JMIR Publications

JMIR mHealth and uHealth

Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.


Journal Description

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 is indexed in PubMed Central/PubMed, and Thomson Reuters' Science Citation Index Expanded (SCIE), and is expecting its first official impact factor in July 2017.

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:

  • Mean engagement with mHealth intervention. Image sourced and copyright owned by authors.

    Analyzing mHealth Engagement: Joint Models for Intensively Collected User Engagement Data


    Background: Evaluating engagement with an intervention is a key component of understanding its efficacy. With an increasing interest in developing behavioral interventions in the mobile health (mHealth) space, appropriate methods for evaluating engagement in this context are necessary. Data collected to evaluate mHealth interventions are often collected much more frequently than those for clinic-based interventions. Additionally, missing data on engagement is closely linked to level of engagement resulting in the potential for informative missingness. Thus, models that can accommodate intensively collected data and can account for informative missingness are required for unbiased inference when analyzing engagement with an mHealth intervention. Objective: The objectives of this paper are to discuss the utility of the joint modeling approach in the analysis of longitudinal engagement data in mHealth research and to illustrate the application of this approach using data from an mHealth intervention designed to support illness management among people with schizophrenia. Methods: Engagement data from an evaluation of an mHealth intervention designed to support illness management among people with schizophrenia is analyzed. A joint model is applied to the longitudinal engagement outcome and time-to-dropout to allow unbiased inference on the engagement outcome. Results are compared to a naïve model that does not account for the relationship between dropout and engagement. Results: The joint model shows a strong relationship between engagement and reduced risk of dropout. Using the mHealth app 1 day more per week was associated with a 23% decreased risk of dropout (P<.001). The decline in engagement over time was steeper when the joint model was used in comparison with the naïve model. Conclusions: Naïve longitudinal models that do not account for informative missingness in mHealth data may produce biased results. Joint models provide a way to model intensively collected engagement outcomes while simultaneously accounting for the relationship between engagement and missing data in mHealth intervention research.

  • Tanning bed. Image source: dorianrochowski, Copyright: CC0 Public Domain.

    Design and Feasibility of a Text Messaging Intervention to Prevent Indoor Tanning Among Young Adult Women: A Pilot Study


    Background: Although skin cancer is largely preventable, it affects nearly 1 of 5 US adults. There is a need for research on how to optimally design persuasive public health indoor tanning prevention messages. Objective: The objective of our study was to examine whether framed messages on indoor tanning behavioral intentions delivered through short message service (SMS) text messaging would produce (1) positive responses to the messages, including message receptivity and emotional response; (2) indoor tanning efficacy beliefs, including response efficacy and self-efficacy; and (3) indoor tanning risk beliefs. Methods: We conducted a pilot study of indoor tanning prevention messages delivered via mobile phone text messaging in a sample of 21 young adult women who indoor tan. Participants completed baseline measures, were randomly assigned to receive gain-, loss-, or balanced-framed text messages, and completed postexposure outcome measures on indoor tanning cognitions and behaviors. Participants received daily mobile phone indoor tanning prevention text messages for 1 week and completed the same postexposure measures as at baseline. Results: Over the 1-week period there were trends or significant changes after receipt of the text messages, including increased perceived susceptibility (P<.001), response efficacy beliefs (P<.001), and message receptivity (P=.03). Ordinary least squares stepwise linear regression models showed an effect of text message exposure on self-efficacy to quit indoor tanning (t6=–2.475, P<.02). Ordinary least squares linear regression including all measured scales showed a marginal effect of SMS texts on self-efficacy (t20=1.905, P=.08). Participants endorsed highly favorable views toward the text messaging protocol. Conclusions: This study supports this use of mobile text messaging as an indoor tanning prevention strategy. Given the nature of skin cancer risk perceptions, the addition of multimedia messaging service is another area of potential innovation for disseminating indoor tanning prevention messages.

  • Smartphone. Image source: Author: JESHOOTS. Copyright: CC0 public domain.

    Smartphone Apps for Measuring Human Health and Climate Change Co-Benefits: A Comparison and Quality Rating of Available Apps


    Background: Climate change and the burden of noncommunicable diseases are major global challenges. Opportunities exist to investigate health and climate change co-benefits through a shift from motorized to active transport (walking and cycling) and a shift in dietary patterns away from a globalized diet to reduced consumption of meat and energy dense foods. Given the ubiquitous use and proliferation of smartphone apps, an opportunity exists to use this technology to capture individual travel and dietary behavior and the associated impact on the environment and health. Objective: The objective of the study is to identify, describe the features, and rate the quality of existing smartphone apps which capture personal travel and dietary behavior and simultaneously estimate the carbon cost and potential health consequences of these actions. Methods: The Google Play and Apple App Stores were searched between October 19 and November 6, 2015, and a secondary Google search using the apps filter was conducted between August 8 and September 18, 2016. Eligible apps were required to estimate the carbon cost of personal behaviors with the potential to include features to maximize health outcomes. The quality of included apps was assessed by 2 researchers using the Mobile Application Rating Scale (MARS). Results: Out of 7213 results, 40 apps were identified and rated. Multiple travel-related apps were identified, however no apps solely focused on the carbon impact or health consequences of dietary behavior. None of the rated apps provided sufficient information on the health consequences of travel and dietary behavior. Some apps included features to maximize participant engagement and encourage behavior change towards reduced greenhouse gas emissions. Most apps were rated as acceptable quality as determined by the MARS; 1 was of poor quality and 10 apps were of good quality. Interrater reliability of the 2 evaluators was excellent (ICC=0.94, 95% CI 0.87-0.97). Conclusions: Existing apps capturing travel and dietary behavior and the associated health and environmental impact are of mixed quality. Most apps do not include all desirable features or provide sufficient health information. Further research is needed to determine the potential of smartphone apps to evoke behavior change resulting in climate change and health co-benefits.

  • Mobile Apps. Image sourced and copyright owned by authors.

    Patient-Facing Mobile Apps to Treat High-Need, High-Cost Populations: A Scoping Review


    Background: Self-management is essential to caring for high-need, high-cost (HNHC) populations. Advances in mobile phone technology coupled with increased availability and adoption of health-focused mobile apps have made self-management more achievable, but the extent and quality of the literature supporting their use is not well defined. Objective: The purpose of this review was to assess the breadth, quality, bias, and types of outcomes measured in the literature supporting the use of apps targeting HNHC populations. Methods: Data sources included articles in PubMed and MEDLINE (National Center for Biotechnology Information), EMBASE (Elsevier), the Cochrane Central Register of Controlled Trials (EBSCO), Web of Science (Thomson Reuters), and the NTIS (National Technical Information Service) Bibliographic Database (EBSCO) published since 2008. We selected studies involving use of patient-facing iOS or Android mobile health apps. Extraction was performed by 1 reviewer; 40 randomly selected articles were evaluated by 2 reviewers to assess agreement. Results: Our final analysis included 175 studies. The populations most commonly targeted by apps included patients with obesity, physical handicaps, diabetes, older age, and dementia. Only 30.3% (53/175) of the apps studied in the reviewed literature were identifiable and available to the public through app stores. Many of the studies were cross-sectional analyses (42.9%, 75/175), small (median number of participants=31, interquartile range 11.0-207.2, maximum 11,690), or performed by an app’s developers (61.1%, 107/175). Of the 175 studies, only 36 (20.6%, 36/175) studies evaluated a clinical outcome. Conclusions: Most apps described in the literature could not be located on the iOS or Android app stores, and existing research does not robustly evaluate the potential of mobile apps. Whereas apps may be useful in patients with chronic conditions, data do not support this yet. Although we had 2-3 reviewers to screen and assess abstract eligibility, only 1 reviewer abstracted the data. This is one limitation of our study. With respect to the 40 articles (22.9%, 40/175) that were assigned to 2 reviewers (of which 3 articles were excluded), inter-rater agreement was significant on the majority of items (17 of 30) but fair-to-moderate on others.

  • Mobile Phone Affinity. Image Source: Author: PublicDomainPictures. Copyright: CC0 Public Domain.

    The Mobile Phone Affinity Scale: Enhancement and Refinement


    Background: Existing instruments that assess individuals’ relationships with mobile phones tend to focus on negative constructs such as addiction or dependence, and appear to assume that high mobile phone use reflects pathology. Mobile phones can be beneficial for health behavior change, disease management, work productivity, and social connections, so there is a need for an instrument that provides a more balanced assessment of the various aspects of individuals’ relationships with mobile phones. Objective: The purpose of this research was to develop, revise, and validate the Mobile Phone Affinity Scale, a multi-scale instrument designed to assess key factors associated with mobile phone use. Methods: Participants (N=1058, mean age 33) were recruited from Amazon Mechanical Turk between March and April of 2016 to complete a survey that assessed participants’ mobile phone attitudes and use, anxious and depressive symptoms, and resilience. Results: Confirmatory factor analysis supported a 6-factor model. The final measure consisted of 24 items, with 4 items on each of 6 factors: Connectedness, Productivity, Empowerment, Anxious Attachment, Addiction, and Continuous Use. The subscales demonstrated strong internal consistency (Cronbach alpha range=0.76-0.88, mean 0.83), and high item factor loadings (range=0.57-0.87, mean 0.75). Tests for validity further demonstrated support for the individual subscales. Conclusions: Mobile phone affinity may have an important impact in the development and effectiveness of mobile health interventions, and continued research is needed to assess its predictive ability in health behavior change interventions delivered via mobile phones.

  • Infographics on Pinterest, screenshot generated by JMIR from[]=%E2%80%9Cnutrition%7Ctyped&term_meta[]=infographic%E2%80%9D%7Ctyped (fair use).

    Evaluation of Diet-Related Infographics on Pinterest for Use of Behavior Change Theories: A Content Analysis


    Background: There is increasing interest in Pinterest as a method of disseminating health information. However, it is unclear whether the health information promoted on Pinterest is evidence-based or incorporates behavior change theory. Objectives: The objective of the study was to determine the presence of health behavior theory (HBT) constructs in pins found on Pinterest and assess the relationship between various pin characteristics and the likelihood of inclusion of HBT. Methods: A content analysis was conducted on pins collected from Pinterest identified with the search terms “nutrition infographic” and “healthy eating infographic.” The coding rubric included HBT constructs, pin characteristics, and visual communication tools. Each HBT construct was coded as present or not present (yes=1, no=0). A total theory score was calculated by summing the values for each of the 9 constructs (range 0-9). Adjusted regression analysis was used to identify factors associated with the inclusion of health behavior change theory in pins (P<.05). Results: The mean total theory score was 2.03 (SD 1.2). Perceived benefits were present most often (170/236, 72%), followed by behavioral capability (123/238, 51.7%) and perceived severity (79/236, 33.5%). The construct that appeared the least was self-regulation/self-control (2/237, 0.8%). Pin characteristics associated with the inclusion of HBT included a large amount of text (P=.01), photographs of real people (P=.001), cartoon pictures of food (P=.01), and the presence of references (P=.001). The number of repins (P=.04), likes (P=.01), and comments (P=.01) were positively associated with the inclusion of HBT. Conclusions: These findings suggest that current Pinterest infographics targeting healthy eating contain few HBT elements. Health professionals and organizations should create and disseminate infographics that contain more elements of HBT to better influence healthy eating behavior. This may be accomplished by creating pins that use both text and images of people and food in order to portray elements of HBT and convey nutritional information.

  • Safety Agenda Mobile App (SAMA). Image source and copyright owned by the authors.

    Design and Testing of the Safety Agenda Mobile App for Managing Health Care Managers’ Patient Safety Responsibilities


    Background: Adverse events are a reality in clinical practice. Reducing the prevalence of preventable adverse events by stemming their causes requires health managers’ engagement. Objective: The objective of our study was to develop an app for mobile phones and tablets that would provide managers with an overview of their responsibilities in matters of patient safety and would help them manage interventions that are expected to be carried out throughout the year. Methods: The Safety Agenda Mobile App (SAMA) was designed based on standardized regulations and reviews of studies about health managers’ roles in patient safety. A total of 7 managers used a beta version of SAMA for 2 months and then they assessed and proposed improvements in its design. Their experience permitted redesigning SAMA, improving functions and navigation. A total of 74 Spanish health managers tried out the revised version of SAMA. After 4 months, their assessment was requested in a voluntary and anonymous manner. Results: SAMA is an iOS app that includes 37 predefined tasks that are the responsibility of health managers. Health managers can adapt these tasks to their schedule, add new ones, and share them with their team. SAMA menus are structured in 4 main areas: information, registry, task list, and settings. Of the 74 users who tested SAMA, 64 (86%) users provided a positive assessment of SAMA characteristics and utility. Over an 11-month period, 238 users downloaded SAMA. This mobile app has obtained the AppSaludable (HealthyApp) Quality Seal. Conclusions: SAMA includes a set of activities that are expected to be carried out by health managers in matters of patient safety and contributes toward improving the awareness of their responsibilities in matters of safety.

  • Smartphone apps. Image Source: Author: Jeshoots. Copyright: CC0 Public Domain.

    Mobile Phone Apps to Improve Medication Adherence: A Systematic Stepwise Process to Identify High-Quality Apps


    Background: There are a growing number of mobile phone apps available to support people in taking their medications and to improve medication adherence. However, little is known about how these apps differ in terms of features, quality, and effectiveness. Objective: We aimed to systematically review the medication reminder apps available in the Australian iTunes store and Google Play to assess their features and their quality in order to identify high-quality apps. Methods: This review was conducted in a similar manner to a systematic review by using a stepwise approach that included (1) a search strategy; (2) eligibility assessment; (3) app selection process through an initial screening of all retrieved apps and full app review of the included apps; (4) data extraction using a predefined set of features considered important or desirable in medication reminder apps; (5) analysis by classifying the apps as basic and advanced medication reminder apps and scoring and ranking them; and (6) a quality assessment by using the Mobile App Rating Scale (MARS), a reliable tool to assess mobile health apps. Results: We identified 272 medication reminder apps, of which 152 were found only in Google Play, 87 only in iTunes, and 33 in both app stores. Apps found in Google Play had more customer reviews, higher star ratings, and lower cost compared with apps in iTunes. Only 109 apps were available for free and 124 were recently updated in 2015 or 2016. Overall, the median number of features per app was 3.0 (interquartile range 4.0) and only 18 apps had ≥9 of the 17 desirable features. The most common features were flexible scheduling that was present in 56.3% (153/272) of the included apps, medication tracking history in 54.8% (149/272), snooze option in 34.9% (95/272), and visual aids in 32.4% (88/272). We classified 54.8% (149/272) of the included apps as advanced medication reminder apps and 45.2% (123/272) as basic medication reminder apps. The advanced apps had a higher number of features per app compared with the basic apps. Using the MARS instrument, we were able to identify high-quality apps that were rated as being very interesting and entertaining, highly interactive and customizable, intuitive, and easy to use and to navigate as well as having a high level of visual appeal and good-quality information. Conclusions: Many medication reminder apps are available in the app stores; however, the majority of them did not have many of the desirable features and were, therefore, considered low quality. Through a systematic stepwise process, we were able to identify high-quality apps to be tested in a future study that will provide evidence on the use of medication reminder apps to improve medication adherence.

  • Activity Trackers Showing Goal. Image Source: Author: Mike Lee. Copyright:

    Feasibility and Effectiveness of Using Wearable Activity Trackers in Youth: A Systematic Review


    Background: The proliferation and popularity of wearable activity trackers (eg, Fitbit, Jawbone, Misfit) may present an opportunity to integrate such technology into physical activity interventions. While several systematic reviews have reported intervention effects of using wearable activity trackers on adults’ physical activity levels, none to date have focused specifically on children and adolescents. Objective: The aim of this review was to examine the effectiveness of wearable activity trackers as a tool for increasing children’s and adolescents’ physical activity levels. We also examined the feasibility of using such technology in younger populations (age range 5-19 years). Methods: We conducted a systematic search of 5 electronic databases, reference lists, and personal archives to identify articles published up until August 2016 that met the inclusion criteria. Articles were included if they (1) specifically examined the use of a wearable device within an intervention or a feasibility study; (2) included participants aged 5-19 years old; (3) had a measure of physical activity as an outcome variable for intervention studies; (4) reported process data concerning the feasibility of the device in feasibility studies; and (5) were published in English. Data were analyzed in August 2016. Results: In total, we identified and analyzed 5 studies (3 intervention, 2 feasibility). Intervention delivery ranged from 19 days to 3 months, with only 1 study using a randomized controlled trial design. Wearable activity trackers were typically combined with other intervention approaches such as goal setting and researcher feedback. While intervention effects were generally positive, the reported differences were largely nonsignificant. The feasibility studies indicated that monitor comfort and design and feedback features were important factors to children and adolescents. Conclusions: There is a paucity of research concerning the effectiveness and feasibility of wearable activity trackers as a tool for increasing children’s and adolescents’ physical activity levels. While there are some preliminary data to suggest these devices may have the potential to increase activity levels through self-monitoring and goal setting in the short term, more research is needed to establish longer-term effects on behavior.

  • God's Lonely man. Image source: Author: Zigg-E. Copyright:

    Formative Work to Develop a Tailored HIV Testing Smartphone App for Diverse, At-Risk, HIV-Negative Men Who Have Sex With Men: A Focus Group Study


    Background: Although gay, bisexual, and other men who have sex with men (MSM) are disproportionately affected by human immunodeficiency virus (HIV) infection, few test for HIV at regular intervals. Smartphone apps may be an ideal tool to increase regular testing among MSM. However, the success of apps to encourage regular testing among MSM will depend on how frequently the apps are downloaded, whether they continue to be used over months or years, and the degree to which such apps are tailored to the needs of this population. Objective: The primary objectives of this study were to answer the following questions. (1) What features and functions of smartphone apps do MSM believe are associated with downloading apps to their mobile phones? (2) What features and functions of smartphone apps are most likely to influence MSM’s sustained use of apps over time? (3) What features and functions do MSM prefer in an HIV testing smartphone app? Methods: We conducted focus groups (n=7, with a total of 34 participants) with a racially and ethnically diverse group of sexually active HIV-negative MSM (mean age 32 years; 11/34 men, 33%, tested for HIV ≥10 months ago) in the United States in Miami, Florida and Minneapolis, Minnesota. Focus groups were digitally recorded, transcribed verbatim, and deidentified for analysis. We used a constant comparison method (ie, grounded theory coding) to examine and reexamine the themes that emerged from the focus groups. Results: Men reported cost, security, and efficiency as their primary reasons influencing whether they download an app. Usefulness and perceived necessity, as well as peer and posted reviews, affected whether they downloaded and used the app over time. Factors that influenced whether they keep and continue to use an app over time included reliability, ease of use, and frequency of updates. Poor performance and functionality and lack of use were the primary reasons why men would delete an app from their phone. Participants also shared their preferences for an app to encourage regular HIV testing by providing feedback on test reminders, tailored testing interval recommendations, HIV test locator, and monitoring of personal sexual behaviors. Conclusions: Mobile apps for HIV prevention have proliferated, despite relatively little formative research to understand best practices for their development and implementation. The findings of this study suggest key design characteristics that should be used to guide development of an HIV testing app to promote regular HIV testing for MSM. The features and functions identified in this and prior research, as well as existing theories of behavior change, should be used to guide mobile app development in this critical area.

  • TextCare. Image sourced and copyright owned by authors.

    Design Considerations in Development of a Mobile Health Intervention Program: The TEXT ME and TEXTMEDS Experience


    Background: Mobile health (mHealth) has huge potential to deliver preventative health services. However, there is paucity of literature on theoretical constructs, technical, practical, and regulatory considerations that enable delivery of such services. Objectives: The objective of this study was to outline the key considerations in the development of a text message-based mHealth program; thus providing broad recommendations and guidance to future researchers designing similar programs. Methods: We describe the key considerations in designing the intervention with respect to functionality, technical infrastructure, data management, software components, regulatory requirements, and operationalization. We also illustrate some of the potential issues and decision points utilizing our experience of developing text message (short message service, SMS) management systems to support 2 large randomized controlled trials: TEXT messages to improve MEDication adherence & Secondary prevention (TEXTMEDS) and Tobacco, EXercise and dieT MEssages (TEXT ME). Results: The steps identified in the development process were: (1) background research and development of the text message bank based on scientific evidence and disease-specific guidelines, (2) pilot testing with target audience and incorporating feedback, (3) software-hardware customization to enable delivery of complex personalized programs using prespecified algorithms, and (4) legal and regulatory considerations. Additional considerations in developing text message management systems include: balancing the use of customized versus preexisting software systems, the level of automation versus need for human inputs, monitoring, ensuring data security, interface flexibility, and the ability for upscaling. Conclusions: A merging of expertise in clinical and behavioral sciences, health and research data management systems, software engineering, and mobile phone regulatory requirements is essential to develop a platform to deliver and manage support programs to hundreds of participants simultaneously as in TEXT ME and TEXTMEDS trials. This research provides broad principles that may assist other researchers in developing mHealth programs.

  • Women with her phone. Image source: Author: Brian Strickland. Copyright: Authors.

    A Systematic Review of Apps using Mobile Criteria for Adolescent Pregnancy Prevention (mCAPP)


    Background: Adolescents in the United States and globally represent a high-risk population for unintended pregnancy, which leads to high social, economic, and health costs. Access to smartphone apps is rapidly increasing among youth, but little is known about the strategies that apps employ to prevent pregnancy among adolescents and young adults. Further, there are no guidelines on best practices for adolescent and young adult pregnancy prevention through mobile apps. Objective: This review developed a preliminary evaluation framework for the assessment of mobile apps for adolescent and young adult pregnancy prevention and used this framework to assess available apps in the Apple App Store and Google Play that targeted adolescents and young adults with family planning and pregnancy prevention support. Methods: We developed an assessment rubric called Mobile Criteria for Adolescent Pregnancy Prevention (mCAPP) for data extraction using evidence-based and promising best practices from the literature. mCAPP comprises 4 domains: (1) app characteristics, (2) user interface features, (3) adolescent pregnancy prevention best practices, and (4) general sexual and reproductive health (SRH) features. For inclusion in the review, apps that advertised pregnancy prevention services and explicitly mentioned youth, were in English, and were free were systematically identified in the Apple App Store and Google Play in 2015. Screening, data extraction, and 4 interrater reliability checks were conducted by 2 reviewers. Each app was assessed for 92 facets of the mCAPP checklist. Results: Our search returned 4043 app descriptions in the Apple App Store (462) and Google Play (3581). After screening for inclusion criteria, 22 unique apps were included in our analysis. Included apps targeted teens in primarily developed countries, and the most common user interface features were clinic and health service locators. While app strengths included provision of SRH education, description of modern contraceptives, and some use of evidence-based adolescent best practices, gaps remain in the implementation of the majority of adolescent best practices and user interface features. Of the 8 best practices for teen pregnancy prevention operationalized through mCAPP, the most commonly implemented best practice was the provision of information on how to use contraceptives to prevent pregnancy (15/22), followed by provision of accurate information on pregnancy risk of sexual behaviors (13/22); information on SRH communication, negotiation, or refusal skills (10/22); and the use of persuasive language around contraceptive use (9/22). Conclusions: The quality and scope of apps for adolescent pregnancy prevention varies, indicating that developers and researchers may need a supportive framework. mCAPP can help researchers and developers consider mobile-relevant evidence-based best practices for adolescent SRH as they develop teen pregnancy prevention apps. Given the novelty of the mobile approach, further research is needed on the impact of mCAPP criteria via mobile channels on adolescent health knowledge, behaviors, and outcomes.

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  • 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.