nlm.nih.gov/pubmed/32755887 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e17699 %T Using Smart Bracelets to Assess Heart Rate Among Students During Physical Education Lessons: Feasibility, Reliability, and Validity Study %A Sun,Jiangang %A Liu,Yang %+ School of Physical Education and Sport Training, Shanghai University of Sport, 650 Qingyuanhuan Rd, Shanghai, 200438, China, 86 21 6550 7989, docliuyang@hotmail.com %K physical education %K heart rate %K validation %K feasibility %K reliability %K Fizzo %K Polar %K wrist-worn devices %K physical education lesson %K monitoring %D 2020 %7 5.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: An increasing number of wrist-worn wearables are being examined in the context of health care. However, studies of their use during physical education (PE) lessons remain scarce. Objective: We aim to examine the reliability and validity of the Fizzo Smart Bracelet (Fizzo) in measuring heart rate (HR) in the laboratory and during PE lessons. Methods: In Study 1, 11 healthy subjects (median age 22.0 years, IQR 3.75 years) twice completed a test that involved running on a treadmill at 6 km/h for 12 minutes and 12 km/h for 5 minutes. During the test, participants wore two Fizzo devices, one each on their left and right wrists, to measure their HR. At the same time, the Polar Team2 Pro (Polar), which is worn on the chest, was used as the standard. In Study 2, we went to 10 schools and measured the HR of 24 students (median age 14.0 years, IQR 2.0 years) during PE lessons. During the PE lessons, each student wore a Polar device on their chest and a Fizzo on their right wrist to measure HR data. At the end of the PE lessons, the students and their teachers completed a questionnaire where they assessed the feasibility of Fizzo. The measurements taken by the left wrist Fizzo and the right wrist Fizzo were compared to estimate reliability, while the Fizzo measurements were compared to the Polar measurements to estimate validity. To measure reliability, intraclass correlation coefficients (ICC), mean difference (MD), standard error of measurement (SEM), and mean absolute percentage errors (MAPE) were used. To measure validity, ICC, limits of agreement (LOA), and MAPE were calculated and Bland-Altman plots were constructed. Percentage values were used to estimate the feasibility of Fizzo. Results: The Fizzo showed excellent reliability and validity in the laboratory and moderate validity in a PE lesson setting. In Study 1, reliability was excellent (ICC>0.97; MD<0.7; SEM<0.56; MAPE<1.45%). The validity as determined by comparing the left wrist Fizzo and right wrist Fizzo was excellent (ICC>0.98; MAPE<1.85%). Bland-Altman plots showed a strong correlation between left wrist Fizzo measurements (bias=0.48, LOA=–3.94 to 4.89 beats per minute) and right wrist Fizzo measurements (bias=0.56, LOA=–4.60 to 5.72 beats per minute). In Study 2, the validity of the Fizzo was lower compared to that found in Study 1 but still moderate (ICC>0.70; MAPE<9.0%). The Fizzo showed broader LOA in the Bland-Altman plots during the PE lessons (bias=–2.60, LOA=–38.89 to 33.69 beats per minute). Most participants considered the Fizzo very comfortable and easy to put on. All teachers thought the Fizzo was helpful. Conclusions: When participants ran on a treadmill in the laboratory, both left and right wrist Fizzo measurements were accurate. The validity of the Fizzo was lower in PE lessons but still reached a moderate level. The Fizzo is feasible for use during PE lessons. %M 32663136 %R 10.2196/17699 %U http://mhealth.jmir.org/2020/8/e17699/ %U https://doi.org/10.2196/17699 %U http://www.ncbi.nlm.nih.gov/pubmed/32663136 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e17803 %T Respiration Rate Estimation Based on Independent Component Analysis of Accelerometer Data: Pilot Single-Arm Intervention Study %A Lee,JeeEun %A Yoo,Sun K %+ Department of Medical Engineering, Yonsei University College of Medicine, Yonsei-ro, Seodaemun-gu, Seoul, , Republic of Korea, 82 10 3458 2435, sunkyoo@yuhs.ac %K respiration rate %K accelerometer %K smartphone %K independent component analysis %K quefrency %K mobile phone %D 2020 %7 10.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: As the mobile environment has developed recently, there have been studies on continuous respiration monitoring. However, it is not easy for general users to access the sensors typically used to measure respiration. There is also random noise caused by various environmental variables when respiration is measured using noncontact methods in a mobile environment. Objective: In this study, we aimed to estimate the respiration rate using an accelerometer sensor in a smartphone. Methods: First, data were acquired from an accelerometer sensor by a smartphone, which can easily be accessed by the general public. Second, an independent component was extracted to calibrate the three-axis accelerometer. Lastly, the respiration rate was estimated using quefrency selection reflecting the harmonic component because respiration has regular patterns. Results: From April 2018, we enrolled 30 male participants. When the independent component and quefrency selection were used to estimate the respiration rate, the correlation with respiration acquired from a chest belt was 0.7. The statistical results of the Wilcoxon signed-rank test were used to determine whether the differences in the respiration counts acquired from the chest belt and from the accelerometer sensor were significant. The P value of the difference in the respiration counts acquired from the two sensors was .27, which was not significant. This indicates that the number of respiration counts measured using the accelerometer sensor was not different from that measured using the chest belt. The Bland-Altman results indicated that the mean difference was 0.43, with less than one breath per minute, and that the respiration rate was at the 95% limits of agreement. Conclusions: There was no relevant difference in the respiration rate measured using a chest belt and that measured using an accelerometer sensor. The accelerometer sensor approach could solve the problems related to the inconvenience of chest belt attachment and the settings. It could be used to detect sleep apnea through constant respiration rate estimation in an internet-of-things environment. %M 32773384 %R 10.2196/17803 %U https://mhealth.jmir.org/2020/8/e17803 %U https://doi.org/10.2196/17803 %U http://www.ncbi.nlm.nih.gov/pubmed/32773384 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e23600 %T Correction: 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 %A Liu,Kaifeng %A Xie,Zhenzhen %A Or,Calvin Kalun %+ Department of Industrial and Manufacturing Systems Engineering, University of Hong Kong, Room 8-7, 8/f., Haking Wong Building,, University of Hong Kong, Hong Kong,, China (Hong Kong), 852 39172587, klor@hku.hk %D 2020 %7 19.8.2020 %9 Corrigenda and Addenda %J JMIR Mhealth Uhealth %G English %X %M 32813666 %R 10.2196/23600 %U http://mhealth.jmir.org/2020/8/e23600/ %U https://doi.org/10.2196/23600 %U http://www.ncbi.nlm.nih.gov/pubmed/32813666 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e20025 %T Using mHealth to Increase the Reach of Local Guidance to Health Professionals as Part of an Institutional Response Plan to the COVID-19 Outbreak: Usage Analysis Study %A Windisch,Olivier %A Zamberg,Ido %A Zanella,Marie-Céline %A Gayet-Ageron,Angèle %A Blondon,Katherine %A Schiffer,Eduardo %A Agoritsas,Thomas %+ Division of Urology, Department of Surgery, University Hospitals of Geneva, Rue Gabrielle-Perret-Gentil, Geneva, Switzerland, 41 79 777 78 89, olivier.windisch@hcuge.ch %K COVID-19 %K smartphone %K mHealth %K information dissemination %K health professionals %K health administration %K health apps %D 2020 %7 19.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The ongoing coronavirus disease (COVID-19) pandemic forced health jurisdictions worldwide to significantly restructure and reorganize their medical activities. In response to the rapidly evolving body of evidence, a solid communication strategy is needed to increase the reach of and adherence to locally drafted and validated guidance to aide medical staff with COVID-19–related clinical decisions. Objective: We present a usage analysis of a dedicated mobile health (mHealth) platform as part of an institutional knowledge dissemination strategy of COVID-19–related guidance to all health care workers (HCWs) in a large academic hospital. Methods: A multidisciplinary team of experts drafted local guidance related to COVID-19. In total, 60 documents and 17 external links were made available through the platform. Documents were disseminated using a recently deployed mHealth platform for HCWs. Targeted dissemination of COVID-19–related content began on March 22, 2020. Using a third-party statistics tool, data concerning user activity and content use was anonymously collected. A quantitative analysis of user activity was performed over a 4-month period, separated into 3 periods: 2 months before (Period A), 2 weeks after (Period B), and 6 weeks following (Period C) targeted dissemination. Regional epidemiological data (daily new COVID-19 cases and total COVID-19–related hospitalizations) was extracted from an official registry. Results: During the study period, the platform was downloaded by 1233 new users. Consequently, the total number of users increased from 1766 users before Period A to a total of 2999 users at the end of Period C. We observed 27,046 document views, of which 12,728 (47.1%) were COVID-19–related. The highest increase in activity occurred in Period B, rapidly following targeted dissemination, with 7740 COVID-19–related content views, representing 71.2% of total content views within the abovementioned period and 550 daily views of COVID-19–related documents. Total documents consulted per day increased from 117 (IQR 74-160) to 657 (IQR 481-1051), P<.001. This increase in activity followed the epidemiological curbing of newly diagnosed COVID-19 cases, which peaked during Period B. Total active devices doubled from 684 to 1400, daily user activity increased fourfold, and the number of active devices rose from 53 (IQR 40-70) to 210 (IQR 167-297), P<.001. In addition, the number of sessions per day rose from 166 (IQR 110-246) to 704 (IQR 517-1028), P<.001. A persistent but reduced increase in total documents consulted per day (172 [IQR 131-251] versus 117 [IQR 74-160], P<.001) and active devices (71 [IQR 64-89] versus 53 [IQR 40-70]) was observed in Period C compared to Period A, while only 29.8% of the content accessed was COVID-19–related. After targeted dissemination, an immediate increase in activity was observed after push notifications were sent to users. Conclusions: The use of an mHealth solution to disseminate time-sensitive medical knowledge seemed to be an effective solution to increase the reach of validated content to a targeted audience. %M 32749996 %R 10.2196/20025 %U http://mhealth.jmir.org/2020/8/e20025/ %U https://doi.org/10.2196/20025 %U http://www.ncbi.nlm.nih.gov/pubmed/32749996 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e19857 %T Acceptability of App-Based Contact Tracing for COVID-19: Cross-Country Survey Study %A Altmann,Samuel %A Milsom,Luke %A Zillessen,Hannah %A Blasone,Raffaele %A Gerdon,Frederic %A Bach,Ruben %A Kreuter,Frauke %A Nosenzo,Daniele %A Toussaert,Séverine %A Abeler,Johannes %+ University of Oxford, Manor Road, Oxford, OX1 3UQ, United Kingdom, 44 1865 281440, johannes.abeler@economics.ox.ac.uk %K COVID-19 %K contact tracing %K proximity tracing %K app %K digital %K user acceptability %K mHealth %K epidemiology %D 2020 %7 28.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The COVID-19 pandemic is the greatest public health crisis of the last 100 years. Countries have responded with various levels of lockdown to save lives and stop health systems from being overwhelmed. At the same time, lockdowns entail large socioeconomic costs. One exit strategy under consideration is a mobile phone app that traces the close contacts of those infected with COVID-19. Recent research has demonstrated the theoretical effectiveness of this solution in different disease settings. However, concerns have been raised about such apps because of the potential privacy implications. This could limit the acceptability of app-based contact tracing in the general population. As the effectiveness of this approach increases strongly with app uptake, it is crucial to understand public support for this intervention. Objective: The objective of this study is to investigate the user acceptability of a contact-tracing app in five countries hit by the pandemic. Methods: We conducted a largescale, multicountry study (N=5995) to measure public support for the digital contact tracing of COVID-19 infections. We ran anonymous online surveys in France, Germany, Italy, the United Kingdom, and the United States. We measured intentions to use a contact-tracing app across different installation regimes (voluntary installation vs automatic installation by mobile phone providers) and studied how these intentions vary across individuals and countries. Results: We found strong support for the app under both regimes, in all countries, across all subgroups of the population, and irrespective of regional-level COVID-19 mortality rates. We investigated the main factors that may hinder or facilitate uptake and found that concerns about cybersecurity and privacy, together with a lack of trust in the government, are the main barriers to adoption. Conclusions: Epidemiological evidence shows that app-based contact tracing can suppress the spread of COVID-19 if a high enough proportion of the population uses the app and that it can still reduce the number of infections if uptake is moderate. Our findings show that the willingness to install the app is very high. The available evidence suggests that app-based contact tracing may be a viable approach to control the diffusion of COVID-19. %M 32759102 %R 10.2196/19857 %U http://mhealth.jmir.org/2020/8/e19857/ %U https://doi.org/10.2196/19857 %U http://www.ncbi.nlm.nih.gov/pubmed/32759102