JMIR mHealth and uHealth
Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.
JMIR mhealth and uhealth (mobile and ubiquitous health) (JMU, ISSN 2291-5222) is a spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2015: 4.532). JMIR mHealth and uHealth has a projected impact factor (2015) of about 2.03. 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.
Jan 12, 2017
Dec 22, 2016
Dec 19, 2016
Dec 19, 2016
Dec 15, 2016
Dec 8, 2016
Dec 8, 2016
Dec 2, 2016
Nov 23, 2016
Nov 16, 2016
Nov 15, 2016
Nov 10, 2016
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
Semantic location from mobile phones: Going beyond GPS
Date Submitted: Jan 10, 2017
Open Peer Review Period: Jan 16, 2017 - Mar 13, 2017
Background: Is someone at home, at their friend’s place, at a restaurant, or enjoying the great outdoors? Knowing the semantic location matters for delivering medical interventions, recommendations,...
Background: Is someone at home, at their friend’s place, at a restaurant, or enjoying the great outdoors? Knowing the semantic location matters for delivering medical interventions, recommendations, and other context-aware services. This knowledge is particularly useful in mental healthcare for monitoring the behavioral indicators of mood states and improving treatment delivery. Local search-and-discovery services such as Foursquare can be used to detect semantic locations based on GPS coordinates, but GPS alone is often inaccurate. Smartphones can also sense other signals, such as movement, light, and sound, and using these signals promises to lead to a better estimation of the semantic location. Objective: To examine the ability of smartphone sensors in estimating semantic locations, and to evaluate the relationship between semantic location visit patterns and mental health. Methods: 208 participants across the United States were asked to log the type of locations they visited daily, including home and work, for a period of 6 weeks, while their phone sensor data was recorded. Based on the sensor data and Foursquare queries, we trained models to predict these logged locations, and evaluated their prediction accuracy on participants not seen by the model. We also evaluated the relationship between the amount of time spent in each semantic location and depression and anxiety, assessed at the baseline, in the middle, and at the end of the study. Results: While Foursquare queries detected the true semantic locations with an average area under the curve (AUC) of 0.60, using phone sensor data increased the AUC to 0.72. When we used Foursquare and sensor data together, the AUC further increased to 0.78. We found a few significant relationships between the time spent in certain locations and depression and anxiety, although these relationships were not consistent. Conclusions: The accuracy of location services such as Foursquare can significantly benefit from using phone sensor data besides their location databases. Our results suggest that the nature of the places we go to explains only a small part of the variance of anxiety and depression.
Use of and beliefs about smartphone applications for diabetes self-management: surveys of people in a hospital diabetes clinic and diabetes health professionals in New Zealand
Date Submitted: Jan 4, 2017
Open Peer Review Period: Jan 10, 2017 - Mar 7, 2017
Background: People with diabetes mellitus (DM) are using smartphone applications (‘apps’) to support self-management. The numerous apps available to assist with diabetes management have a variety...
Background: People with diabetes mellitus (DM) are using smartphone applications (‘apps’) to support self-management. The numerous apps available to assist with diabetes management have a variety of functions. Some functions, like insulin dose calculators, have significant potential for harm. Objective: 1. To establish if people with DM in Wellington, New Zealand, use apps for DM self-management and evaluate desirable features of apps. 2. To establish if health professionals (HPs) in New Zealand treating people with DM recommend apps to patients, the features HPs regard as important and confidence with recommending apps. Methods: A survey of patients seen at a hospital diabetes clinic over twelve months (n= 539) assessing current app use and desirable features. A second survey of HPs attending a diabetes conference (n=286) assessed confidence with app recommendations and perceived usefulness. Results: 19.6% (n=37) of the 189 responders (35.0% response rate) to the patient survey had used a diabetes app. App users were younger and more had Type 1 DM. App users most favoured feature was a glucose diary (86.5%, n=32/37), and an insulin calculator was the most desirable function for a future app (45.9%, n=17/37). In non-app users, the most desirable feature for a future app was a glucose diary (64.5%, n=98/152). Of the 115 responders (40.2% response rate) to the HPs survey 60.2% had recommended a diabetes app. Diaries for blood glucose levels and carbohydrate counting were considered the most useful app features and the features HPs felt most confident to recommend. HPs were least confident in recommending insulin calculation apps. Conclusions: The use of apps to record blood glucose was the most favoured function in apps used by people with diabetes, with interest in insulin dose calculating function. HPs do not feel confident in recommending insulin dose calculators. There is an urgent need for an app assessment process to give confidence in the quality and safety of diabetes management apps to people with diabetes (potential app users) and HPs (potential app prescribers).
Mobile phone interventions for sleep disorders: A Systematic review and meta-analysis
Date Submitted: Dec 31, 2016
Open Peer Review Period: Jan 3, 2017 - Feb 28, 2017
Background: Although mobile health technologies have been developed for interventions to improve sleep disorders, evidence of their effectiveness remains limited. Objective: A systematic literature re...
Background: Although mobile health technologies have been developed for interventions to improve sleep disorders, evidence of their effectiveness remains limited. Objective: A systematic literature review and subsequent meta-analysis were performed to: 1) examine current research trends in mobile technologies, and 2) determine the effectiveness of mobile technology interventions for improving sleep disorders. Methods: Four electronic databases (CINAHL, PubMed/ Medline, Scopus (EBSCO), and Web of Science) were searched for articles on mobile technology and sleep disorders published between January 2001 and December 2015. Studies were eligible for inclusion if they met the following criteria: adequate details on study design, focus on sleep intervention research, sleep index measurement outcome provided, and publication in peer-reviewed journals. A meta-analysis was conducted to examine the combined effect size and differences on the impact of mobile phone compared to traditional interventions on sleep disorders. Results: Nine eligible studies were evaluated to examine the impact of mobile phone interventions on sleep disorders. These included one case study, two pre/posttest studies, and six randomized control trials (RCTs). The studies were categorized as mobile ‘phone and traditional intervention’ or ‘smartphone application (apps) intervention’. All nine studies concluded that mobile phone interventions have the capability to attenuate sleep disorders. From the subgroup meta-analysis based on various sleep measurement tools, (i.e. PSQI (n=414); ISI, DBAS, SOL and WASO (n=445)), mobile phone interventions positively influence sleep quality, quantity, and sleep disorders. Conclusions: We found evidence to support the use of mobile phone interventions to address sleep disorders. Our findings suggest that mobile phone technologies can be effective for future sleep intervention research.
How do apps work?: An analysis of app users’ perceptions of behavior change mechanisms
Date Submitted: Dec 21, 2016
Open Peer Review Period: Dec 28, 2016 - Feb 22, 2017
Background: Physical activity apps are commonly used to increase levels of activity and health status. The focus of research to date has been to determine the potential of apps to influence behavior,...
Background: Physical activity apps are commonly used to increase levels of activity and health status. The focus of research to date has been to determine the potential of apps to influence behavior, to determine the efficacy of a limited number of apps to change behavior, and to identify characteristics of apps that users prefer. Objective: The purpose of this study was to identify the mechanisms by which apps may influence users’ behavior. Methods: This study used a cross-sectional survey of users of health apps during the past 6 months. An electronic survey was created in Qualtrics and deployed on Amazon Mechanical Turk. Individuals that had used a physical activity app in the past 6 months were eligible to respond. The final sample consisted of 207 adults living in the US. Behavior change theory informed the creation of 20 items relating to mechanisms of behavior change. Respondents also reported about engagement with the app(s) and their actual physical activity behavior. Results: Respondents reported that using a physical activity app in the past 6 months resulted in a change in their attitudes, beliefs, perceptions and motivation. Engagement with the app (P < .001), frequency of app use (P = .03), and app price (P = .01) were related to reported impact of the behavior change theory or mechanisms of change. The mechanisms of change were associated with significant changes in physical activity behaviors (P < .001). Conclusions: The findings from this study provide an overview of the mechanisms by which apps may impact changes in behavior. App developers may wish to incorporate these mechanisms in an effort to increase impact. Practitioners should consider the extent to which behavior change theory is integrated into a particular app when they consider recommendations to others wishing to increase levels of physical activity.
mHealth for Clinical Decision-making Support in sub-Saharan Africa: A Scoping Review
Date Submitted: Dec 17, 2016
Open Peer Review Period: Dec 21, 2016 - Feb 15, 2017
Background: In a bid to deliver quality health services in resource-poor settings, mobile technology is increasingly adopted (mHealth). The role of mHealth in facilitating evidence-based clinical deci...
Background: In a bid to deliver quality health services in resource-poor settings, mobile technology is increasingly adopted (mHealth). The role of mHealth in facilitating evidence-based clinical decision-making through data collection, decision algorithms and evidence-based guidelines for example, is established in resource-rich settings. However, the extent to which mobile clinical decision support systems (mCDSS) have been adopted specifically in resource-poor settings such as Africa, and lessons learned about their use in such settings, is yet to be established. Objective: The aim of this study was to synthesize evidence on the use of mHealth for point-of-care decision support and improved quality of care by health care workers in Africa. Methods: A scoping review of four peer-reviewed and one grey literature databases was conducted. No date limits were applied, but only articles in English language were selected. Using pre-established criteria, two reviewers screened articles and extracted data. Articles were analysed using Excel and MAXQDA. Results: Twenty-two articles representing eleven different studies in seven sub-Saharan African countries were retained. Interventions were mainly in the domain of maternal health and ranged from simple text messaging to complex multi-component interventions. Although health workers are generally supportive of mCDSS and perceive them as useful, concerns about increased workload and altered workflow hinder sustainability. Facilitators and barriers to use of mCDSS include technical and infrastructural support, ownership, health system challenges and training. Conclusions: The use of mobile clinical decision support systems in sub-Saharan Africa is an indication of progress in mHealth, although their effect on quality of service delivery is yet to be fully explored. Lessons learned are useful for informing future research, policy and practice for technologically supported health care delivery, especially in resource-poor settings.
Design of a Mobile App for Nutrition Education (TreC-LifeStyle) and Formative Evaluation with Parents of Overweight Children
Date Submitted: Dec 1, 2016
Open Peer Review Period: Dec 5, 2016 - Jan 30, 2017
Background: Nutrition and diet apps represent today a popular area of mHealth, offering the possibility of delivering behavior change interventions for healthy eating and weight management in a scalab...
Background: Nutrition and diet apps represent today a popular area of mHealth, offering the possibility of delivering behavior change interventions for healthy eating and weight management in a scalable and cost-effective way. However, if commercial apps for pediatric weight management fail to retain users because of a lack of theoretical background and evidence-based content, mHealth apps that are more evidence-based are found less engaging and popular amongst consumers. Approaching the apps development process from a multidisciplinary and user-centered design perspective is likely to help overcome these limitations, raising the chances for an easier adoption and integration of nutrition education apps within primary care interventions. Objective: The aim of this study is to describe the design and development of the TreC-LifeStyle nutrition education app and the results of a formative evaluation with parents. Methods: The design of the nutrition education intervention was based on a multidisciplinary user-centered design (UCD) approach, involving a team of behavior change experts, working with 2 nutritionists and 3 pediatricians from a primary care center. The app content was derived from evidence-based knowledge founded on the Food Pyramid and Mediterranean Diet guidelines used by pediatricians in primary care. A formative evaluation of the TreC-LifeStyle app involved 6 parents of overweight children (aged 7-12) self-reporting daily food intake of children for 6 weeks and providing feedback on the user experience with the mHealth intervention. Analysis of the app’s usage patterns during the intervention and of participants’ feedback informed the refinement of the app design and a tuning of the nutrition education strategies to improve user engagement and compliance with the intervention. Results: Design sessions with the contribution of pediatricians and nutritionists helped to define the nutrition education app and intervention, providing an effective human and virtual coaching approach to raise parents’ awareness about children’s eating behavior and lifestyle. The six parents participating to the pilot study found the app usable and showed high compliance with the intervention over the 6 weeks, but they also asked for getting a better support from the app in specifying food intake quantities, in visualizing data on calories intake/burnt, in preparing guidelines-compliant meals over the week. Conclusions: The UCD and formative evaluation of TreC-LifeStyle show that nutrition education apps are feasible and acceptable solutions to support brief health promotion interventions in primary care.