Maintenance Note

On Friday, August 31, 2018 at 12:00 pm Eastern Time, JMIR will be completing a server migration to improve site stability and user experience. We expect to be back online Friday, August 31, 2018 at 5:00 pm Eastern Time. Should any problems arise our technical team will be using the weekend to resolve them, and users will be able to access our site by Sunday, September 2, 2018 at 1:00pm Eastern Time.

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Journal Description

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

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

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

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

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


Recent Articles:

  • Source: Image created by the Authors; Copyright: The Authors; URL:; License: Licensed by JMIR.

    A Dietary Management System Using Radio-Frequency Identification Technology to Collect Information on Chinese Food Consumption: Development and Feasibility...


    Background: Dietary management is important for personal health. However, it is challenging to record quantified food information in an efficient, accurate, and sustainable manner, particularly for the consumption of Chinese food. Objective: The objective of this study was to develop a dietary management system to record information on consumption of Chinese food, which can help in assessing individuals’ dietary intake and maintaining healthy eating behaviors. We proposed to use plates embedded with radio-frequency identification chips to carry Chinese foods and collect food consumption data. Methods: We obtained food composition and nutrient (eg, carbohydrate, fat, fiber) data from the Chinese Recipe Database and China Food Composition Database. To test the feasibility of the dietary management system at a population level, we applied it to collect data on 489 Chinese foods that were consumed at lunchtime across 7 weeks by 10,528 individuals. To test individual-level output, we selected an individual participant with completed 20-day dietary data for analysis. We examined the system’s nutrient calculation performance by comparing the nutrient values of 3 selected Chinese dishes calculated by our method with the results of chemical measurements. Results: We collected the dietary intake for a group of 10,528 individuals aged from 20 to 40 years having lunch in a restaurant across 7 weeks. A total of 489 Chinese dishes were identified. We analyzed a specified customer’s diet recordings and broke his or her 20 lunch diet recordings down to ingredients and then to nutrient intake. We compared the nutrient value of a given Chinese dish (eg, garlic puree cooked pork leg) calculated by our method with the results of chemical measurements. The mean absolute percentage deviation showed that our method enabled collection of dietary intake for Chinese foods. Conclusions: This preliminary study demonstrated the feasibility of radio-frequency identification–based dietary management for Chinese food consumption. In future, we will investigate factors such as preparation method, weight of food consumed, and auxiliary ingredients to improve dietary assessment accuracy.

  • Comparison of location information collected from a GPS watch and a smartphone (montage). Source: The Authors /; Copyright: JMIR Publications; URL:; License: Creative Commons Attribution + Noncommercial + ShareAlike (CC-BY-NC-SA).

    Comparing the Data Quality of Global Positioning System Devices and Mobile Phones for Assessing Relationships Between Place, Mobility, and Health: Field Study


    Background: Mobile devices are increasingly used to collect location-based information from individuals about their physical activities, dietary intake, environmental exposures, and mental well-being. Such research, which typically uses wearable devices or mobile phones to track location, benefits from the growing availability of fine-grained data regarding human mobility. However, little is known about the comparative geospatial accuracy of such devices. Objective: In this study, we compared the data quality of location information collected from two mobile devices that determine location in different ways—a global positioning system (GPS) watch and a mobile phone with Google’s Location History feature enabled. Methods: A total of 21 chronically ill participants carried both devices, which generated digital traces of locations, for 28 days. A mobile phone–based brief ecological momentary assessment (EMA) survey asked participants to manually report their location at 4 random times throughout each day. Participants also took part in qualitative interviews and completed surveys twice during the study period in which they reviewed recent mobile phone and watch trace data to compare the devices’ trace data with their memory of their activities on those days. Trace data from the devices were compared on the basis of (1) missing data days, (2) reasons for missing data, (3) distance between the route data collected for matching day and the associated EMA survey locations, and (4) activity space total area and density surfaces. Results: The watch resulted in a much higher proportion of missing data days (P<.001), with missing data explained by technical differences between the devices as well as participant behaviors. The mobile phone was significantly more accurate in detecting home locations (P=.004) and marginally more accurate (P=.07) for all types of locations combined. The watch data resulted in a smaller activity space area and more accurately recorded outdoor travel and recreation. Conclusions: The most suitable mobile device for location-based health research depends on the particular study objectives. Furthermore, data generated from mobile devices, such as GPS phones and smartwatches, require careful analysis to ensure quality and completeness. Studies that seek precise measurement of outdoor activity and travel, such as measuring outdoor physical activity or exposure to localized environmental hazards, would benefit from the use of GPS devices. Conversely, studies that aim to account for time within buildings at home or work, or those that document visits to particular places (such as supermarkets, medical facilities, or fast food restaurants), would benefit from the greater precision demonstrated by the mobile phone in recording indoor activities.

  • Proficient runners attract extensive attention in association with city races and championships worldwide, leading to strong competitiveness, mounting training loads, and increasing injury risk. Source: The Authors; Copyright: The Authors; URL:; License: Licensed by JMIR.

    mHealth Self-Report Monitoring in Competitive Middle- and Long-Distance Runners: Qualitative Study of Long-Term Use Intentions Using the Technology...


    Background: International middle- and long-distance running competitions attract millions of spectators in association with city races, world championships, and Olympic Games. It is therefore a major concern that ill health and pain, as a result of sports overuse, lead to numerous hours of lost training and decreased performance in competitive runners. Despite its potential for sustenance of performance, approval of mHealth self-report monitoring (mHSM) in this group of athletes has not been investigated. Objective: The objective of our study was to explore individual and situational factors associated with the acceptance of long-term mHSM in competitive runners. Methods: The study used qualitative research methods with the Technology Acceptance Model as the theoretical foundation. The study population included 20 middle- and long-distance runners competing at national and international levels. Two mHSM apps asking for health and training data from track and marathon runners were created on a platform for web survey development (Briteback AB). Data collection for the technology acceptance analysis was performed via personal interviews before and after a 6-week monitoring period. Preuse interviews investigated experience and knowledge of mHealth monitoring and thoughts on benefits and possible side effects. The postuse interviews addressed usability and usefulness, attitudes toward nonfunctional issues, and intentions to adhere to long-term monitoring. In addition, the runners’ trustworthiness when providing mHSM data was discussed. The interview data were investigated using a deductive thematic analysis. Results: The mHSM apps were considered technically easy to use. Although the runners read the instructions and entered data effortlessly, some still perceived mHSM as problematic. Concerns were raised about the selection of items for monitoring (eg, recording training load as running distance or time) and about interpretation of concepts (eg, whether subjective well-being should encompass only the running context or daily living on the whole). Usefulness of specific mHSM apps was consequently not appraised on the same bases in different subcategories of runners. Regarding nonfunctional issues, the runners competing at the international level requested detailed control over who in their sports club and national federation should be allowed access to their data; the less competitive runners had no such issues. Notwithstanding, the runners were willing to adhere to long-term mHSM, provided the technology was adjusted to their personal routines and the output was perceived as contributing to running performance. Conclusions: Adoption of mHSM by competitive runners requires clear definitions of monitoring purpose and populations, repeated in practice tests of monitoring items and terminology, and meticulousness regarding data-sharing routines. Further naturalistic studies of mHSM use in routine sports practice settings are needed with nonfunctional ethical and legal issues included in the evaluation designs.

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

    Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective...


    Background: Several studies have recently reported on the correlation between objective behavioral features collected via mobile and wearable devices and depressive mood symptoms in patients with affective disorders (unipolar and bipolar disorders). However, individual studies have reported on different and sometimes contradicting results, and no quantitative systematic review of the correlation between objective behavioral features and depressive mood symptoms has been published. Objective: The objectives of this systematic review were to (1) provide an overview of the correlations between objective behavioral features and depressive mood symptoms reported in the literature and (2) investigate the strength and statistical significance of these correlations across studies. The answers to these questions could potentially help identify which objective features have shown most promising results across studies. Methods: We conducted a systematic review of the scientific literature, reported according to the preferred reporting items for systematic reviews and meta-analyses guidelines. IEEE Xplore, ACM Digital Library, Web of Sciences, PsychINFO, PubMed, DBLP computer science bibliography, HTA, DARE, Scopus, and Science Direct were searched and supplemented by hand examination of reference lists. The search ended on April 27, 2017, and was limited to studies published between 2007 and 2017. Results: A total of 46 studies were eligible for the review. These studies identified and investigated 85 unique objective behavioral features, covering 17 various sensor data inputs. These features were divided into 7 categories. Several features were found to have statistically significant and consistent correlation directionality with mood assessment (eg, the amount of home stay, sleep duration, and vigorous activity), while others showed directionality discrepancies across the studies (eg, amount of text messages [short message service] sent, time spent between locations, and frequency of mobile phone screen activity). Conclusions: Several studies showed consistent and statistically significant correlations between objective behavioral features collected via mobile and wearable devices and depressive mood symptoms. Hence, continuous and everyday monitoring of behavioral aspects in affective disorders could be a promising supplementary objective measure for estimating depressive mood symptoms. However, the evidence is limited by methodological issues in individual studies and by a lack of standardization of (1) the collected objective features, (2) the mood assessment methodology, and (3) the statistical methods applied. Therefore, consistency in data collection and analysis in future studies is needed, making replication studies as well as meta-analyses possible.

  • The Fitbit Flex. Source: Image created by the authors; Copyright: The Authors; URL:; License: Licensed by JMIR.

    Accuracy of Fitbit Devices: Systematic Review and Narrative Syntheses of Quantitative Data


    Background: Although designed as a consumer product to help motivate individuals to be physically active, Fitbit activity trackers are becoming increasingly popular as measurement tools in physical activity and health promotion research and are also commonly used to inform health care decisions. Objective: The objective of this review was to systematically evaluate and report measurement accuracy for Fitbit activity trackers in controlled and free-living settings. Methods: We conducted electronic searches using PubMed, EMBASE, CINAHL, and SPORTDiscus databases with a supplementary Google Scholar search. We considered original research published in English comparing Fitbit versus a reference- or research-standard criterion in healthy adults and those living with any health condition or disability. We assessed risk of bias using a modification of the Consensus-Based Standards for the Selection of Health Status Measurement Instruments. We explored measurement accuracy for steps, energy expenditure, sleep, time in activity, and distance using group percentage differences as the common rubric for error comparisons. We conducted descriptive analyses for frequency of accuracy comparisons within a ±3% error in controlled and ±10% error in free-living settings and assessed for potential bias of over- or underestimation. We secondarily explored how variations in body placement, ambulation speed, or type of activity influenced accuracy. Results: We included 67 studies. Consistent evidence indicated that Fitbit devices were likely to meet acceptable accuracy for step count approximately half the time, with a tendency to underestimate steps in controlled testing and overestimate steps in free-living settings. Findings also suggested a greater tendency to provide accurate measures for steps during normal or self-paced walking with torso placement, during jogging with wrist placement, and during slow or very slow walking with ankle placement in adults with no mobility limitations. Consistent evidence indicated that Fitbit devices were unlikely to provide accurate measures for energy expenditure in any testing condition. Evidence from a few studies also suggested that, compared with research-grade accelerometers, Fitbit devices may provide similar measures for time in bed and time sleeping, while likely markedly overestimating time spent in higher-intensity activities and underestimating distance during faster-paced ambulation. However, further accuracy studies are warranted. Our point estimations for mean or median percentage error gave equal weighting to all accuracy comparisons, possibly misrepresenting the true point estimate for measurement bias for some of the testing conditions we examined. Conclusions: Other than for measures of steps in adults with no limitations in mobility, discretion should be used when considering the use of Fitbit devices as an outcome measurement tool in research or to inform health care decisions, as there are seemingly a limited number of situations where the device is likely to provide accurate measurement.

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

    The Effect of Mobile App Interventions on Influencing Healthy Maternal Behavior and Improving Perinatal Health Outcomes: Systematic Review


    Background: Perinatal morbidity and mortality are significant public health issues with an enduring impact on the health and well-being of women and their families. Millions of pregnant women now download and use mobile applications to access, store, and share health information. However, little is known about the consequences. An investigation of their impact on perinatal health outcomes is particularly topical. Objective: To determine the effects of mobile app interventions during pregnancy on influencing healthy maternal behavior and improving perinatal health outcomes. Methods: Searches of PubMed, Embase, the Cochrane Library, CINAHL, WHO Global Health Library, POPLINE, and CABI Global Health were conducted with no date or language restrictions. Randomized and non-randomized studies were included if they reported perinatal health outcomes of interventions targeting pregnant women, using mobile apps compared with other communication modalities or with standard care. The primary outcome measure was the change in maternal behaviors (as defined by trial authors), by intervention goals. Two reviewers independently extracted data using standardized forms. Results: Four randomized controlled trials (RCTs) involving 456 participants were included. All studies targeted participants in early pregnancy; however, wide variation was evident in participant characteristics, intervention, and study outcomes measures. Three trials were based in hospital settings, comparing women using mobile apps with routine antenatal care. One community-based trial gave all participants a device to promote physical activity; the intervention arm was also given a mobile app. All studies reported data for the primary outcome measure, describing some benefit from the intervention compared with controls. However, few statistically significant primary or secondary outcomes were reported. Due to insufficient data, the planned meta-analysis and subgroup analyses were not performed. Conclusions: Due to limited numbers, heterogeneity of interventions, comparators, and outcome measures, no firm conclusions can be drawn on the effects of mobile application interventions during pregnancy on maternal knowledge, behavior change, and perinatal health outcomes. As millions of women utilize mobile apps during pregnancy, rigorous studies are essential for health care and maternity care providers to optimally design, implement, and evaluate interventions.

  • Source: Flickr; Copyright: Ben Grey; URL:; License: Creative Commons Attribution + ShareAlike (CC-BY-SA).

    A Web-Based Survey Assessing the Attitudes of Health Care Professionals in Germany Toward the Use of Telemedicine in Pregnancy Monitoring: Cross-Sectional Study


    Background: The demand for fetal monitoring and constant reassurance is high in pregnant women. Consequently, pregnant women use various health apps and are more likely to visit emergency departments due to subjective but nonurgent complaints. However, electronic health (eHealth) and mobile health (mHealth) solutions are rarely used to prevent nonurgent emergency consultations. To implement modern care solutions, a better understanding of the attitudes, fears, and hopes of health care professionals toward eHealth and mHealth is needed. Objective: The aim of this study was to investigate the attitudes of health care professionals in obstetrics toward telemedicine. Methods: A quantitative Web-based survey on health care professionals in obstetrics in Germany was conducted. The participants included nurses, midwives, and physicians of all age groups and job positions working in hospitals that provide various levels of health care. The questionnaire comprised 24 questions about the characteristics of the study population, views about emergency consultations in obstetrics, attitude toward telemedicine, job satisfaction, and sleeping behavior. Results: In total, 244 health care professionals participated in the Web-based survey. In general, health care professionals were skeptical (170/233, 72.9%) about the use of telemedicine in obstetrics; however, 55.8% (130/233) recognized its potential. Moreover, 72% (62/86) of physicians were optimistic in using apps for pregnancy monitoring, whereas 36.1% (47/130) of nonphysicians (P<.001) were not. Significantly, more nonphysicians rejected such developments (75/130, 57.7% rejected) compared with physicians (24/86, 28%; P<.001). We also found that obstetricians with more than 10 years of work-experience are more skeptical; however, approximately 49% (18/37) of them believed that telemedicine could reduce nonurgent emergency consultations, whereas 73.2% (106/145) of obstetricians with less than 5 years of experience (P=.01) thought otherwise. Our survey revealed a high job satisfaction and a prevalence of regular sleeping problems of 45.9% (91/198) among health care professionals in obstetrics. Surprisingly, both job satisfaction and sleeping problems were independent from the number of night shifts per month (P=.77 and P=.99, respectively). Yet, 56.6% (112/198) of the survey participants thought they would be happier with their job if they had to work fewer night shifts per month. Conclusions: Our study reveals an ambivalent attitude toward the use of telemedicine among health care professionals in obstetrics in Germany at the moment. Efforts to promote the use of telemedicine should focus on nurses and midwives because these groups are the most skeptical. By contrast, particularly young physicians recognize the potential of apps in patient care and would like to use such technology in pregnancy monitoring.

  • Capturing a suspicious mole with a smartphone. Source: The Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution (CC-BY).

    mHealth Approaches in Managing Skin Cancer: Systematic Review of Evidence-Based Research Using Integrative Mapping


    Background: mHealth, which encompasses mobile health technologies and interventions, is rapidly evolving in various medical specialties, and its impact is evident in oncology. In particular, mHealth has established itself as a prominent part of dermatology for cancer screening. Intensified research to seek its use and effectiveness in each phase of the skin cancer continuum is needed in this fast-growing field of teledermatology. Objective: The purpose of this review was to describe current trends in research addressing the integration of mHealth and its contributions across the skin cancer continuum. Methods: A systematic review framework was applied to the search using three electronic databases: PubMed, Web of Science, and Embase. We extensively reviewed appropriate studies regarding skin cancer and mobile technology published between 2007 and 2017. Studies of the role and impact of mobile technology in the prevention and management of skin cancer were included. We selected 18 studies adhering to the inclusion and exclusion criteria for analysis. Results: Of the 18 studies, 5 (28%) evaluated prevention interventions, 6 (33%) assessed diagnostic accuracy, and 7 (39%) pertained to feasibility in the context of mHealth approaches for skin cancer care. These studies portray the potential of mobile teledermatology in the prevention and management of skin cancer. However, not all phases of skin cancer involve mHealth, and not all have been addressed by research. Conclusions: This review extends our knowledge not only on the contributions of mHealth technologies, but also on their integration in different phases of skin cancer care. To optimize the effectiveness of mHealth in dermatology, larger numbers of robust, evidence-based studies on teledermatology implementations, distributed evenly across the care continuum, should be conducted so that research can be expanded to systematic reviews.

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

    A Smartphone Game-Based Intervention (Tumaini) to Prevent HIV Among Young Africans: Pilot Randomized Controlled Trial


    Background: There is a pressing need to ensure that youth in high HIV prevalence settings are prepared for a safer sexual debut. Smartphone ownership is increasing dramatically in low-income and middle-income countries. Smartphone games that are appropriately grounded in behavioral theory and evidence-based practice have the potential to become valuable tools in youth HIV prevention efforts in Sub-Saharan Africa. Objective: To pilot-test a theory-based, empirically grounded smartphone game for young Kenyans designed to increase age and condom use at first sex, aiming to establish directionality of effects on behavior change. Methods: Tumaini (“hope for the future” in Swahili) is an interactive, narrative-based game grounded in social cognitive theory. A randomized controlled pilot study was conducted in Kisumu, Western Kenya, from April to June 2017 with 60 participants aged 11-14 (mean 12.7) years. Intervention arm participants (n=30) were provided with an Android smartphone with Tumaini installed on it and were instructed to play the game for at least 1 hour a day for 16 days; control arm participants (n=30) received no intervention. All participants completed a survey on behavioral mediators, delivered via an audio computer-assisted self-interview system at baseline (T1), post intervention (T2), and at 6 weeks postintervention (T3). The postintervention survey for intervention arm participants included questions eliciting feedback on the game. Intervention arm participants and their parents participated in 8 postintervention focus group discussions. Game log files were analyzed to calculate the length of exposure to the game. Behavioral survey data were analyzed using two-sample t tests to compare mean change from T1 to T2 and to T3 for intervention versus control arm participants. Descriptive statistics on game feedback questions were computed. Focus group transcripts were uploaded to MAXQDA software, where they were labeled with deductive and inductive codes. Data were analyzed thematically and compared across demographics. Results: Intervention arm participants played Tumaini for a mean of approximately 27 hours. The intervention arm showed significant gains in sexual health-related knowledge and self-efficacy (both P<.001), behavioral intention for risk-avoidance strategies and sexual risk communication (P=.006), and overall survey scores (P<.001) compared with the control arm at T3. The postintervention survey revealed high subjective measures of the game’s value, relevance, and appeal. Focus groups identified a wide range of knowledge and skills the participants had gained, including setting goals and planning how to achieve them, which was perceived as a key motivator for avoiding or reducing risk. Conclusions: The study supports the need for further research to assess the efficacy of the game-based intervention. If proven efficacious, smartphone games have the potential to dramatically increase the reach of culturally adapted behavioral interventions while ensuring fidelity to intervention design. Trial Registration: NCT03054051; (Archived by WebCite at

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

    Evaluating the Implementation of a Mobile Phone–Based Telemonitoring Program: Longitudinal Study Guided by the Consolidated Framework for Implementation...


    Background: Telemonitoring has shown promise for alleviating the burden of heart failure on individuals and health systems. However, real-world implementation of sustained programs is rare. Objective: The objective of this study was to evaluate the implementation of a mobile phone–based telemonitoring program, which has been implemented as part of standard care in a specialty heart function clinic by answering two research questions: (1) To what extent was the telemonitoring program successfully implemented? (2) What were the barriers and facilitators to implementing the telemonitoring program? Methods: We conducted a longitudinal single case study. The implementation success was evaluated using the following four implementation outcomes: adoption, penetration, feasibility, and fidelity. Semistructured interviews based on the Consolidated Framework for Implementation Research (CFIR) were conducted at 0, 4, and 12 months with 12 program staff members to identify the barriers and facilitators of the implementation. Results: One year after the implementation, 98 patients and 8 clinicians were enrolled in the program. Despite minor technical issues, the intervention was used as intended. We obtained qualitative data from clinicians (n=8) and implementation staff members (n=4) for 24 CFIR constructs. A total of 12 constructs were facilitators clustered in the CFIR domains of inner setting (culture, tension for change, compatibility, relative priority, learning climate, leadership engagement, and available resources), characteristics of individuals (knowledge and beliefs about the intervention and self-efficacy), and process (engaging and reflecting and evaluating). In addition, we identified other notable facilitators from the characteristics of the intervention domain (relative advantage and adaptability) and the outer setting (patient needs and resources). Four constructs were perceived as minor barriers— the complexity of the intervention, cost, inadequate communication among high-level stakeholders, and the absence of a formal implementation plan. The remaining CFIR constructs had a neutral impact on the overall implementation. Conclusions: This is the first comprehensive evaluation of the implementation of a mobile phone–based telemonitoring program. Although the acceptability of the telemonitoring system was high, the strongest facilitators to the implementation success were related to the implementation context. By identifying what works and what does not in a real-world clinical context using a framework-guided approach, this work will inform the design of telemonitoring services and implementation strategies of similar telemonitoring interventions.

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

    A Realistic Talking Human Embodied Agent Mobile Phone Intervention to Promote HIV Medication Adherence and Retention in Care in Young HIV-Positive African...


    Background: Avatars and embodied agents are a promising innovation for human health intervention because they may serve as a relational agent that might augment user engagement in a behavioral change intervention and motivate behavioral change such as antiretroviral adherence and retention in care. Objective: This study aimed to develop a theory-driven talking avatar-like embodied agent mobile phone intervention guided by the information-motivation-behavioral skills model to promote HIV medication adherence and retention in care in young African American men who have sex with men (MSM). Methods: We performed 5 iterative focus groups in Chicago with HIV-positive African American MSM aged 18-34 years to inform the ongoing development of a mobile phone app. Participants for the focus groups were recruited from 4 University of Illinois at Chicago Community Outreach Intervention Project sites located in different high HIV incidence areas of the city and the University of Illinois at Chicago HIV clinic using fliers and word of mouth. The focus group data analysis included developing an ongoing list of priorities for app changes and discussion between two of the investigators based on the project timeline, resources, and to what extent they served the app’s objectives. Results: In this study, 16 men participated, including 3 who participated in two groups. The acceptability for an embodied agent app was universal in all 5 focus groups. The app included the embodied agent response to questions and antiretroviral regimen information, adherence tracking, CD4 count and viral load tracking, motivational spoken messages, and customizability. Concerns that were identified and responded to in the development process included privacy, stigma, avoiding the harsh or commanding tone of voice, avoiding negative motivational statements, and making reminder functions for a variety of health care interactions. Conclusions: An avatar-like embodied agent mHealth approach was acceptable to young HIV-positive African American MSM. Its relational nature may make it an effective method of informing, motivating, and promoting health behavioral skills. Furthermore, the app’s ease of access, stigma-free environment, and audiovisual format may help overcome some adherence barriers reported in this population.

  • Source: Flickr; Copyright: Intel Free Press; URL:; License: Creative Commons Attribution (CC-BY).

    A Path to Better-Quality mHealth Apps

    Authors List:


    The rapid growth of mobile health (mHealth) apps has resulted in confusion among health care providers and the public about which products rely on evidence-based medicine. Only a small subset of mHealth apps are regulated by the US Food and Drug Administration. The system similar to that used to accredit and certify laboratory testing under the Clinical Laboratory Improvement Amendment offers a potential model for ensuring basic standards of quality and safety for mHealth apps. With these products expanding into the realm of diagnosis and treatment, physicians and consumers are in a strong position to demand oversight that delivers safe and high-quality mHealth apps.

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  • A Model for Assessing Clinicians’ Readiness to Adopt mHealth into Rural Patient Care

    Date Submitted: Aug 10, 2018

    Open Peer Review Period: Aug 14, 2018 - Oct 9, 2018

    Background: Mobile health (mHealth) technology dissemination has penetrated rural and urban areas alike. Yet, healthcare organization oversight and clinician adoption have not kept pace with patient u...

    Background: Mobile health (mHealth) technology dissemination has penetrated rural and urban areas alike. Yet, healthcare organization oversight and clinician adoption have not kept pace with patient use. mHealth could have a unique impact on health and quality of life for rural populations. Objective: This study explored organizational readiness for rural mHealth adoption, the use of patient-reported data by clinical care teams, and potential impact on improving rural healthcare delivery. Methods: : Semi-structured, open-ended interviews were used to investigate clinicians’ current practices, motivators, and perceived barriers to their use of mHealth technologies in rural settings. Results: Thirteen clinicians were interviewed, and 53.8% reported encouraging use of mHealth apps or wearable devices with rural patients. Perceived barriers to adoption were categorized into three primary pillars: 1) personal (clinician), 2) patient, and 3) organizational. Organizational was most prominent, with sub-codes of time, uniformity, and policy/direction. Thematic analysis revealed code-category linkages that identify the complex nature of a rural healthcare organization’s current climate from a clinician perspective. A thematic map was developed to visualize the flow from category to code. Identified linkages guided the development of a refined rural mHealth readiness model. Conclusions: Clinicians (physicians included) have limited time for continuing education, research, or exploration of emerging technologies. If organizations were prepared to manage mHealth, it is likely clinicians could improve the quality of care for their patients, both rural and urban. However, many organizations are not yet prepared to prescribe or prohibit third-party mHealth technologies. Clinicians are motivated to learn more, but they need guidance through organization-led directives. Rural healthcare institutions should invest in mHealth analysis, tool development, and formal recommendations of sanctioned tools for clinicians to use with patients.

  • Impact of Use Frequency of a Mobile Diabetes Management App on Blood Glucose Control

    Date Submitted: Aug 14, 2018

    Open Peer Review Period: Aug 14, 2018 - Aug 23, 2018

    Background: Technology has long been used to carry out self-management as well as improve adherence to treatment of diabetic patients. However, most technology-based applications (apps) do not meet th...

    Background: Technology has long been used to carry out self-management as well as improve adherence to treatment of diabetic patients. However, most technology-based applications (apps) do not meet the basic requirements for engaging patients. Objective: To evaluate the effect of use frequency of a diabetes management app on glycemic control and analyze the role of app engagement through self-efficacy and personal empowerment. Methods: Two studies were performed. The first analyzed the reduction of blood glucose (BG) mean and the respective HbA1c, using a randomly selected group of 211 users of the SocialDiabetes app, among which 68.2% (144/211) had type 1 diabetes (T1D) and 31.8% (67/211) had type 2 diabetes (T2D). BG levels at baseline, month 3, and month 6 were calculated using the intercept of a regression model based on data from months 1, 4, and 7, respectively. The second study examined the impact of low and high BG risk. A total of 2692 users of the SocialDiabetes app were analyzed, among which 83.5% (2248/2692) had T1D and 16.5% (444/2692) had T2D. From each group, the highest quartile regarding low and high BG indices (LBGI and HBGI) at baseline (t1) was selected (n=74 for group A, n=440 for group B). Changes in HBGI and LBGI at month 6 (t2) were analyzed. Inclusion criteria: engagement (logging ≥5 days/month for ≥6 months). Results: For study 1, baseline BG-results for T1D groups A and B were 213.61 (SD=31.57) mg/dL and 206.43 (SD=18.65) mg/dL, respectively, which decreased at month 6 to 175.15 (SD=37.88) mg/dL and 180.6 (SD=40.47) mg/dL, respectively. For T2D, baseline BG was 218.77 (SD=40.18) mg/dL and 232.55 (SD=46.78) mg/dL, respectively, which decreased at month 6 to 160.51 (SD=39.32) mg/dL and 173.14 (SD=52.81) mg/dL for groups A and B, respectively. This represents a reduction of eA1c of approximately 1.3% (P<.001) and 0.9% (P=.001) for T1D groups A and B, respectively, and 2% (P<.001) for both A and B T2D groups, respectively. For study 2, T1D baseline LBGI results for groups A and B were 5.2 (SD=3.9) and 4.4 (SD=2.3), respectively, which decreased at t2 to 3.4 (SD=3.3) and 3.4 (SD=1.9), respectively; this was a reduction of 39% (P=.005) and 22% (P=.02), respectively, in the mean. Baseline HBGI results for groups A and B were 12.6 (SD=4.3) and 10.6 (SD=4.03), respectively, which decreased at t2 to 9.0 (SD=6.5) and 8.6 (SD=4.7), respectively; this was a reduction of 30% (P=.001) and 22% (P=.003), respectively, in the mean. Conclusions: A significant reduction in BG was found in all groups, independent of the use frequency of the app. Better outcomes were found for T2D patients. A significant reduction in LBGI and HBGI was found in all groups, regardless of the use frequency of the app. LBGI and HBGI indices of both groups tend to have similar values after 6 months of app use.

  • Accuracy of Apple Watch Measurements of Heart Rate and Energy Expenditure in Patients with Cardiovascular Disease

    Date Submitted: Aug 9, 2018

    Open Peer Review Period: Aug 13, 2018 - Oct 8, 2018

    Background: Wrist-worn tracking devices such as the Apple Watch are becoming more and more integrated in healthcare. However, validation studies of these consumer devices remain scarce. Objective: Thi...

    Background: Wrist-worn tracking devices such as the Apple Watch are becoming more and more integrated in healthcare. However, validation studies of these consumer devices remain scarce. Objective: This study aimed to determine the accuracy of the Apple Watch in measuring heart rate (HR) and estimating energy expenditure (EE) during a cardiopulmonary exercise test (CPET) in patients with cardiovascular disease. Methods: Forty patients (mean age 61.9 +/- 15.2 yrs, 80% male) with cardiovascular disease (70% ischemic, 22.5% valvular, 7.5% other) completed a graded maximal CPET on a cycle ergometer while wearing an Apple Watch. A 12-lead electrocardiogram (ECG) was used as criterion for HR, indirect calorimetry was used as criterion for EE. HR was analysed at three levels of intensity (seated rest, HR1; moderate intensity, HR2; maximal performance, HR3) for 30 seconds. The EE of the entire test was used. Bias or mean difference (MD), standard deviation of difference (SDD), limits of agreement (LoA) and intraclass correlation coefficients (ICCs) were calculated. Bland-Altman plots and scatterplots were constructed. Results: SDD for HR1, HR2 and HR3 was 12.4, 16.2 and 12.0 beats/min respectively. Bias and LoA (lower, upper LoA) were 3.61 (-20.74, 27.96) for HR1, 0.91 (-30.82, 32.63) for HR2 and -1.82 (-25.27, 21.63) for HR3. The ICC was 0.729 (p<.001) for HR1, 0.828 (p<.001) for HR2 and 0.958 (p<.001) for HR3. Bland-Altman plots and scatterplots showed good correlation without systematic error when comparing Apple Watch with ECG measurements. SDD for EE was 17.5 kcal. Bias and LoA were 30.47 (-3.80, 64.74). The ICC for EE was 0.797 (p<.001). The Bland-Altman plot and a scatterplot directly comparing Apple Watch and indirect calorimetry showed systematic bias with an overestimation of EE by the Apple Watch. Conclusions: In patients with cardiovascular disease the Apple Watch measures HR with clinically acceptable accuracy during exercise. If confirmed, it might be considered safe to incorporate the Apple Watch in HR-guided training programs in the setting of cardiac rehabilitation. However, the Apple Watch systematically overestimates EE in this group of patients. Some caution might therefore be warranted when using the Apple Watch for measuring EE.

  • Towards Minimally Disruptive Medicine: Assessing the need for Mobile Healthcare (mHealthcare) in Monitoring the Diabetic Lower Extremity

    Date Submitted: Aug 8, 2018

    Open Peer Review Period: Aug 12, 2018 - Oct 7, 2018

    Background: Complications of the diabetic lower extremity often result when monitoring is infrequent, and often result in serious sequelae like amputation and even death. Objective: To develop an effe...

    Background: Complications of the diabetic lower extremity often result when monitoring is infrequent, and often result in serious sequelae like amputation and even death. Objective: To develop an effective solution to the problem of infrequent monitoring, we evaluated 1) the self-management routines of a group of diabetic patients in order to better understand the barriers to monitoring in this patient population, 2) patient and clinician opinion on the use of mobile healthcare (mHealth) in this space. Methods: Patients with diabetic foot ulcers (DFUs) in Toronto, Canada completed a 25-item questionnaire addressing their foot care practices, mobile phone use, and views on mHealth. Wound care clinicians across Canada were also surveyed using a 9-item questionnaire. Results: Of the 115 patients surveyed, 51.3% spend less than a minute checking their feet, and 15% of patients find it difficult to see their doctor or get to the hospital regularly. Mobile phone use was widespread in our cohort (80.4% of respondents). Of mobile phone users, 73.1% would use a device on their phone to help them check their feet. 242 clinicians completed the questionnaire, and only 3.5% of clinicians were familiar with mHealth. Importantly, 92% of clinicians expressed interest in using mHealth to monitor their patients between visits. Conclusions: Patient education/motivation and clinician training were identified as the major barriers to mHealth use in the diabetic lower extremity, which is a promising solution to the problem of infrequent monitoring.

  • High-fidelity prototyping for Mobile Electronic Data Collection Forms through design and user evaluation

    Date Submitted: Aug 7, 2018

    Open Peer Review Period: Aug 9, 2018 - Oct 4, 2018

    Background: Mobile data collection systems are often difficult to use, for non-technical or novice users. This can be attributed to the fact that, developers of such tools do not adequately involve en...

    Background: Mobile data collection systems are often difficult to use, for non-technical or novice users. This can be attributed to the fact that, developers of such tools do not adequately involve end-users in the design and development of product features and functions. This has led to products which seem obvious to the developers in their functions but not to the general users, creating a big usability gap. Objective: The main objective of this study was to assess the research assistants’ (end users) user experience of a high-fidelity prototype that was developed based on their design preferences using the group testing approach. We also sought to gain insight into the use of group testing approach in the design of generic mobile data collection systems. Methods: We developed an online high fidelity prototype for data collection forms between January and February 2018, using Axure RP8, and the prototype did not have any backend functionality. Thirty four (n=34) research assistants who were all involved in data collection on a maternal and child health project in Northern Uganda evaluated the high fidelity prototype in March 2018 based on the group testing approach by completing some tasks. A study tailored evaluation questionnaire (STEQ) comprising of 13 affirmative statements, coupled with the commonly used and validated System Usability Scale (SUS) were administered to evaluate the usability and user experience after interaction with the prototype. The STEQ evaluation was summarized using frequencies in an excel sheet where the evaluation statement with majority agreeing to it was taken as the most preferred option. The SUS scores were calculated based on whether the statement was positive (user selection minus 1) or negative (5 minus user selection). These were summed up and the score contributions multiplied by 2.5 to give the overall form usability from each participant. Results: The results gave an SUS average score of 67.5, which is marginally below the recommended average score of 68, depicting some levels of dissatisfaction. Results from the Study Tailored Evaluation Questionnaire (STEQ) indicated a 70% level of agreement with the affirmative evaluation statements, which shows a fair level of satisfaction with the forms. Notably, low scores were observed for readability of the content on the screen and the instructions indicating the data capture format being unclear. The study proves that the group testing approach is an appropriate technique for cases where software developers are unable to elicit user requirements for projects whose conceptualization is innovative, formative and evolving. Conclusions: Evaluating user design preferences as a part of user experience using the group testing approach is not a very common approach in the development of mobile data collection forms and yet this could be one way of tailoring design to the user needs so as to cater for the diversity in context and user groups especially in rural Africa. Using high fidelity prototyping turned out to be a feasible and affordable form development option. The adoption of design variations to clearly understand user design preferences cannot be under estimated. This may be more time-consuming compared to other approaches; however, the long-term benefits could lead to development of highly usable forms, increased data accuracy, and a pleasant user experience.

  • The Effects of Social Media and Mobile Health Apps for Pregnancy Care: A Meta-analysis

    Date Submitted: Aug 4, 2018

    Open Peer Review Period: Aug 9, 2018 - Oct 4, 2018

    Background: The use of social media and mobile health (mHealth) apps has been increasing in pregnancy care. However, the effectiveness of these interventions is still unclear. Objective: We conducted...

    Background: The use of social media and mobile health (mHealth) apps has been increasing in pregnancy care. However, the effectiveness of these interventions is still unclear. Objective: We conducted a meta-analysis to examine the effectiveness of these interventions with regard to different health outcomes of pregnant and postpartum women; and to investigate the characteristics and components of interventions that may affect program effectiveness. Methods: We performed a comprehensive literature search of major electronic databases and reference sections of related reviews and eligible studies. A random effects model was used to calculate the effect size. Results: Fifteen RCT studies published in and before June 2018 that met the inclusion criteria were included in the meta-analysis. The interventions were effective in promoting maternal physical health, including weight management, gestational diabetes mellitus control, and asthma control, with a moderate to large effect size (d = 0.72). Large effect sizes were also found for improving maternal mental health (d = 0.84) and knowledge about pregnancy (d = 0.80). Weight control interventions using wearable devices were more effective. Conclusions: The social media and mHealth apps have the potential to be widely used in improving maternal well-being. More large-scale clinical trials focusing on different health outcomes are suggested for future studies.