Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?


Journal Description

JMIR mHealth and uHealth (JMU, ISSN 2291-5222; Impact Factor 4.301) is a sister journal of JMIR, the leading eHealth journal. JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, Scopus, MEDLINE and Science Citation Index Expanded (SCIE), and in June 2019 received an Impact Factor of 4.301, which ranks the journal #2 (behind JMIR) 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:

  • Source: The Authors / Wikimedia Commons; Copyright: The Authors / Sage Ross; URL:,_2015-04-16.jpg; License: Creative Commons Attribution + ShareAlike (CC-BY-SA).

    Health Observation App for COVID-19 Symptom Tracking Integrated With Personal Health Records: Proof of Concept and Practical Use Study


    Background: As a counter-cluster measure to prevent the spread of the infectious novel coronavirus disease (COVID-19), an efficient system for health observation outside the hospital is urgently required. Personal health records (PHRs) are suitable for the daily management of physical conditions. Importantly, there are no major differences between the items collected by daily health observation via PHR and the observation of items related to COVID-19. Until now, observations related to COVID-19 have been performed exclusively based on disease-specific items. Therefore, we hypothesize that PHRs would be suitable as a symptom-tracking tool for COVID-19. To this end, we integrated health observation items specific to COVID-19 with an existing PHR-based app. Objective: This study is conducted as a proof-of-concept study in a real-world setting to develop a PHR-based COVID-19 symptom-tracking app and to demonstrate the practical use of health observations for COVID-19 using a smartphone or tablet app integrated with PHRs. Methods: We applied the PHR-based health observation app within an active epidemiological investigation conducted by Wakayama City Public Health Center. At the public health center, a list is made of individuals who have been in close contact with known infected cases (health observers). Email addresses are used by the app when a health observer sends data to the public health center. Each health observer downloads the app and installs it on their smartphone. Self-observed health data are entered daily into the app. These data are then sent via the app by email at a designated time. Localized epidemiological officers can visualize the collected data using a spreadsheet macro and, thus, monitor the health condition of all health observers. Results: We used the app as part of an active epidemiological investigation executed at a public health center. During the investigation, 72 close contacts were discovered. Among them, 57 had adopted the use of the health observation app. Before the introduction of the app, all health observers would have been interviewed by telephone, a slow process that took four epidemiological officers more than 2 hours. After the introduction of the app, a single epidemiological officer can carry out health observations. The app was distributed for free beginning in early March, and by mid-May, it had been used by more than 20,280 users and 400 facilities and organizations across Japan. Currently, health observation of COVID-19 is socially recognized and has become one of the requirements for resuming social activities. Conclusions: Health observation by PHRs for the purpose of improving health management can also be effectively applied as a measure against large-scale infectious diseases. Individual habits of improving awareness of personal health and the use of PHRs for daily health management are powerful armaments against the rapid spread of infectious diseases. Ultimately, similar actions may help to prevent the spread of COVID-19.

  • Hand Holding Human Heart Model In Front Of Chest. Source:; Copyright: Ben Schonewille; URL:; License: Creative Commons Attribution (CC-BY).

    Telemonitoring Versus Usual Care for Elderly Patients With Heart Failure Discharged From the Hospital in the United States: Cost-Effectiveness Analysis


    Background: Telemonitoring-guided interventional management reduces the need for hospitalization and mortality of patients with chronic heart failure (CHF). Objective: This study aimed to analyze the cost-effectiveness of usual care with and without telemonitoring-guided management in patients with CHF discharged from the hospital, from the perspective of US health care providers. Methods: A lifelong Markov model was designed to estimate outcomes of (1) usual care alone for all postdischarge patients with CHF (New York Heart Association [NYHA] class I-IV), (2) usual care and telemonitoring for all postdischarge patients with CHF, (3) usual care for all postdischarge patients with CHF and telemonitoring for patients with NYHA class III to IV, and (4) usual care for all postdischarge patients with CHF plus telemonitoring for patients with NYHA class II to IV. Model inputs were derived from the literature and public data. Sensitivity analyses were conducted to assess the robustness of model. The primary outcomes were total direct medical cost, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratio (ICER). Results: In the base case analysis, universal telemonitoring group gained the highest QALYs (6.2967 QALYs), followed by the telemonitoring for NYHA class II to IV group (6.2960 QALYs), the telemonitoring for NYHA class III to IV group (6.2450 QALYs), and the universal usual care group (6.1530 QALYs). ICERs of the telemonitoring for NYHA class III to IV group (US $35,393 per QALY) and the telemonitoring for NYHA class II to IV group (US $38,261 per QALY) were lower than the ICER of the universal telemonitoring group (US $100,458 per QALY). One-way sensitivity analysis identified five critical parameters: odds ratio of hospitalization for telemonitoring versus usual care, hazard ratio of all-cause mortality for telemonitoring versus usual care, CHF hospitalization cost and monthly outpatient costs for NYHA class I, and CHF hospitalization cost for NYHA class II. In probabilistic sensitivity analysis, probabilities of the universal telemonitoring, telemonitoring for NYHA class II to IV, telemonitoring for NYHA class III to IV, and universal usual care groups to be accepted as cost-effective at US $50,000 per QALY were 2.76%, 76.31%, 18.6%, and 2.33%, respectively. Conclusions: Usual care for all discharged patients with CHF plus telemonitoring-guided management for NYHA class II to IV patients appears to be the preferred cost-effective strategy.

  • Source: Shutterstock; Copyright: Wright Studio; URL:; License: Licensed by the authors.

    Understanding Clinicians’ Adoption of Mobile Health Tools: A Qualitative Review of the Most Used Frameworks


    Background: Although there is a push toward encouraging mobile health (mHealth) adoption to harness its potential, there are many challenges that sometimes go beyond the technology to involve other elements such as social, cultural, and organizational factors. Objective: This review aimed to explore which frameworks are used the most, to understand clinicians’ adoption of mHealth as well as to identify potential shortcomings in these frameworks. Highlighting these gaps and the main factors that were not specifically covered in the most frequently used frameworks will assist future researchers to include all relevant key factors. Methods: This review was an in-depth subanalysis of a larger systematic review that included research papers published between 2008 and 2018 and focused on the social, organizational, and technical factors impacting clinicians’ adoption of mHealth. The initial systematic review included 171 studies, of which 50 studies used a theoretical framework. These 50 studies are the subject of this qualitative review, reflecting further on the frameworks used and how these can help future researchers design studies that investigate the topic of mHealth adoption more robustly. Results: The most commonly used frameworks were different forms of extensions of the Technology Acceptance Model (TAM; 17/50, 34%), the diffusion of innovation theory (DOI; 8/50, 16%), and different forms of extensions of the unified theory of acceptance and use of technology (6/50, 12%). Some studies used a combination of the TAM and DOI frameworks (3/50, 6%), whereas others used the consolidated framework for implementation research (3/50, 6%) and sociotechnical systems (STS) theory (2/50, 4%). The factors cited by more than 20% of the studies were usefulness, output quality, ease of use, technical support, data privacy, self-efficacy, attitude, organizational inner setting, training, leadership engagement, workload, and workflow fit. Most factors could be linked to one framework or another, but there was no single framework that could adequately cover all relevant and specific factors without some expansion. Conclusions: Health care technologies are generally more complex than tools that address individual user needs as they usually support patients with comorbidities who are typically treated by multidisciplinary teams who might even work in different health care organizations. This special nature of how the health care sector operates and its highly regulated nature, the usual budget deficits, and the interdependence between health care organizations necessitate some crucial expansions to existing theoretical frameworks usually used when studying adoption. We propose a shift toward theoretical frameworks that take into account implementation challenges that factor in the complexity of the sociotechnical structure of health care organizations and the interplay between the technical, social, and organizational aspects. Our consolidated framework offers recommendations on which factors to include when investigating clinicians’ adoption of mHealth, taking into account all three aspects.

  • Doctor demonstrating health app with patient. Source: iStockphoto; Copyright: Dragonimages; URL:; License: Licensed by the authors.

    Barriers and Facilitators to the Adoption of Mobile Health Among Health Care Professionals From the United Kingdom: Discrete Choice Experiment


    Background: Despite the increasing availability of mobile health services, clinical engagement remains minimal. Objective: This study aims to identify and weight barriers to and drivers of health app use among health care professionals (HCPs) from the United Kingdom. Methods: A discrete choice experiment was conducted with 222 HCPs using a web-based survey between March 2019 and June 2019. Participants were recruited to take part via social media and asked to choose their preferred option of 2 hypothetical health apps to prescribe to a hypothetical patient or to prescribe neither. Choices were characterized by differing levels of patient age, cost, published evidence bases, whether they had a National Health Service (NHS) stamp of approval, personal familiarity with the technology, and whether they were recommended by a fellow HCP. The results were analyzed using a mixed logit model, with subgroup analyses to account for heterogeneity. Results: We received 230 responses, a total of 96.5% (n=222/230) of respondents understood the survey task and passed the test of rationality. The median age was between 36 and 45 years, and 62.6% (n=139/222) of the health care providers responding to the survey had previously recommended the use of health apps to patients. Health apps were most likely to be prescribed to patients if they had an NHS stamp of approval or if they were recommended by another HCP (both P<.001). Published studies detailing clinical effectiveness were important (P<.001), but it would take five published studies to have the same impact on prescribing behavior as an NHS stamp of approval and two studies to be as convincing as having used the technology personally. Increasing patient age and costs resulted in significant reductions in digital health prescribing (P<.001), none more so than among allied health professionals. Willingness-to-pay for health apps increased by £124.61 (US $151.14) if an NHS stamp of approval was present and by £29.20 (US $35.42) for each published study. Overall, 8.1% (n=18/222) of respondents were reluctant to use health apps, always choosing the I would prescribe neither option, particularly among older HCPs, nurses, and those who do not use health apps personally. Subgroup analyses revealed significant differences in preferences among HCPs of differing ages and clinical backgrounds. Conclusions: An NHS stamp of approval, published studies, and recommendations from fellow HCPs are significant facilitators of digital prescribing, whereas increasing costs and patient age are significant barriers to engagement. These findings suggest that demonstrating assurances of health apps and supporting both the dissemination and peer-to-peer recommendation of evidence-based technologies are critical if the NHS is to achieve its long-term digital transformation ambitions.

  • Source: freepik; Copyright: freepik; URL:; License: Licensed by JMIR.

    Effect of a Health System–Sponsored Mobile App on Perinatal Health Behaviors: Retrospective Cohort Study


    Background: Pregnancy mobile apps are becoming increasingly popular, with parents-to-be seeking information related to their pregnancy and their baby through mobile technology. This increase raises the need for prenatal apps with evidence-based content that is personalized and reliable. Previous studies have looked at whether prenatal apps impact health and behavior outcomes among pregnant and postpartum individuals; however, research has been limited. Objective: The primary objective of this study is to assess whether the use of a health system–sponsored mobile app—Circle by Providence—aimed at providing personalized and reliable health information on pregnancy, postpartum recovery, and infant care is associated with improved health outcomes and increased healthy behaviors and knowledge among users. Methods: This observational study compared app users and app nonusers using a self-reported survey and electronic medical records. The study took place over 18 months and was conducted at Providence St. Joseph Health in Portland, Oregon. The sample included patients who received prenatal care at one of seven Providence clinics and had a live birth at a Providence hospital. Recruitment occurred on a rolling basis and only those who completed the survey were included. Survey respondents were separated into app users and app nonusers, and survey responses and clinical outcomes were compared across groups using univariate and adjusted multivariate logistic regression. Results: A total of 567 participants were enrolled in the study—167 in the app user group and 400 in the nonuser group. We found statistically significant differences between the two groups for certain behavior outcomes: subjects who used the app had 75% greater odds of breastfeeding beyond 6 months postpartum (P=.012), were less likely to miss prenatal appointments (P=.046), and were 50% more likely to exercise 3 or more times a week during pregnancy (P=.04). There were no differences in nutritional measures, including whether they took prenatal vitamins, ate 5 fruits or vegetables a day, or drank caffeine. We found no differences in many of the infant care outcomes; however, there was an increase in awareness of “purple crying.” Finally, there were no significant differences in measured clinical health outcomes, including cesarean births, length of hospital stays (in minutes), low birth weight infants, preterm births, small-for-gestational-age births, large-for-gestational-age births, and neonatal intensive care unit stays. Conclusions: The use of the Circle app, which provides access to personalized and evidence-based health information, was associated with an increase in certain healthy behaviors and health knowledge, although there was no impact on clinical health outcomes. More research is needed to determine the impact of mobile prenatal apps on healthy pregnancies, clinical health outcomes, and infant care.

  • Source: freepik; Copyright: prostooleh; URL:; License: Licensed by JMIR.

    Ecological Momentary Assessment Within a Digital Health Intervention for Reminiscence in Persons With Dementia and Caregivers: User Engagement Study


    Background: User-interaction event logs provide rich and large data sets that can provide valuable insights into how people engage with technology. Approaches such as ecological momentary assessment (EMA) can be used to gather accurate real-time data in an individual’s natural environment by asking questions at any given instant. Objective: The purpose of this study was to evaluate user engagement and responses to EMA questions using InspireD, an app used for reminiscence by persons with dementia and their caregivers. Research findings can be used to inform EMA use within digital health interventions. Methods: A feasibility trial was conducted in which participants (n=56) used the InspireD app over a 12-week period. Participants were a mean age of 73 (SD 13) and were either persons with dementia (n=28) or their caregivers (n=28). Questions, which they could either answer or choose to dismiss, were presented to participants at various instants after reminiscence with personal or generic photos, videos, and music. Presentation and dismissal rates for questions were compared by hour of the day and by trial week to investigate user engagement. Results: Overall engagement was high, with 69.1% of questions answered when presented. Questions that were presented in the evening had the lowest dismissal rate; the dismissal rate for questions presented at 9 PM was significantly lower than the dismissal rate for questions presented at 11 AM (9 PM: 10%; 11 AM: 50%; χ21=21.4, P<.001). Questions asked following reminiscence with personal media, especially those asked after personal photos, were less likely to be answered compared to those asked after other media. In contrast, questions asked after the user had listened to generic media, in particular those asked after generic music, were much more likely to be answered. Conclusions: The main limitation of our study was the lack of generalizability of results to a larger population given the quasi-experimental design and older demographic where half of participants were persons with dementia; however, this study shows that older people are willing to participate and engage in EMA. Based on this study, we propose a series of recommendations for app design to increase user engagement with EMA. These include presenting questions no more than once per day, after 8 PM in the evening, and only if the user is not trying to complete a task within the app.

  • Source: freepik; Copyright: prostooleh; URL:; License: Licensed by JMIR.

    Mobile Phone Technologies in the Management of Ischemic Heart Disease, Heart Failure, and Hypertension: Systematic Review and Meta-Analysis


    Background: Cardiovascular disease (CVD) remains the leading cause of death worldwide. Mobile phones have become ubiquitous in most developed societies. Smartphone apps, telemonitoring, and clinician-driven SMS allow for novel opportunities and methods in managing chronic CVD, such as ischemic heart disease, heart failure, and hypertension, and in the conduct and support of cardiac rehabilitation. Objective: A systematic review was conducted using seven electronic databases, identifying all relevant randomized control trials (RCTs) featuring a mobile phone intervention (MPI) used in the management of chronic CVD. Outcomes assessed included mortality, hospitalizations, blood pressure (BP), and BMI. Methods: Electronic data searches were performed using seven databases from January 2000 to June 2019. Relevant articles were reviewed and analyzed. Meta-analysis was performed using standard techniques. The odds ratio (OR) was used as a summary statistic for dichotomous variables. A random effect model was used. Results: A total of 26 RCTs including 6713 patients were identified and are described in this review, and 12 RCTs were included in the meta-analysis. In patients with heart failure, MPIs were associated with a significantly lower rate of hospitalizations (244/792, 30.8% vs 287/803, 35.7%; n=1595; OR 0.77, 95% CI 0.62 to 0.97; P=.03; I2=0%). In patients with hypertension, patients exposed to MPIs had a significantly lower systolic BP (mean difference 4.3 mm Hg; 95% CI −7.8 to −0.78 mm Hg; n=2023; P=.02). Conclusions: The available data suggest that MPIs may have a role as a valuable adjunct in the management of chronic CVD.

  • Untitled. Source: Freepik; Copyright: tirachardz; URL:; License: Licensed by JMIR.

    Application and Preliminary Outcomes of Remote Diagnosis and Treatment During the COVID-19 Outbreak: Retrospective Cohort Study


    Background: The coronavirus disease (COVID-19) pandemic, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in the self-quarantine of countless people due to possible infection. This situation makes telemedicine necessary as it can overcome geographical barriers, increase the number of people served, and provide online clinical support for patients. However, the outcomes of telemedicine have not yet been evaluated. Objective: The aim of our study is to describe the epidemiological features and clinical symptoms of patients receiving remote diagnosis and treatment at the online outpatient clinic of our hospital, as well as to analyze the outcomes and advantages of telemedicine, during the COVID-19 pandemic. Methods: Data from patients receiving remote diagnosis and treatment via consultation services for COVID-19 concerns at the online outpatient clinic of Henan Provincial People's Hospital from January 24 to February 17, 2020, were collected. A retrospective analysis was performed on epidemiological features, clinical symptoms, and preliminary outcomes. Results: Online inquiry, consultation, and suggestions were provided for patient concerns related to COVID-19. Our hospital also offered offline noncontact drug delivery services following online ordering and payment. A total of 4589 patients receiving remote diagnosis and treatment were recruited. The daily number of online outpatient visits initially increased and then decreased, reaching its peak on January 28 when the daily number of online outpatient visits totaled 612. Of 4589 patients, 1940 (42.3%) were males and 2649 (57.7%) were females (age range: 78 days to 85 years). Most patients were aged 20-39 years (n=3714, 80.9%) and came from Henan Province (n=3898, 84.9%). The number of patients from other provinces was 691 (15.1%). During the online consultations, patients discussed the following symptoms: fever (n=2383), cough (n=1740), nasal obstruction (n=794), fatigue (n=503), and diarrhea (n=276). A total of 873 orders of noncontact drug delivery following online payment was completed. The daily number of such orders gradually stabilized after the initial, steady increase. For offline drug delivery orders, the median (IQR) was 36 (58). An online satisfaction survey was filled out postconsultation by patients; of the 985 responses received, 98.1% (n=966) of respondents were satisfied with the service they received. Conclusions: Remote diagnosis and treatment offered via online outpatient consultations effectively reduced the burden on hospitals, prevented overcrowding, reduced the risk of cross-infection, and relieved patients' anxiety during the COVID-19 outbreak. This plays an essential role in pandemic management.

  • Source: Image created by the Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution (CC-BY).

    Effects of a 12-Week Multifaceted Wearable-Based Program for People With Knee Osteoarthritis: Randomized Controlled Trial


    Background: Current guidelines emphasize an active lifestyle in the management of knee osteoarthritis (OA), but up to 90% of patients with OA are inactive. In a previous study, we demonstrated that an 8-week physiotherapist (PT)-led counseling intervention, with the use of a Fitbit, improved step count and quality of life in patients with knee OA, compared with a control. Objective: This study aimed to examine the effect of a 12-week, multifaceted wearable-based program on physical activity and patient outcomes in patients with knee OA. Methods: This was a randomized controlled trial with a delay-control design. The immediate group (IG) received group education, a Fitbit, access to FitViz (a Fitbit-compatible app), and 4 biweekly phone calls from a PT over 8 weeks. Participants then continued using Fitbit and FitViz independently up to week 12. The delay group (DG) received a monthly electronic newsletter in weeks 1 to 12 and started the same intervention in week 14. Participants were assessed in weeks 13, 26, and 39. The primary outcome was time spent in daily moderate-to-vigorous physical activity (MVPA; in bouts ≥10 min) measured with a SenseWear Mini. Secondary outcomes included daily steps, time spent in purposeful activity and sedentary behavior, Knee Injury and OA Outcome Score, Patient Health Questionnaire-9, Partners in Health Scale, Theory of Planned Behavior Questionnaire, and Self-Reported Habit Index. Results: We enrolled 51 participants (IG: n=26 and DG: n=25). Compared with the IG, the DG accumulated significantly more MVPA time at baseline. The adjusted mean difference in MVPA was 13.1 min per day (95% CI 1.6 to 24.5). A significant effect was also found in the adjusted mean difference in perceived sitting habit at work (0.7; 95% CI 0.2 to 1.2) and during leisure activities (0.7; 95% CI 0.2 to 1.2). No significant effect was found in the remaining secondary outcomes. Conclusions: A 12-week multifaceted program with the use of a wearable device, an app, and PT counseling improved physical activity in people with knee OA. Trial Registration: NCT02585323;

  • Source: Image created by the Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution + Noncommercial + NoDerivatives (CC-BY-NC-ND).

    Maintaining Physical Activity Level Through Team-Based Walking With a Mobile Health Intervention: Cross-Sectional Observational Study


    Background: The health conditions of Japanese salespersons may be adversely affected by their lifestyle. Face-to-face or on-site health interventions are not convenient for salespersons because of their tendency for out-of-office sales. Previous studies showed that mobile health (mHealth) interventions (compared to usual practice) have great potential to promote physical activity. For Japanese salespersons, mHealth can offer additional convenience to change their physical activity habits because they can access the mHealth contents anytime and anywhere. However, the specific elements that are most important to maintain physical activity levels using an mHealth approach remain unclear. Objective: We aimed to identify elements that account for both a high average physical activity level and can help to prevent a decrease in physical activity during a 9-week intervention period. Methods: Salespersons were recruited from 11 Japanese companies. A team-based walking intervention was held from October to December 2018 (for a total of 9 weeks), during which the walking step data were recorded by smartphone apps. Average walking steps of each participant during the intervention and the difference in walking steps between the initial and the final week were respectively used as dependent variables. The effects of team characteristics (ie, frequency of communication with team members and team size) and behavioral characteristics (ie, number of days with recorded steps on the apps) on the average walking steps, and the difference in walking steps between the initial and the final week were estimated using multiple and multilevel regression analyses. Results: Of the 416 participants, walking step data of 203 participants who completed postintervention assessments were included in the analyses. Multiple regression analysis of the average walking steps showed that the number of days with recorded steps was positively correlated with the log-transformed average walking steps (β=.01, P<.001). Multilevel analysis of the average walking steps considering the company level estimated that the intraclass correlation coefficient was 37%. This means that belonging to the same company largely affected an individual’s average walking steps. Multiple regression analysis of the difference in walking steps showed that communication with team members once or twice a week correlated with preventing a decrease in walking steps from the initial to the final week (β=1539.4, P=.03), and being on a larger team correlated with a decrease in walking steps from the initial to the final week (β=–328.4, P=.01). Conclusions: This study showed that the elements accounting for high average walking steps and those preventing the decrease in walking steps from the initial to the final week differed. Behavioral characteristics correlated positively with average walking steps. Team characteristics (ie, regular communication and a smaller team size) significantly correlated with preventing a decrease in walking steps.

  • Source: Piqsels; Copyright: Piqsels; URL:; License: Licensed by JMIR.

    Privacy Assessment in Mobile Health Apps: Scoping Review


    Background: Privacy has always been a concern, especially in the health domain. The proliferation of mobile health (mHealth) apps has led to a large amount of sensitive data being generated. Some authors have performed privacy assessments of mHealth apps. They have evaluated diverse privacy components; however, different authors have used different criteria for their assessments. Objective: This scoping review aims to understand how privacy is assessed for mHealth apps, focusing on the components, scales, criteria, and scoring methods used. A simple taxonomy to categorize the privacy assessments of mHealth apps based on component evaluation is also proposed. Methods: We followed the methodology defined by Arksey and O’Malley to conduct a scoping review. Included studies were categorized based on the privacy component, which was assessed using the proposed taxonomy. Results: The database searches retrieved a total of 710 citations—24 of them met the defined selection criteria, and data were extracted from them. Even though the inclusion criteria considered articles published since 2009, all the studies that were ultimately included were published from 2014 onward. Although 12 papers out of 24 (50%) analyzed only privacy, 8 (33%) analyzed both privacy and security. Moreover, 4 papers (17%) analyzed full apps, with privacy being just part of the assessment. The evaluation criteria used by authors were heterogeneous and were based on their experience, the literature, and/or existing legal frameworks. Regarding the set of items used for the assessments, each article defined a different one. Items included app permissions, analysis of the destination, analysis of the content of communications, study of the privacy policy, use of remote storage, and existence of a password to access the app, among many others. Most of the included studies provided a scoring method that enables the comparison of privacy among apps. Conclusions: The privacy assessment of mHealth apps is a complex task, as the criteria used by different authors for their evaluations are very heterogeneous. Although some studies about privacy assessment have been conducted, a very large set of items to evaluate privacy has been used up until now. In-app information and privacy policies are primarily utilized by the scientific community to extract privacy information from mHealth apps. The creation of a scale based on more objective criteria is a desirable step forward for privacy assessment in the future.

  • Source: Freepik; Copyright: tirachardz; URL:; License: Licensed by JMIR.

    A Web-Based Mobile App (INTERACCT App) for Adolescents Undergoing Cancer and Hematopoietic Stem Cell Transplantation Aftercare to Improve the Quality of...


    Background: A growing number of cancer and hematopoietic stem cell transplant (HSCT) survivors require long-term follow-up with optimal communication schemes, and patients' compliance is crucial. Adolescents have various unmet needs. Regarding self-report of symptoms and health status, users of mobile apps showed enhanced compliance. Currently, HSCT aftercare at the HSCT outpatient clinic of the St. Anna Children’s Hospital in Vienna, Austria, is based on handwritten diaries, carrying various disadvantages. Recently, we developed the prototype of a web-based, self-monitoring gamified mobile app tailored for adolescents: the INTERACCT (Integrating Entertainment and Reaction Assessment into Child Cancer Therapy) app. Objective: This observational, prospective study evaluated the usability of the INTERACCT app for tracking real-time self-reported symptoms and health status data in adolescent HSCT patients and a healthy matched control group. The primary outcome of the study was the quality of the self-reported medical information. We hypothesized that the mobile app would provide superior medical information for the clinicians than would the handwritten diaries. Methods: Health data were reported via paper diary and mobile app for 5 consecutive days each. The quality of medical information was rated on a 5-point scale independently and blinded by two HSCT clinicians, and the duration of use was evaluated. A total of 52 participant questionnaires were assessed for gaming patterns and device preferences, self-efficacy, users’ satisfaction, acceptability, and suggestions for improvement of the mobile app. Interrater reliability was calculated with the intraclass correlation coefficient, based on a two-way mixed model; one-way repeated-measures analysis of variance and t tests were conducted post hoc. Descriptive methods were used for correlation with participants’ demographics. For users’ satisfaction and acceptability of the mobile app, the median and the IQR were calculated. Results: Data from 42 participants—15 patients and 27 healthy students—with comparable demographics were evaluated. The results of our study indicated a superiority of the quality of self-reported medical data in the INTERACCT app over traditional paper-and-pencil assessment (mobile app: 4.14 points, vs paper-based diary: 3.77 points, P=.02). The mobile app outperformed paper-and-pencil assessments mainly among the patients, in particular among patients with treatment-associated complications (mobile app: 4.43 points, vs paper-based diary: 3.73 points, P=.01). The mobile app was used significantly longer by adolescents (≥14 years: 4.57 days, vs ≤13 years: 3.14 days, P=.03) and females (4.76 days for females vs 2.95 days for males, P=.004). This corresponds with a longer duration of use among impaired patients with comorbidities. User satisfaction and acceptability ratings for the mobile app were high across all groups, but adherence to entering a large amount of data decreased over time. Based on our results, we developed a case vignette of the target group. Conclusions: Our study was the first to show that the quality of patient-reported medical information submitted via the INTERACCT app embedded in a serious game is superior to that submitted via a handwritten diary. In light of these results, a refinement of the mobile app supported by a machine learning approach is planned within an international research project.

Citing this Article

Right click to copy or hit: ctrl+c (cmd+c on mac)

Latest Submissions Open for Peer-Review:

View All Open Peer Review Articles
  • An eHealth platform for monitoring ketogenic diet therapies in patients with refractory epilepsy

    Date Submitted: Jun 30, 2020

    Open Peer Review Period: Jun 30, 2020 - Aug 25, 2020

    Ketogenic diet therapies (KDTs) are high-fat, low-carbohydrate, and moderate-protein interventions that have been used over the years to control seizures in patients with treatment-refractory epilepsy...

    Ketogenic diet therapies (KDTs) are high-fat, low-carbohydrate, and moderate-protein interventions that have been used over the years to control seizures in patients with treatment-refractory epilepsy and certain inborn errors of metabolism. The mechanism of action of KDTs is thought to be related to molecular changes that are the result of increased systemic ketone-body concentration and decreased glucose levels leading to a reduction in seizure frequency. Therefore, systemic ketone bodies and glucose levels are measured daily in these patients. “My Keto Life” was developed as a dynamic and easy to use web- and App-based monitoring and support tool for epilepsy patients on KDTs. Using this eHealth tool patients are able to regularly record self-measured values, such as ketone bodies, glucose levels, and seizures, to monitor adherence and allow real-time intervention by physicians and nutritionists. Based on non-structured interviews with experts in metabolism, epileptologists, and nutritionists from the KDT team at Hospital Garrahan, Buenos Aires, Argentina, a suitable digital platform was designed and developed to improve care of epilepsy patients on KDTs. Daily self-tracking of ketone bodies and glucose levels, the dynamic recording of food intake, supplements, and antiseizure medications by users, real-time monitoring by and communication with physicians and nutritionists, and personalized reminders for taking anti seizure medications, supplements, and ketone measures are the most prominent features of this tool. “My Keto Life” is a rapid and iterative eHealth tool developed together with physicians and nutritionists for the adequate management of epilepsy patients on KDTs in order to promote patient engagement, facilitate monitoring by physicians, and optimize treatment leading to better therapeutic outcomes.

  • Digital Technology Interventions for Risk Factor Modification in Patients with Cardiovascular Disease: a Systematic Literature Review and Meta-Analysis

    Date Submitted: Jun 5, 2020

    Open Peer Review Period: Jun 4, 2020 - Jul 30, 2020

    Background: Cardiovascular diseases (CVDs) remain one of the commonest causes of early death and disability worldwide with 17.9 million deaths and 422.7 million cases annually. There are approximately...

    Background: Cardiovascular diseases (CVDs) remain one of the commonest causes of early death and disability worldwide with 17.9 million deaths and 422.7 million cases annually. There are approximately 1.7 million inpatient episodes in the UK per year. Approximately 50% of CVD is attributable to lifestyle risk factors. Despite widespread education, personal knowledge and efficacy, many individuals fail to adequately modify these risk factors, even after a cardiovascular event. Digital technologies have been suggested as a viable equivalent and potential alternative to conventional cardiac rehabilitation centre care. However, little is known about the clinical effectiveness of these technologies in bringing about behaviour change in CVD patients at individual level. Objective: This systematic review seeks to 1) identify digital technologies and measure effectiveness of their interventions that have been tested in randomized control trials (RCTs) and 2) summarize their behavioural change and clinical outcome applications, and demographic qualities; for risk factor modification among CVD patients. Methods: Mixed data from studies, extracted from selected research databases and filtered to RCTs only, were analysed using qualitative and quantitative methods. Results: The use of digital technologies in cardiac patients was associated with improvements in total cholesterol, high density lipoprotein, low density lipoprotein, physical activity, physical inactivity (sedentary), healthy diet and medication adherence (at P≤0.05). However, there were no differences seen in body mass index, triglycerides, blood pressures (diastolic and systolic), blood sugar, alcohol intake and smoking (at P=0.05). Conclusions: This systematic review concludes that digital technology interventions may have benefit in improving protective behavioural factors (physical activity, healthy diet and medication adherence) and more potent when engaged in multiple behavioural outcome treatment (e.g. medication adherence plus…), but did not appear to reduce risky behavioural factors (smoking, alcohol intake and unhealthy diet) and clinical outcomes (body mass index, diastolic blood pressure, systolic blood pressure and blood sugar, HbA1c).

  • Sleep Validation of Commercially Available Smart Ring and Watch Against Medical-Grade Actigraphy in Everyday Settings

    Date Submitted: May 19, 2020

    Open Peer Review Period: May 19, 2020 - Jul 14, 2020

    Background: Assessment of sleep quality is essential to address poor sleep quality and understand the changes. Thanks to the advances in Internet-of-Things and wearable technologies, sleep monitoring...

    Background: Assessment of sleep quality is essential to address poor sleep quality and understand the changes. Thanks to the advances in Internet-of-Things and wearable technologies, sleep monitoring in free-living conditions has become feasible and practicable. Smart rings and smartwatches can be employed to perform mid- or long-term home-based sleep monitoring. However, the validity of such wearables should be investigated in terms of sleep parameters. Sleep validation studies are mostly limited to short-term laboratory tests. There is a need for a study to assess the sleep attributes of wearables in everyday settings, where the users engage in their daily routines. Objective: We evaluate the sleep parameters of Oura ring along with Samsung Gear Sport watch in comparison to a medically-approved actigraphy device in a mid-term everyday setting, where the users engage in their daily routines. Methods: We conduct home-based sleep monitoring in which the sleep parameters of forty-five healthy individuals (23 females and 22 males) are tracked for seven days. The total sleep time (TST), sleep efficiency (SE), and wake after sleep onset (WASO) of the ring and watch are assessed using the paired t-tests, Bland-Altman plots, and Pearson correlation. The parameters are also investigated, considering the gender of the participants as a dependent variable. Results: Our findings show that there are significant correlations between the TST (r=0.86,P<0.001), WASO (r=0.41,P<0.001), and SE (r=0.47,P<0.001) of the ring and actigraphy. In comparison of the watch with actigraphy, there is a significant correlation in TST (r=0.59, P<0.001). The mean differences of the TST, WASO, and SE of the ring and actigraphy are in the satisfactory ranges, although there are significant differences between the parameters (P<0.001). For the watch, the TST and SE mean differences are also in the satisfactory ranges, and the WASO is slightly higher than the range (31.27±35.15). However, the mean differences of the parameters between the watch and actigraphy are considerably higher than the ring. The watch also shows a significant difference between female and male groups in TST (P<0.001). Conclusions: Consequently, in a population sample of healthy adults, the sleep parameters of both Oura ring and Samsung watch have acceptable mean differences and indicate significant correlations with the actigraphy, but the ring outperforms the watch in terms of the non-staging sleep parameters.