Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Monday, December 24 through Wednesday, December 26 inclusive. 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) 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:

  • Source: Freepik; Copyright: Katemangostar; URL:; 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


    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:; License: Creative Commons Attribution (CC-BY).

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


    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:; URL:; License: Licensed by the authors.

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


    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:; License: Creative Commons Attribution (CC-BY).

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


    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;

  • Source: Pixabay; Copyright: Fotorech; URL:; License: Public Domain (CC0).

    User Models for Personalized Physical Activity Interventions: Scoping Review


    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:; 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:...


    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:; License: Creative Commons Attribution (CC-BY).

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


    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:; License: Creative Commons Attribution (CC-BY).

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


    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:; 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


    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.

  • Source: iStock by Getty Images; Copyright: Prykhodov; URL:; License: Licensed by the authors.

    Mobile Phone Ownership, Health Apps, and Tablet Use in US Adults With a Self-Reported History of Hypertension: Cross-Sectional Study


    Background: Mobile phone and tablet ownership have increased in the United States over the last decade, contributing to the growing use of mobile health (mHealth) interventions to help patients manage chronic health conditions like diabetes. However, few studies have characterized mobile device ownership and the presence of health-related apps on mobile devices in people with a self-reported history of hypertension. Objective: This study aimed to describe the prevalence of smartphone, tablet, and basic mobile phone ownership and the presence of health apps by sociodemographic factors and self-reported hypertension status (ie, history) in a nationally representative sample of US adults, and to describe whether mobile devices are associated with health goal achievement, medical decision making, and patient-provider communication. Methods: Data from 3285 respondents from the 2017 Health Information National Trends Survey were analyzed. Participants were asked if they owned a smartphone, tablet, or basic mobile phone and if they had health apps on a smartphone or tablet. Participants were also asked if their smartphones or tablets helped them achieve a health-related goal like losing weight, make a decision about how to treat an illness, or talk with their health care providers. Chi-square analyses were conducted to test for differences in mobile device ownership, health app presence, and app helpfulness by patient characteristics. Results: Approximately 1460 (37.6% weighted prevalence) participants reported a history of hypertension. Tablet and smartphone ownership were lower in participants with a history of hypertension than in those without a history of hypertension (55% vs 66%, P=.001, and 86% vs 68%, P<.001, respectively). Participants with a history of hypertension were more likely to own a basic mobile phone only as compared to those without a history of hypertension (16% vs 9%, P<.001). Among those with a history of hypertension exclusively, basic mobile phone, smartphone, and tablet ownership were associated with age and education, but not race or sex. Older adults were more likely to report having a basic mobile phone only, whereas those with higher education were more likely to report owning a tablet or smartphone. Compared to those without a history of hypertension, participants with a history of hypertension were less likely to have health-related apps on their smartphones or tablets (45% vs 30%, P<.001) and report that mobile devices helped them achieve a health-related goal (72% vs 63%, P=.01). Conclusions: Despite the increasing use of smartphones, tablets, and health-related apps, these tools are used less among people with a self-reported history of hypertension. To reach the widest cross-section of patients, a mix of novel mHealth interventions and traditional health communication strategies (eg, print, web based, and in person) are needed to support the diverse needs of people with a history of hypertension.

  • Source: Shutterstock; Copyright: Dragon Images; URL:; License: Licensed by the authors.

    Mobile App for Improved Self-Management of Type 2 Diabetes: Multicenter Pragmatic Randomized Controlled Trial


    Background: As the increasing prevalence of type 2 diabetes mellitus has put pressure on health systems to appropriately manage these patients, there have been a growing number of mobile apps designed to improve the self-management of diabetes. One such app, BlueStar, has been shown to significantly reduce hemoglobin A1c (HbA1c) levels in small studies and is the first app in the United States to receive Food and Drug Administration approval as a mobile prescription therapy. However, the impact of the app across real-world population among different clinical sites and health systems remains unclear. Objective: The primary objective of this study was to conduct a pragmatic randomized controlled trial of the BlueStar mobile app to determine if app usage leads to improved HbA1c levels among diverse participants in real-life clinical contexts. We hypothesized that this mobile app would improve self-management and HbA1c levels compared with controls. Methods: The study consisted of a multicenter pragmatic randomized controlled trial. Overall, 110 participants randomized to the immediate treatment group (ITG) received the intervention for 6 months, and 113 participants randomized to the wait-list control (WLC) group received usual care for the first 3 months and then received the intervention for 3 months. The primary outcome was glucose control measured by HbA1c levels at 3 months. Secondary outcomes assessed intervention impact on patient self-management, experience of care, and self-reported health utilization using validated scales, including the Problem Areas in Diabetes, the Summary of Diabetes Self-Care Activities, and the EuroQol-5D. Intervention usage data were collected directly from the app. Results: The results of an analysis of covariance controlling for baseline HbA1c levels did not show evidence of intervention impact on HbA1c levels at 3 months (mean difference [ITG−WLC] −0.42, 95% CI −1.05 to 0.21; P=.19). Similarly, there was no intervention effect on secondary outcomes measuring diabetes self-efficacy, quality of life, and health care utilization behaviors. An exploratory analysis of 57 ITG participants investigating the impact of app usage on HbA1c levels showed that each additional day of app use corresponded with a 0.016-point decrease in participants’ 3-month HbA1c levels (95% CI −0.03 to −0.003). App usage varied significantly by site, as participants from 1 site logged in to the app a median of 36 days over 14 weeks (interquartile range [IQR] 10.5-124); those at another site used the app significantly less (median 9; IQR 6-51). Conclusions: The results showed no difference between intervention and control arms for the primary clinical outcome of glycemic control measured by HbA1c levels. Although there was low usage of the app among participants, results indicate contextual factors, particularly site, had a significant impact on overall usage. Future research into the patient and site-specific factors that increase app utilization are needed. Trial Registration: NCT02813343; (Archived by WebCite at

  • Graphical user interface of the SymptomMapper app that was used in our study. Its drawing module allows for quick and easy data entry without previous training, a crucial prerequisite when studying patients in acute pain situations. Sides are emphasized by the words left (“links”) and right (“rechts”). Doctors and patients used the same app for their pain drawings. Source: Figure 1 from; Copyright: the authors; License: Creative Commons Attribution (CC-BY).

    Digital Pain Drawings Can Improve Doctors’ Understanding of Acute Pain Patients: Survey and Pain Drawing Analysis


    Background: Pain drawings (PDs) are an important tool to evaluate, communicate, and objectify pain. In the past few years, there has been a shift toward tablet-based acquisition of PDs, and several studies have been conducted to test the usefulness, reliability, and repeatability of electronic PDs. However, to our knowledge, no study has investigated the potential role of electronic PDs in the clinical assessment and treatment of inpatients in acute pain situations. Objective: The aim of this study was to evaluate whether knowledge of the patients’ electronic PD has the potential to improve the doctors’ understanding of their patients and to influence their clinical decision making. Furthermore, we sought to identify differences between electronic PDs of patients and their treating pain specialists in an acute pain situation and to find those specific characteristics derived from the PDs that had the largest impact on doctors’ understanding. Methods: We obtained electronic PDs from 47 inpatients in acute pain situations before their consultation with a pain specialist on a tablet personal computer with a stylus. Before looking at their patients’ drawings, these specialists drew their own conception of the patients’ pain after anamnesis and physical examination. Patients’ drawings were then revealed to the doctors, and they were asked to evaluate how much the additional information improved their understanding of the case and how much it influenced their clinical decision on an 11-point Likert scale (0=“not at all” and 10=“very much”). Similarities and differences of patients’ and doctors’ PDs were assessed by visual inspection and by calculating Jaccard index and intraclass correlation coefficient (ICC) of the pain area and the number of pain clusters. Exploratory analyses were conducted by means of correlation tables to identify specific factors that influenced doctors’ understanding. Results: Patients’ PDs significantly improved the doctors’ understanding (mean score 4.81, SD 2.60, P<.001) and to a lesser extent their clinical decision (mean 2.68, SD 1.18, P<.001). Electronic PDs of patients and doctors showed fair to good similarity for pain extent (r=.454, P=.001) and widespreadness (P=.447, r=.002) were important factors helping doctors to understand their patients. Conclusions: In a clinical setting, electronic PDs can improve doctors’ understanding of patients in acute pain situations. The ability of electronic PDs to visualize differences between doctors’ and patients’ conception of pain has the potential to improve doctor-patient communication.

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
  • With a little help from my walking app? Predictors of profile classifications of current users, previous users, and informed nonusers in a sample of Dutch adults

    Date Submitted: Jan 14, 2019

    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: 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.