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Journal Description

JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a sister journal of JMIR, the leading eHealth journal. JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, Scopus, and Science Citation Index Expanded (SCIE), and in June 2018 received an Impact Factor of 4.541, which ranks the journal #2 (behind JMIR) out of 25 journals in the medical informatics category indexed by the Science Citation Index Expanded (SCIE) by Thomson Reuters/Clarivate

The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics.

JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research

JMIR mHealth and uHealth features a rapid and thorough peer-review process, professional copyediting, professional production of PDF, XHTML, and XML proofs.

JMIR mHealth and uHealth adheres to the same quality standards as JMIR and all articles published here are also cross-listed in the Table of Contents of JMIR, the worlds' leading medical journal in health sciences / health services research and health informatics.

 

Recent Articles:

  • Image used within the Dallas intervention by one of the Dallas communities. Source: Sitekit Solutions Ltd; Copyright: Sitekit Solutions Ltd; URL: https://www.sitekit.net/case-studies/living-it-up-case-study.htm; License: Licensed by the authors.

    Valuing Mobile Health: An Open-Ended Contingent Valuation Survey of a National Digital Health Program

    Abstract:

    Background: Changing population demographics and technology developments have resulted in growing interest in the potential of consumer-facing digital health. In the United Kingdom, a £37 million (US $49 million) national digital health program delivering assisted living lifestyles at scale (dallas) aimed to deploy such technologies at scale. However, little is known about how consumers value such digital health opportunities. Objective: This study explored consumers’ perspectives on the potential value of digital health technologies, particularly mobile health (mHealth), to promote well-being by examining their willingness-to-pay (WTP) for such health solutions. Methods: A contingent valuation study involving a UK-wide survey that asked participants to report open-ended absolute and marginal WTP or willingness-to-accept for the gain or loss of a hypothetical mHealth app, Healthy Connections. Results: A UK-representative cohort (n=1697) and a dallas-like (representative of dallas intervention communities) cohort (n=305) were surveyed. Positive absolute and marginal WTP valuations of the app were identified across both cohorts (absolute WTP: UK-representative cohort £196 or US $258 and dallas-like cohort £162 or US $214; marginal WTP: UK-representative cohort £160 or US $211 and dallas-like cohort £151 or US $199). Among both cohorts, there was a high prevalence of zeros for both the absolute WTP (UK-representative cohort: 467/1697, 27.52% and dallas-like cohort: 95/305, 31.15%) and marginal WTP (UK-representative cohort: 487/1697, 28.70% and dallas-like cohort: 99/305, 32.5%). In both cohorts, better general health, previous amount spent on health apps (UK-representative cohort 0.64, 95% CI 0.27 to 1.01; dallas-like cohort: 1.27, 95% CI 0.32 to 2.23), and age had a significant (P>.00) association with WTP (UK-representative cohort: −0.1, 95% CI −0.02 to −0.01; dallas-like cohort: −0.02, 95% CI −0.03 to −0.01), with younger participants willing to pay more for the app. In the UK-representative cohort, as expected, higher WTP was positively associated with income up to £30,000 or US $39,642 (0.21, 95% CI 0.14 to 0.4) and increased spending on existing phone and internet services (0.52, 95% CI 0.30 to 0.74). The amount spent on existing health apps was shown to be a positive indicator of WTP across cohorts, although the effect was marginal (UK-representative cohort 0.01, 95% CI 0.01 to 0.01; dallas-like cohort 0.01, 95% CI 0.01 to 0.02). Conclusions: This study demonstrates that consumers value mHealth solutions that promote well-being, social connectivity, and health care control, but it is not universally embraced. For mHealth to achieve its potential, apps need to be tailored to user accessibility and health needs, and more understanding of what hinders frequent users of digital technologies and those with long-term conditions is required. This novel application of WTP in a digital health context demonstrates an economic argument for investing in upskilling the population to promote access and expedite uptake and utilization of such digital health and well-being apps.

  • iCanCope app. Source: The Authors; Copyright: The Hospital for Sick Children and University Health Network; URL: http://mhealth.jmir.org/2019/1/e11838/; License: Licensed by the authors.

    Capturing Daily Disease Experiences of Adolescents With Chronic Pain: mHealth-Mediated Symptom Tracking

    Abstract:

    Background: Chronic pain is a common problem in adolescents that can negatively impact all aspects of their health-related quality of life. The developmental period of adolescence represents a critical window of opportunity to optimize and solidify positive health behaviors and minimize future pain-related disability and impaired work productivity. This research focuses on the development and evaluation of a smartphone-based pain self-management app for adolescents with chronic pain. Objective: The objectives of this study were to characterize (1) the feasibility of deploying a mobile health (mHealth) app (iCanCope) to the personal smartphones of adolescent research participants; (2) adherence to daily symptom tracking over 55 consecutive days; (3) participant interaction with their symptom history; and (4) daily pain-related experiences of adolescents with chronic pain. Methods: We recruited adolescents aged 15-18 years from 3 Canadian pediatric tertiary care chronic pain clinics. Participants received standardized instructions to download the iCanCope app and use it once a day for 55 days. Detailed app analytics were captured at the user level. Adherence was operationally defined as per the relative proportion of completed symptom reports. Linear mixed models were used to examine the trajectories of daily symptom reporting. Results: We recruited 60 participants between March 2017 and April 2018. The mean age of the participants was 16.4 (SD 0.9) years, and 88% (53/60) of them were female. The app was deployed to 98% (59/60) devices. Among the 59 participants, adherence was as follows: low (4, 7%), low-moderate (14, 24%), high-moderate (16, 27%), and high (25, 42%). Most (49/59, 83%) participants chose to view their historical symptom trends. Participants reported pain intensity and pain-related symptoms of moderate severity, and these ratings tended to be stable over time. Conclusions: This study indicates that (1) the iCanCope app can be deployed to adolescents’ personal smartphones with high feasibility; (2) adolescents demonstrated moderate-to-high adherence over 55 days; (3) most participants chose to view their symptom history; and (4) adolescents with chronic pain experience stable symptomology of moderate severity. Trial Registration: ClinicalTrials.gov NCT02601755; https://clinicaltrials.gov/ct2/show/NCT02601755 (Archived by WebCite at http://www.webcitation.org/74F4SLnmc)

  • Doctors using mobile EHR. Source: Image created by the Authors; Copyright: The Authors; URL: http://mhealth.jmir.org/2019/1/e12041/; License: Creative Commons Attribution (CC-BY).

    Variability in Doctors’ Usage Paths of Mobile Electronic Health Records Across Specialties: Comprehensive Analysis of Log Data

    Abstract:

    Background: With the emergence of mobile devices, mobile electronic health record (mEHR) systems have been utilized by health care professionals (HCPs), including doctors, nurses, and other practitioners, to improve efficiency at the point of care. Although several studies on mEHR systems were conducted, including those analyzing their effects and HCPs’ usage frequency, only a few considered the specific workflows of doctors based on their specialties in which the work process differs greatly. Objective: This study aimed to investigate the differences in mEHR usage paths across clinical specialties. Methods: We collected the log data of 974 doctors who worked from August 2016 to August 2017 and used the mEHR system at the Samsung Medical Center, one of the biggest hospitals in South Korea. The doctors were classified into 3 groups based on their specialty: the physician, the surgeon, and other hospital-based physician (OHBP) groups. We used various descriptive and visualization methods to understand and compare doctors’ usage paths of mEHRs. First, the average numbers of log-ins per day and features used per log-in were examined over different specialties and positions. Second, the number of features used by each doctor was visualized via a heat map to provide an overview of mEHR usage across feature types and doctors’ specialties. Third, we conducted a path analysis via a Sankey diagram to describe main usage paths and association rule mining to find frequent paths in mEHR usage. Results: The physician group logged on most frequently, whereas the OHBP group logged on least frequently. In fact, the number of log-ins per day of residents in the physician group was 4.4 times higher than that of staff members in the other groups. The heat map visualization showed a visible difference among specialty groups. The physician group used more consultation-related features, whereas the surgeon group used more surgery-related features. Generally, 50% of the doctors spent about 15 seconds at a time when using mEHRs. In the Sankey diagram, the physician group showed diverse usage patterns with higher complexity compared with the other 2 groups; in particular, their paths contained more loops, which reflected repetitive checks on multiple patients. The most frequent path included inpatient summary, which means that most users stopped at the point of summary and did not proceed to view more details. Conclusions: The usage paths of mEHRs showed considerable differences among the specialty groups. Such differences can be accommodated into an mEHR design to enhance the efficiency of care.

  • Source: Freepik; Copyright: Katemangostar; URL: https://www.freepik.com/free-photo/pensive-young-caucasian-woman-in-lab-coat-holding-phone_3584935.htm; License: Licensed by JMIR.

    Factors for Supporting Primary Care Physician Engagement With Patient Apps for Type 2 Diabetes Self-Management That Link to Primary Care: Interview Study

    Abstract:

    Background: The health burden of type 2 diabetes can be mitigated by engaging patients in two key aspects of diabetes care: self-management and regular contact with health professionals. There is a clear benefit to integrating these aspects of care into a single clinical tool, and as mobile phone ownership increases, apps become a more feasible platform. However, the effectiveness of online health interventions is contingent on uptake by health care providers, which is typically low. There has been little research that focuses specifically on barriers and facilitators to health care provider uptake for interventions that link self-management apps to the user’s primary care physician (PCP). Objective: This study aimed to explore PCP perspectives on proposed features for a self-management app for patients with diabetes that would link to primary care services. Methods: Researchers conducted 25 semistructured interviews. The interviewer discussed potential features that would link in with the patient’s primary care services. Interviews were audio-recorded, transcribed, and coded. Framework analysis and the Consolidated Criteria for Reporting Qualitative Research checklist were employed to ensure rigor. Results: Our analysis indicated that PCP attitudes toward proposed features for an app were underpinned by perceived roles of (1) diabetes self-management, (2) face-to-face care, and (3) the anticipated burden of new technologies on their practice. Theme 1 explored PCP perceptions about how an app could foster patient independence for self-management behaviors but could also increase responsibility and liability for the PCP. Theme 2 identified beliefs underpinning a commonly expressed preference for face-to-face care. PCPs perceived information was more motivating, better understood, and presented with greater empathy when delivered face to face rather than online. Theme 3 described how most PCPs anticipated an initial increase in workload while they learned to use a new clinical tool. Some PCPs accepted this burden on the basis that the change was inevitable as health care became more integrated. Others reported potential benefits were outweighed by effort to implement an app. This study also identified how app features can be positively framed, highlighting potential benefits for PCPs to maximize PCP engagement, buy-in, and uptake. For example, PCPs were more positive when they perceived that an app could facilitate communication and motivation between consultations, focus on building capacity for patient independence, and reinforce rather than replace in-person care. They were also more positive about app features that were automated, integrated with existing software, flexible for different patients, and included secondary benefits such as improved documentation. Conclusions: This study provided insight into PCP perspectives on a diabetes app integrated with primary care services. This was observed as more than a technological change; PCPs were concerned about changes in workload, their role in self-management, and the nature of consultations. Our research highlighted potential facilitators and barriers to engaging PCPs in the implementation process.

  • Source: Flickr; Copyright: Victor; URL: https://www.flickr.com/photos/v1ctor/10871254373/in/photolist-hyE2be-4vGMmS-2dH7exW-aWtmCa-phZ3XD-21SfAKy-enD3ff-297vH8d-eeQDLy-N3BVec-NQKnJC-3C2rUT-BSW1Y-5uhCrA-bA5Nx1-L6Gwo-pBVAkU-RGgEU9-27ZGBEt-4PHiMr-3NkWZW-cQu8Ho-293ocsq-2Vw7wA-2bdN6Eo-2bxaCYx-6g9xTZ; License: Creative Commons Attribution (CC-BY).

    Examining Diabetes Management Apps Recommended From a Google Search: Content Analysis

    Abstract:

    Background: The availability of smartphone health apps empowers people to manage their own health. Currently, there are over 300,000 health apps available in the market targeting a variety of user needs from weight loss to management of chronic conditions, with diabetes being the most commonly targeted condition. To date, health apps largely fall outside government regulation, and there are no official guidelines to help clinicians and patients in app selection. Patients commonly resort to the internet for suggestions on which diabetes app to use. Objective: The objective of this study was to investigate apps identified through a Google search and characterize these apps in terms of features that support diabetes management. Methods: We performed a Google search for the “best diabetes apps 2017” and explored the first 4 search results. We identified and compiled a list of the apps recommended in the returned search results, which were Web articles. Information about each app was extracted from the papers and corresponding app store descriptions. We examined the apps for the following diabetes management features: medication management, blood glucose self-management, physical activity, diet and nutrition, and weight management. Results: Overall, 26 apps were recommended in 4 papers. One app was listed in all 4 papers, and 3 apps appeared on 3 of the 4 lists. Apart from one paper, there were no explicit criteria to justify or explain the selection of apps. We found a wide variation in the type and the number of diabetes management features in the recommended apps. Five apps required payment to be used. Two-thirds of the apps had blood glucose management features, and less than half had medication management features. The most prevalent app features were nutrition or diet-related (19/24, 79%) and physical activity tracking (14/24, 58%). Conclusions: The ambiguity of app selection and the wide variability in key features of the apps recommended for diabetes management may pose difficulties for patients when selecting the most appropriate app. It is critical to involve patients, clinicians, relevant professional bodies, and policy makers to define the key features an app should have for it to be classified as a “diabetes management” app. The lessons learned here may be extrapolated for the development and recommendation of apps for the management of other chronic conditions.

  • Source: Pexels; Copyright: rawpixels.com; URL: https://www.pexels.com/photo/three-person-holding-smartphones-1061579/; License: Licensed by the authors.

    Public Views on Using Mobile Phone Call Detail Records in Health Research: Qualitative Study

    Abstract:

    Background: Mobile phone call detail records (CDRs) are increasingly being used in health research. The location element in CDRs is used in various health geographic studies, for example, to track population movement and infectious disease transmission. Vast volumes of CDRs are held by multinational organizations, which may make them available for research under various data governance regimes. However, there is an identified lack of public engagement on using CDRs for health research to contribute to an ethically founded framework. Objective: This study aimed to explore public views on the use of call detail records in health research. Methods: Views on using CDRs in health research were gained via a series of three public workshops (N=61) informed by a pilot workshop of 25 people. The workshops included an initial questionnaire to gauge participants’ prior views, discussion on health research using CDRs, and a final questionnaire to record workshop outcome views. The resulting data were analyzed for frequencies and emerging themes. Results: At the outset, most participants (66%, 40/61) knew that location data were collected by operators, but only 3% (2/61) knew they were being used for health research. Initially, the majority of the participants (62%, 38/61) was content for their anonymous CDRs to be used, and this increased (80%, 49/61) after the discussion explained that safeguards were in place. Participants highlighted that terms and conditions should be clearer, as should information to phone users on data collection, privacy safeguards, sharing, and uses in research. Conclusions: This is the first known study exploring public views of using mobile phone CDRs in health research. It revealed a lack of knowledge among the public on uses of CDRs and indicated that people are generally amenable to the use of anonymized data for research, but they want to be properly informed and safeguarded. We recommend that public views be incorporated into an ethically founded framework for the use of CDRs in health research to promote awareness and social acceptability in data use.

  • Music eScape app (montage). Source: The Authors / Placeit; Copyright: JMIR Publications; URL: http://mhealth.jmir.org/2019/1/e11482/; License: Creative Commons Attribution (CC-BY).

    Efficacy and Outcomes of a Music-Based Emotion Regulation Mobile App in Distressed Young People: Randomized Controlled Trial

    Abstract:

    Background: Emotion dysregulation increases the risk of depression, anxiety, and substance use disorders. Music can help regulate emotions, and mobile phones provide constant access to it. The Music eScape mobile app teaches young people how to identify and manage emotions using music. Objective: This study aimed to examine the effects of using Music eScape on emotion regulation, distress, and well-being at 1, 2, 3, and 6 months. Moderators of outcomes and user ratings of app quality were also examined. Methods: A randomized controlled trial compared immediate versus 1-month delayed access to Music eScape in 169 young people (aged 16 to 25 years) with at least mild levels of mental distress (Kessler 10 score>17). Results: No significant differences between immediate and delayed groups on emotion regulation, distress, or well-being were found at 1 month. Both groups achieved significant improvements in 5 of the 6 emotion regulation skills, mental distress, and well-being at 2, 3, and 6 months. Unhealthy music use moderated improvements on 3 emotion regulation skills. Users gave the app a high mean quality rating (mean 3.8 [SD 0.6]) out of 5. Conclusions: Music eScape has the potential to provide a highly accessible way of improving young people’s emotion regulation skills, but further testing is required to determine its efficacy. Targeting unhealthy music use in distressed young people may improve their emotion regulation skills. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12615000051549; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=365974

  • Source: Pixabay; Copyright: Fotorech; URL: https://pixabay.com/en/walk-path-walking-feet-trail-2635038/; License: Public Domain (CC0).

    User Models for Personalized Physical Activity Interventions: Scoping Review

    Abstract:

    Background: Fitness devices have spurred the development of apps that aim to motivate users, through interventions, to increase their physical activity (PA). Personalization in the interventions is essential as the target users are diverse with respect to their activity levels, requirements, preferences, and behavior. Objective: This review aimed to (1) identify different kinds of personalization in interventions for promoting PA among any type of user group, (2) identify user models used for providing personalization, and (3) identify gaps in the current literature and suggest future research directions. Methods: A scoping review was undertaken by searching the databases PsycINFO, PubMed, Scopus, and Web of Science. The main inclusion criteria were (1) studies that aimed to promote PA; (2) studies that had personalization, with the intention of promoting PA through technology-based interventions; and (3) studies that described user models for personalization. Results: The literature search resulted in 49 eligible studies. Of these, 67% (33/49) studies focused solely on increasing PA, whereas the remaining studies had other objectives, such as maintaining healthy lifestyle (8 studies), weight loss management (6 studies), and rehabilitation (2 studies). The reviewed studies provide personalization in 6 categories: goal recommendation, activity recommendation, fitness partner recommendation, educational content, motivational content, and intervention timing. With respect to the mode of generation, interventions were found to be semiautomated or automatic. Of these, the automatic interventions were either knowledge-based or data-driven or both. User models in the studies were constructed with parameters from 5 categories: PA profile, demographics, medical data, behavior change technique (BCT) parameters, and contextual information. Only 27 of the eligible studies evaluated the interventions for improvement in PA, and 16 of these concluded that the interventions to increase PA are more effective when they are personalized. Conclusions: This review investigates personalization in the form of recommendations or feedback for increasing PA. On the basis of the review and gaps identified, research directions for improving the efficacy of personalized interventions are proposed. First, data-driven prediction techniques can facilitate effective personalization. Second, use of BCTs in automated interventions, and in combination with PA guidelines, are yet to be explored, and preliminary studies in this direction are promising. Third, systems with automated interventions also need to be suitably adapted to serve specific needs of patients with clinical conditions. Fourth, previous user models focus on single metric evaluations of PA instead of a potentially more effective, holistic, and multidimensional view. Fifth, with the widespread adoption of activity monitoring devices and mobile phones, personalized and dynamic user models can be created using available user data, including users’ social profile. Finally, the long-term effects of such interventions as well as the technology medium used for the interventions need to be evaluated rigorously.

  • Medical licentiate students during training with their tablets. Source: Image created by the Authors; Copyright: Sandra Barteit; URL: http://mhealth.jmir.org/2019/1/e12637/; License: Creative Commons Attribution + Noncommercial + NoDerivatives (CC-BY-NC-ND).

    Perspectives of Nonphysician Clinical Students and Medical Lecturers on Tablet-Based Health Care Practice Support for Medical Education in Zambia, Africa:...

    Abstract:

    Background: Zambia is faced with a severe shortage of health workers and challenges in national health financing. This burdens the medical licentiate practitioner (MLP) program for training nonphysician clinical students in Zambia because of the shortage of qualified medical lecturers and learning resources at training sites. To address this shortage and strengthen the MLP program, a self-directed electronic health (eHealth) platform was introduced, comprising technology-supported learning (e-learning) for medical education and support for health care practice. MLP students were provided with tablets that were preloaded with content for offline access. Objective: This study aimed to explore MLP students’ and medical lecturers’ perceptions of the self-directed eHealth platform with an offline-based tablet as a training and health care practice support tool during the first year of full implementation. Methods: We conducted in-depth qualitative interviews with 8 MLP students and 5 lecturers and 2 focus group discussions with 16 students to gain insights on perceptions of the usefulness, ease of use, and adequacy of self-directed e-learning and health care practice support accessible through the offline-based tablet. Participants were purposively sampled. Verbatim transcripts were analyzed following hypothesis coding. Results: The eHealth platform (e-platform), comprising e-learning for medical education and health care practice support, was positively received by students and medical lecturers and was seen as a step toward modernizing the MLP program. Tablets enabled equal access to offline learning contents, thus bridging the gap of slow or no internet connections. The study results indicated that the e-platform appears adequate to strengthen medical education within this low-resource setting. However, student self-reported usage was low, and medical lecturer usage was even lower. One stated reason was the lack of training in tablet usage and another was the quality of the tablets. The mediocre quality and quantity of most e-learning contents were perceived as a primary concern as materials were reported to be outdated, missing multimedia features, and addressing only part of the curriculum. Medical lecturers were noted to have little commitment to updating or creating new learning materials. Suggestions for improving the e-platform were given. Conclusions: To address identified major challenges, we plan to (1) introduce half-day training sessions at the beginning of each study year to better prepare users for tablet usage, (2) further update and expand e-learning content by fostering collaborations with MLP program stakeholders and nominating an e-platform coordinator, (3) set up an e-platform steering committee including medical lecturers, (4) incorporate e-learning and e-based health care practice support across the curriculum, as well as (5) implement processes to promote user-generated content. With these measures, we aim to sustainably strengthen the MLP program by implementing the tablet-based e-platform as a serious learning technology for medical education and health care practice support.

  • Source: Flickr; Copyright: Marco Verch; URL: https://www.flickr.com/photos/160866001@N07/44573043810/; License: Creative Commons Attribution (CC-BY).

    Health Benefits and Cost-Effectiveness From Promoting Smartphone Apps for Weight Loss: Multistate Life Table Modeling

    Abstract:

    Background: Obesity is an important risk factor for many chronic diseases. Mobile health interventions such as smartphone apps can potentially provide a convenient low-cost addition to other obesity reduction strategies. Objective: This study aimed to estimate the impacts on quality-adjusted life-years (QALYs) gained and health system costs over the remainder of the life span of the New Zealand population (N=4.4 million) for a smartphone app promotion intervention in 1 calendar year (2011) using currently available apps for weight loss. Methods: The intervention was a national mass media promotion of selected smartphone apps for weight loss compared with no dedicated promotion. A multistate life table model including 14 body mass index–related diseases was used to estimate QALYs gained and health systems costs. A lifetime horizon, 3% discount rate, and health system perspective were used. The proportion of the target population receiving the intervention (1.36%) was calculated using the best evidence for the proportion who have access to smartphones, are likely to see the mass media campaign promoting the app, are likely to download a weight loss app, and are likely to continue using this app. Results: In the base-case model, the smartphone app promotion intervention generated 29 QALYs (95% uncertainty interval, UI: 14-52) and cost the health system US $1.6 million (95% UI: 1.1-2.0 million) with the standard download rate. Under plausible assumptions, QALYs increased to 59 (95% UI: 27-107) and costs decreased to US $1.2 million (95% UI: 0.5-1.8) when standard download rates were doubled. Costs per QALY gained were US $53,600 for the standard download rate and US $20,100 when download rates were doubled. On the basis of a threshold of US $30,000 per QALY, this intervention was cost-effective for Māori when the standard download rates were increased by 50% and also for the total population when download rates were doubled. Conclusions: In this modeling study, the mass media promotion of a smartphone app for weight loss produced relatively small health gains on a population level and was of borderline cost-effectiveness for the total population. Nevertheless, the scope for this type of intervention may expand with increasing smartphone use, more easy-to-use and effective apps becoming available, and with recommendations to use such apps being integrated into dietary counseling by health workers.

  • Source: Flickr; Copyright: Marco Verch; URL: https://www.flickr.com/photos/160866001@N07/31743798047; License: Creative Commons Attribution (CC-BY).

    Use of Health Apps and Wearable Devices: Survey Among Italian Associations for Patient Advocacy

    Abstract:

    Background: Technological tools such as Web-based social networks, telemedicine, apps, or wearable devices are becoming more widespread in health care like elsewhere. Although patients are the main users, for example, to monitor symptoms and clinical parameters or to communicate with the doctor, their perspective is seldom analyzed, and to the best of our knowledge, no one has focused on the patients’ health care advocacy associations’ point of view. Objective: The objective of this study was to assess patients’ health care advocacy associations’ opinions about the use, usefulness, obstacles, negative aspects, and impact of health apps and wearable devices through a Web-based survey. Methods: We conducted a Web-based survey through SurveyMonkey over nearly 3 months. Participants were contacted via an email explaining the aims of the survey and providing a link to complete the Web-based questionnaire. All the 20 items were mandatory, and the anonymized data were collected automatically into a database. Only fully completed questionnaires were considered for analysis. Results: We contacted 1998 patients’ health care advocacy associations; a total of 258 questionnaires were received back (response rate 12.91%), and 227 of the received questionnaires were fully completed (completion rate 88.0%). Informative apps, hospital apps for viewing medical reports or booking visits, and those for monitoring physical activity are the most used. They are considered especially useful to improve patients’ engagement and compliance with treatment. Wearable devices to check physical activity and glycemia are the most widespread considering, again, their benefits in increasing patients’ involvement and treatment compliance. For health apps and wearable devices, the main obstacles to their use are personal and technical reasons; the risk of overmedicalization is considered the most negative aspect of their constant use, while privacy and confidentiality of data are not rated a limitation. No statistical difference was found on stratifying the answers by responders’ technological level (P=.30), age (P=.10), and the composition of the association’s advisory board (P=.15). Conclusions: According to responders, health apps and wearable devices are sufficiently known and used and are considered potential supports for greater involvement in health management. However, there are still obstacles to their adoption, and the developers need to work to make them more accessible and more useful. The involvement of patients and their associations in planning services and products based on these technologies (as well as others) would be desirable to overcome these barriers and boost awareness about privacy and the confidentiality of data.

  • Source: Flickr; Copyright: Philips Communications; URL: https://www.flickr.com/photos/philips_newscenter/21246464018; License: Creative Commons Attribution + Noncommercial + NoDerivatives (CC-BY-NC-ND).

    The Efficacy of Mobile Phone Apps for Lifestyle Modification in Diabetes: Systematic Review and Meta-Analysis

    Abstract:

    Background: Diabetes and related complications are estimated to cost US $727 billion worldwide annually. Type 1 diabetes, type 2 diabetes, and gestational diabetes are three subtypes of diabetes that share the same behavioral risk factors. Efforts in lifestyle modification, such as daily physical activity and healthy diets, can reduce the risk of prediabetes, improve the health levels of people with diabetes, and prevent complications. Lifestyle modification is commonly performed in a face-to-face interaction, which can prove costly. Mobile phone apps provide a more accessible platform for lifestyle modification in diabetes. Objective: This review aimed to summarize and synthesize the clinical evidence of the efficacy of mobile phone apps for lifestyle modification in different subtypes of diabetes. Methods: In June 2018, we conducted a literature search in 5 databases (Cochrane Central Register of Controlled Trials, MEDLINE, Embase, CINAHL, and PsycINFO). We evaluated the studies that passed screening using The Cochrane Collaboration’s risk of bias tool. We conducted a meta-analysis for each subtype on the mean difference (between intervention and control groups) at the posttreatment glycated hemoglobin (HbA1c) level. Where possible, we analyzed subgroups for short-term (3-6 months) and long-term (9-12 months) studies. Heterogeneity was assessed using the I2 statistic. Results: We identified total of 2669 articles through database searching. After the screening, we included 26 articles (23 studies) in the systematic review, of which 18 studies (5 type 1 diabetes, 11 type 2 diabetes, and 2 prediabetes studies) were eligible for meta-analysis. For type 1 diabetes, the overall effect on HbA1c was statistically insignificant (P=.46) with acceptable heterogeneity (I2=39%) in the short-term subgroup (4 studies) and significant heterogeneity between the short-term and long-term subgroups (I2=64%). Regarding type 2 diabetes, the overall effect on HbA1c was statistically significant (P<.01) in both subgroups, and when the 2 subgroups were combined, there was virtually no heterogeneity within and between the subgroups (I2 range 0%-2%). The effect remained statistically significant (P<.01) after adjusting for publication bias using the trim and fill method. For the prediabetes condition, the overall effect on HbA1c was statistically insignificant (P=.67) with a large heterogeneity (I2=65%) between the 2 studies. Conclusions: There is strong evidence for the efficacy of mobile phone apps for lifestyle modification in type 2 diabetes. The evidence is inconclusive for the other diabetes subtypes.

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    Open Peer Review Period: Jan 15, 2019 - Mar 12, 2019

    Background: The last decade has seen a substantial increase in the use of mobile health apps and research into the effects of those apps on health and health behaviour. In parallel, research has aimed...

    Background: The last decade has seen a substantial increase in the use of mobile health apps and research into the effects of those apps on health and health behaviour. In parallel, research has aimed at identifying population subgroups that are more likely to use those health apps. There are two major limitations to the present evidence base. First, research into mobile health apps has focused on vary broad health apps or health apps for behavioral categories. No research has investigated which population subgroups are more likely to use apps for a specific health behaviour. In this study, we focused on walking apps. Second, research has tended to focus on health app users versus non-users: little research effort has been directed at subgroups of non-users, including populations who previously used apps but decided not to use them anymore. Objective: We aimed to provide profile distributions of current users, previous users, and informed non-users, and to identify predictor variables relevant for profile classification. Methods: Data were available from 1683 participants who were participants of a national walking event in September 2017. They provided information on demographics, walking behaviour and walking app usage, and items from User Acceptance of Information Technology, in an online survey. Data were analyzed using discriminant function analyses and multinominal logistic regression analysis. Results: The majority was a current walking app user (n = 899, 53.4%) and only a small part was a previous walking app user (n = 121, 7.2%). Current walking app users were more likely to walk on at least five days per week and for at least 30 minutes for bout (OR = 1.4, 95% CI [1.1; 1.9], P = .005), but also to be more likely to be overweight, OR = 1.7, 95% CI [1.2 - 2.4], P = .001, or obese, OR = 1.4, 95% CI [1.1; 1.9], P = .005, as compared to informed non-users. Further, current walking app users perceived the app to be less boring, to be easier to ease and to retrieve information, and to be more helpful to obtain their goal. Effect sizes ranged from 0.10, 95% CI [0.08 – 0.30] to 1.58, 95% CI [1.47 – 1.70]. Conclusions: Results demonstrated the usefulness to focus on behaviour-specific apps and on subgroups of non-users. The findings provide indications for health practitioners to stimulate walking app usage. For app-developers, findings indicate suggestions to prevent people to stop using (walking) apps.

  • Sleep Apps for Youth: A Scoping Review of What is Available and What is Needed

    Date Submitted: Jan 14, 2019

    Open Peer Review Period: Jan 15, 2019 - Mar 12, 2019

    Background: Sleep difficulties are prevalent and concerning for many North Americans. Despite strong empirical support for insomnia treatment, lack of access presents a significant barrier to treatmen...

    Background: Sleep difficulties are prevalent and concerning for many North Americans. Despite strong empirical support for insomnia treatment, lack of access presents a significant barrier to treatment dissemination. This is particularly true amongst teens and young adults. Mobile applications (‘apps’) are uniquely suited to address this need. Objective: We conducted a scoping review to identify and appraise commercially available apps for AYAs with sleep difficulties. Methods: Proceeding in 3 phases, a comprehensive search of commercially available apps was conducted between August 2016 and January 2017. The initial phase involved a search of app stores using relevant search terms (sleep; sleeping; insomnia; sleep aid; night). In the second phase, apps were assessed for eligibility using the following inclusion criteria: 1) Goal is to provide education, tools, or advice related to management of insomnia symptoms. 2) Primary intended users are AYAs. Exclusion criteria were: 1) App is classified as an ‘e-book.’ 2) Primary utility is meditation, hypnosis, or relaxation for sleep. 3) Primary function is background sleep music or sounds. 4) Primary function is alarm clock. 5) Sole sleep aid function is tracking/monitoring, with no education, tools, or advice for insomnia. In the third phase, apps were culled for functionality information, including: A) Self-monitoring of symptoms; B) Tracking sleep; C) Education related to insomnia; D) Advice or intervention for managing insomnia symptoms. Finally, the primary investigator conducted a final review of phase 3 apps, closely examining the functionality of these apps, based on app descriptions, app content, and developer website (where available). Results: The initial search yielded 2036 apps; after eligibility criteria were applied, functionality information was extracted for 48 apps. Twenty-three of these were later excluded. Of the final 25 apps, 24% included self-monitoring of symptoms; 28% included a sleep tracking function; 56% provided insomnia education; and 92% provided advice or intervention for managing sleep difficulties. The majority (80%) were free. Several (20%) provided sleep interventions that are not supported by research. In the final evaluation, only 6 apps met all four of the functionality criteria; of these, none were geared towards AYA users specifically. The purported and examined functionality of these six apps are discussed. Conclusions: Insomnia is a unique problem among AYAs, as non-insomnia factors must also be considered when designing an appropriate intervention (e.g., AYAs are more delayed in sleep schedule, require more sleep than adults). There are currently 6 apps that are appropriate for self-management of adult insomnia. There are 0 apps designed for AYA users. Development of an evidence-based app for managing insomnia in this population is critical. Once an appropriate app becomes available, future studies should test its usability and efficacy in AYA samples.

  • Development of Smartphone Applications for Skin Cancer Risk Assessment: Progress and Promise.

    Date Submitted: Jan 14, 2019

    Open Peer Review Period: Jan 14, 2019 - Mar 11, 2019

    Skin cancer is a growing public health problem. Early and accurate detection is important, since prognosis and cost of treatment is highly dependent on cancer stage at detection. However, access to sp...

    Skin cancer is a growing public health problem. Early and accurate detection is important, since prognosis and cost of treatment is highly dependent on cancer stage at detection. However, access to specialized health care professionals is not always straightforward and population screening programs are unlikely to become implemented. Furthermore, there is a wide margin for improving efficiency of skin cancer diagnostics. Namely, the diagnostic accuracy of general practitioners and family physicians (GPs) in differentiating benign and malignant skin tumors is relatively low. Both access to care and diagnostic accuracy fuel the interest in developing smartphone applications (SAs) equipped with algorithms for image analyses of suspicious lesions to detect skin cancer. Based on a recent review, seven smartphone apps claim to do image analyses for skin cancer detection, but as of October 2018, only 3 seem to be active. They have been criticized in the past due to their lack of diagnostic accuracy. Here we review the development of the SkinVision smartphone application (SVA) which has more than 900,000 users worldwide. The latest version of SVA (October 2018) has a 95% sensitivity (78% specificity) to detect skin cancer. The current accuracy of the algorithm may warrant the usage of this SA as an aid by lay users or general practitioners. Nonetheless, in order for mHealth apps to become broadly accepted, further research is needed on its health impact both for the health system and in the population. Ultimately, mHealth apps could become a powerful tool to curb healthcare costs related to skin cancer management, and minimize the morbidity of skin cancer in the population.

  • Prevalence of Schistosoma haematobium in an unexplored endemic region in the sub-prefecture of Torrock, Chad

    Date Submitted: Jan 10, 2019

    Open Peer Review Period: Jan 14, 2019 - Mar 11, 2019

    Background: Schistosoma haematobium is a parasitic digenetic trematode responsible for schistosomiasis (also known as bilharzia). The disease is caused by penetration of the skin by the parasite, spre...

    Background: Schistosoma haematobium is a parasitic digenetic trematode responsible for schistosomiasis (also known as bilharzia). The disease is caused by penetration of the skin by the parasite, spread by intermediate host molluscs in stagnant waters, and can be treated by administration of praziquantel. Objective: . The aim of this study was to investigate the prevalence of schistosomiasis in the sub-prefecture of Torrock, an endemic area in Chad where no earlier investigation had been conducted, and no distribution system for pharmacotherapy has ever existed. Methods: The study examined 1,875 children aged 1–14 years, over a period of one year. After centrifugation, urine examination was performed by direct microscopic investigation for eggs. The investigation was conducted with a mobile health (M-health) approach, using short messaging service (SMS) to communicate among parents, local health workers, a pharmacist and a medical doctor. An initial awareness campaign requested parents to have their children examined for schistosomiasis. Urine was then collected at home following SMS request by the parents. Urine results that proved positive were sent to a medical doctor by SMS, who in turn ordered a pharmacist by SMS to distribute praziquantel to the infected children. Results: : Direct microscopic examination of urine found 467 positive cases (24.9% of the total sample). Of all male and female samples, 341 (34 %) and 127 (14.4 %) samples were positive, respectively. The infection rate was equally distributed over age groups. The newly developed M-health system had a limited level of participation (8%) from an estimated total of 25,000 children in the target group. Conclusions: The prevalence of schistosomiasis in children in the sub-prefecture of Torrock is moderately high. Efforts will be required to enhance the awareness of parents and to reach a larger percentage of the population. Systematic governmental measures should be put in place as soon as possible to increase awareness in the area and to diagnose and treat cases of schistosomiasis.

  • A randomised controlled pilot trial evaluating an Internet-based cognitive-behavioural program for adolescents with anxiety

    Date Submitted: Jan 10, 2019

    Open Peer Review Period: Jan 14, 2019 - Mar 11, 2019

    Background: Internet-based cognitive-behavioural therapy (ICBT) is a newer studied treatment format that provides frontline treatment to adolescents with anxiety disorders. Objective: This study pilot...

    Background: Internet-based cognitive-behavioural therapy (ICBT) is a newer studied treatment format that provides frontline treatment to adolescents with anxiety disorders. Objective: This study piloted procedures and obtained data on methodological processes and intervention satisfaction to determine the feasibility of a definitive randomised controlled trial (RCT) of the effectiveness of a self-managed ICBT program, Breathe (Being Real, Easing Anxiety: Tools Helping Electronically), for adolescents with anxiety concerns. Methods: Two-arm, multi-site, pilot RCT. Adolescents aged 13–17 years with a self-identified anxiety concern were recruited online, from health care settings, and from school-based mental health care services across Canada between April 2014 and May 2016. We compared 8 weeks of ICBT with limited telephone and e-mail support (Breathe experimental group) to access to a static webpage listing anxiety resources (control group). The primary outcome was the change in self-reported anxiety on the MASC2 from baseline to 8 weeks (post-treatment) in order to determine a sample size for a definitive RCT. Secondary outcomes were recruitment and retention rates, a minimal clinically important difference (MCID) for the primary outcome, intervention acceptability and satisfaction, use of co-interventions, and health care resource use, including a cost-consequence analysis. Results: Of the 588 adolescents screened, 94 adolescents were eligible and enrolled in the study (49 adolescents were allocated to the Breathe group and 45 allocated to the control group). Analysis was based on 70/94 adolescents who completed baseline measures and progressed through the study. Enrolled adolescents were, on average, 15.3 years old (standard deviation, SD: 1.2) and female (90.0%). The retention rates at 8 weeks were 28.3% (Breathe group) and 58.1% (control group). Fourteen (38.9%) adolescents provided feedback at the completion of the Breathe program. The mean satisfaction score among these adolescents was 28.5/40 (SD 4.0) indicating modest satisfaction. All but one adolescent indicated that the Breathe program was easy to use and that they had understood all the material presented within the program. The most frequent barrier identified for program completion was difficulty in completing exposure activities. The power analysis indicated that 177 adolescents per group would be needed to detect a medium effect size (d=0.3) between groups in a definitive trial. Data for calculating a MCID or conducting a cost-consequence analysis were insufficient due to a low participant response rate. Conclusions: Adolescents were moderately satisfied with the Breathe program. However, program adjustments are needed to address attrition during program use and reduce adolescents’ perceived barriers to completing key aspects of the program. A definitive RCT to evaluate the effectiveness of the program will be feasible if protocol adjustments are made to improve the study’s recruitment and retention rates to ensure timely study completion and increase the completeness of the data at each outcome measurement time-point. Clinical Trial: clinicaltrials.gov NCT02059226

  • Estimating VO2max with Daily Activity Data Measured by a Watch-type Fitness Tracker

    Date Submitted: Jan 8, 2019

    Open Peer Review Period: Jan 11, 2019 - Mar 8, 2019

    Background: Cardiorespiratory fitness (CRF), an important index of physical fitness, is the ability to take in and provide oxygen to the exercising muscle. However, despite its importance, the current...

    Background: Cardiorespiratory fitness (CRF), an important index of physical fitness, is the ability to take in and provide oxygen to the exercising muscle. However, despite its importance, the current gold standard for measuring CRF is impractical, requiring a maximal exercise from the participants. Objective: This study aimed to develop a convenient and practical estimation model for CRF using data collected from daily life with a wristwatch-type device. Methods: A total of 191 subjects, aged 20 to 65 years old, participated in this study. Maximal oxygen uptake (VO2max), a standard measure of CRF, was measured with a maximal exercise test. Heart rate (HR) and physical activity data were collected using a commercial wristwatch-type fitness tracker (Fitbit) for 3 consecutive days. Maximal activity energy expenditure (aEEmax) and slope between HR and physical activity were calculated by a linear regression. A VO2max estimation model was built using multiple linear regression with data on age, sex, height, percentage body fat, aEEmax, and the slope. The result was validated with two different cross-validation methods. Results: aEEmax showed a moderate correlation with VO2max (r = 0.50). The correlation coefficient for the multiple linear regression model was 0.81, and the standard error of estimate (SEE) was 3.518 mL/kg/min. The regression model was cross-validated through the predicted residual error sum of square (PRESS). The PRESS correlation coefficient was 0.79, and the PRESS SEE was 3.667 mL/kg/min. The model was further validated by dividing into different subgroups and calculating the constant error (CE) where, the low CE showed that the model does not significantly overestimate or underestimate VO2max. Conclusions: This study proposes a CRF estimation method using data collected by a wristwatch-type fitness tracker without any specific protocol for a wide range of population.

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