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Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.
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, and Science Citation Index Expanded (SCIE), and in June 2017 received an impressive inaugural Impact Factor of 4.636, which ranks the journal #2 (behind JMIR) out of over 20 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.
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Background: Digital health – mobile health, health information technology, wearable devices, telehealth, and personalized medicine – is an advancing phenomenon in the healthcare systems of modern...
Background: Digital health – mobile health, health information technology, wearable devices, telehealth, and personalized medicine – is an advancing phenomenon in the healthcare systems of modern societies. Epidemiology has provided frameworks to support studies which utilize, evaluate, focus on, or benefit from digital health technologies in their methodology. Objective: Our study systematically evaluates the articles published by major epidemiology journals, with focus on or utilization of digital health technologies, to quantify their trends and visibility. Methods: All 27 PubMed-indexed, epidemiology journals were searched between 2006 and 2016, to find articles in English, in which the authors focused on, utilized, or discussed at least one digital health technology in the design, methodology, or conduct of their study. Additionally, a bibliometric analysis was conducted using the freely-available, Profiles Research Networking Software by the Harvard Clinical and Translational Science Center. Results: Out of 58,251 articles published on or using digital health technologies, 368 articles (0.63%) were published by 24 epidemiology journals (307 articles [0.53%] in the past decade), with ten-year average citation per article of 3.44. More than two-third (210 articles; 68.4%) were published by five major epidemiology journals, mainly by Pharmacoepidemiol Drug Saf, with 98 published articles (31.9%). Conclusions: The reflection of different digital health technologies in epidemiology journals increased dramatically over the past decade and Pharmacoepidemiol Drug Saf was the leading major epidemiology journal in this endeavor. For improving the share of epidemiology journals in publishing literature around digital health technologies, more regular bibliographic and bibliometric analyses would be needed.
Background: Heavy alcohol use is prevalent among young adults and may contribute to obesity. However, measurement tools for assessing caloric intake from alcohol are limited and rely on self-report, w...
Background: Heavy alcohol use is prevalent among young adults and may contribute to obesity. However, measurement tools for assessing caloric intake from alcohol are limited and rely on self-report, which is prone to biases. Objective: The purpose of the pilot study was to conduct feasibility testing of SmartIntake®, a photo-based smartphone app, to assess alcohol use among young adults. Aims consisted of 1) quantifying the ability of SmartIntake® to capture drinking behavior; 2) assessing app usability with the Computer System Usability Questionnaire (CSUQ); 3) conducting a qualitative interview; and 4) comparing preference, compliance, and alcohol use estimates (calories, grams per drinking episode) between SmartIntake® and online diet recalls that participants completed for a parent study. Methods: College students (N=15) who endorsed a pattern of heavy drinking were recruited from a larger study examining the impact of drinking on weight. Participants used SmartIntake® to send photographs of all alcohol and food intake over a three-day period, and then completed a follow up interview and the CSUQ. CSUQ items range from 1-7, with lower scores indicating greater usability. Total number of drinking occasions was determined by adding the number of drinking occasions captured by SmartIntake® plus the number of drinking occasions participants reported that they missed capturing. Compliance was defined by the number of days participants provided food/beverage photo data through the app, or the number of diet recalls completed. Results: The SmartIntake® app captured 13 of 15 (87%) drinking occasions. Participants rated the app as highly usable in the CSUQ (M= 2.28). Most participants (93%) preferred using SmartIntake® vs. recalls and compliance was significantly higher with SmartIntake® than recalls (93% vs 78%; P= .04). Alcohol grams and calories per drinking occasion were not significantly different between the two methods (P values range .25-.99); however triple the number of participants submitted alcohol reports with SmartIntake® compared to the diet recalls (SmartIntake® 9/15 vs recalls 3/15; P=.06). Conclusions: SmartIntake® was well accepted by college students who drink heavily and captured most drinking occasions. Participants had higher compliance with SmartIntake® compared to diet recalls and triple the number of participants reported alcohol use with SmartIntake®, suggesting this method may be well suited to assessing alcohol use in young adults.
Background: Mobile health (mHealth) technology provides innovative ways to deliver weight loss interventions. Understanding how engagement in mHealth interventions relates to weight change may help de...
Background: Mobile health (mHealth) technology provides innovative ways to deliver weight loss interventions. Understanding how engagement in mHealth interventions relates to weight change may help develop more effective intervention strategies. Objective: To examine 1) patterns of participant engagement overall and in key intervention features within the interventions of the Cell Phone Intervention For You (CITY) clinical trial, 2) associations of engagement with weight change, and 3) characteristics of participants that are related to engagement. Methods: The CITY trial tested two 24-month behavioral weight loss interventions. One was delivered with a smartphone application (app) (Cell Phone; CP) that contained 24 features (weighing, tracking of diets, etc.) and included regular prompting by the app in pre-determined frequency and forms. The other intervention was delivered by a coach via monthly phone calls (Personal Coaching; PC) supplemented with limited app features (18 total) and without any prompting by the app. Engagement was assessed by calculating the percentage of days each app feature was used and the frequency of usage. Engagement was also examined across four weight change categories: gained (≥2%), stable (±2%), mild loss (≥2% to <5%), and greater loss (≥5%). Results: Data from 122 CP and 120 PC participants were analyzed. Usage of the app features was highest during month 1 for both groups; thereafter, usage dropped substantially and continuously until the end of the study. During the first six months, mean percentage of days any app feature was used was higher for the CP (74.2%, standard deviation [SD], 20.1) than for the PC group (48.9%, SD, 22.4). The CP group used the app features an average of 5.3 times/day [SD, 3.1], while the PC used them 1.7 times/day [SD, 1.2]. Similarly, when the self-weighing feature was examined alone, CP self-weighed more than PC (57.1% days [SD, 23.7] vs. 32.9% [23.3]). Further, percentage of days any app feature was used, number of app usages/day and percentage of days self-weighed all showed significant differences across the four weight categories for both CP and PC. Pearson correlation coefficients showed a negative linear association between weight change and percentage of days any app feature was used (CP: r=-0.213; PC: r=-0.319), number of app usages/day (CP:r=-0.264; PC:r=-0.308), and percentage of days self-weighed (CP:r=-0.297; PC:r=-0.354). Conclusions: Engagement in CITY intervention was associated with weight loss during the first six months. Nevertheless, engagement dropped substantially early on for most intervention features. Prompting may be helpful initially. More flexible and less-intrusive prompting strategies may be needed during different stages of an intervention to increase or sustain engagement. Future studies should explore the motivations for engagement and non-engagement in order to design effective intervention. Clinical Trial: NCT01092364
This manuscript needs more reviewersPeer-Review Me
Background: Amid considerable community concern about prevalence and harms associated with crystal methamphetamine use, increased use of smartphones to access health information and a growing number o...
Background: Amid considerable community concern about prevalence and harms associated with crystal methamphetamine use, increased use of smartphones to access health information and a growing number of available smartphone applications (‘apps’) related to crystal methamphetamine (ice), no previous reviews have examined content and quality of these apps. Objective: This present study aimed to systematically review existing apps in the iTunes and Google Play Stores to determine the existence, composition and quality of educational smartphone apps about methamphetamines, including ice. Methods: The iTunes and Google Play Stores were systematically searched in April 2017 for iOS Apple and Android apps, respectively. English-language apps that provided educational content or information about methamphetamine were eligible for inclusion. Eligible apps were downloaded and independently evaluated for quality by two reviewers using the Mobile Application Rating Scale (MARS). Results: A total of 2205 apps were initially identified, of which 18 were eligible and rated using the MARS. The mean MARS quality total score for all rated apps was 3.0 (SD = 0.6) indicating poor to acceptable quality. Overall mean scores were highest for functionality (x ̅=4.0; SD=0.5) and lowest for engagement (x ̅=2.3, SD=0.7). Conclusions: The present study demonstrated a shortage of high-quality educational and engaging smartphone apps specifically related to methamphetamine. The findings from this review highlight a need for further development of engaging and evidence-based apps that provide educational information about crystal methamphetamine.
This manuscript needs more reviewersPeer-Review Me
Background: ScreenMen, a mobile web-app which aimed to improve health screening uptake in men was developed based on theories, evidence and needs. Objective: This study aimed to evaluate ScreenMen for...
Background: ScreenMen, a mobile web-app which aimed to improve health screening uptake in men was developed based on theories, evidence and needs. Objective: This study aimed to evaluate ScreenMen for its utility and usability with men from the community. Methods: This study used a mixed-method approach. Healthy men who are working in a banking institution were recruited to participant in this study. They were purposively sampled according to job position, age, education level and screening status. Men were asked to use ScreenMen independently while the screen activities are being recorded. Once completed, retrospective think aloud with playback was conducted with men to obtain their feedback. They were asked to answer the System Usability Scale. Intention to undergo screening pre- and post- intervention were also measured. Qualitative data were analysed using a framework approach and followed by thematic analysis. For quantitative data obtained, the mean SUS score and change in intention to screening were calculated and analyses using McNemar test. Results: Twenty-four men participated in this study. Based on the qualitative data, men found ScreenMen useful as they could learn more about their health risks and screening. They found ScreenMen convenient to use and might trigger men to undergo screening. In terms of usability, men thought that ScreenMen was user-friendly and easy to understand. The key revision done on utility was the addition of a reminder function while for usability, the revisions done were in terms of attracting and gaining users trust; improving learnability; and making ScreenMen usable to all types of users. To attract men to use it, ScreenMen was introduced to users in terms of ‘improving health’ instead of ‘going for screening’. Another important revision made was emphasising the screening tests the users do not need instead of just informing them the screening tests they need. A ‘Quick Assessment Mode’ was also added for users with limited attention span. The quantitative data showed that eight (34.8%) out of 23 men planned to attend screening earlier than intended after using the ScreenMen. Out of 12 men who were in pre-contemplation stage, 4 (33.3%) changed to either contemplation or preparation stage after using ScreenMen. In terms of usability, the SUS score of 76.4 indicated that ScreenMen had good usability. Conclusions: This study showed that ScreenMen was acceptable to men in terms of its utility and usability. The preliminary data suggested that ScreenMen might increase men’s intention to undergo screening. This paper also presented key lessons learnt from the beta testing, which would useful for public health experts and researchers when developing a user-centered mobile web-app. Clinical Trial: Not applicable
Background: Promising first results for Kaia, a mobile app digitalizing multidisciplinary rehabilitation for low back pain, were recently published. It remained unclear, whether the implementation of...