自引率: 13.1%
被引量: 4226
通过率: 暂无数据
审稿周期: 1
版面费用: 暂无数据
国人发稿量: 12
投稿须知/期刊简介:
Focus and ScopeJMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a newer spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2015: 4.532). JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and we are expecting the first impact factor for JMU in 2017 which will be at least 2.84. 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 even faster and has a broader scope with including papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research. In addition to peer-reviewing paper submissions by researchers, JMIR mHealth and uHealth offers peer-review of medical apps itself (we will write and publish a peer-review report for you - please submit your proposal at http://tinyurl.com/appsform). JMIR mHealth and uHealth journal 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 (http://www.jmir.org/issue/current).We are looking for papers covering for example the following themes:Ubiquitous Health (uHealth)mHealth for Data Collection and ResearchUsability and user perceptions of mHealthmHealth in the Developing World and for Global HealthmHealth in a Clinical SettingmHealth for Symptom and Disease MonitoringmHealth for Wellness, Behavior Change and PreventionmHealth for ScreeningText-messaging (SMS)-Based InterventionsDesign and Formative Evaluation of Mobile AppsSecurity and Privacy of mHealth and uHealthQuality Evaluation and Descriptive Analysis of Multiple Existing Mobile Apps mHealth for Treatment AdherenceUse and User Demographics of mHealthmHealth for Telemedicine and HomecaremHealth for Patient EducationmHealth in Medical Education and TrainingEvaluation and Research Methodology for mHealthWearable Devices and SensorsFitness Trackers and Smart Pedometers/AccelerometersGoogle Glass and Augmented Reality ApplicationsProduct Reviews and Tutorials in mHealth
期刊描述简介:
Focus and Scope JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a newer spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2015: 4.532). JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and we are expecting the first impact factor for JMU in 2017 which will be at least 2.84. 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 even faster and has a broader scope with including papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research. In addition to peer-reviewing paper submissions by researchers, JMIR mHealth and uHealth offers peer-review of medical apps itself. JMIR mHealth and uHealth journal 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 . We are looking for papers covering for example the following themes: Ubiquitous Health (uHealth) mHealth for Data Collection and Research Usability and user perceptions of mHealth mHealth in the Developing World and for Global Health mHealth in a Clinical Setting mHealth for Symptom and Disease Monitoring mHealth for Wellness, Behavior Change and Prevention mHealth for Screening Text-messaging (SMS)-Based Interventions Design and Formative Evaluation of Mobile Apps Security and Privacy of mHealth and uHealth Quality Evaluation and Descriptive Analysis of Multiple Existing Mobile Apps mHealth for Treatment Adherence Use and User Demographics of mHealth mHealth for Telemedicine and Homecare mHealth for Patient Education mHealth in Medical Education and Training Evaluation and Research Methodology for mHealth Wearable Devices and Sensors Fitness Trackers and Smart Pedometers/Accelerometers Google Glass and Augmented Reality Applications Product Reviews and Tutorials in mHealth
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The Use of Noncommercial Parent-Focused mHealth Interventions for Behavioral Problems in Youth: Systematic Review.
被引量：- 发表：1970
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Evaluating the Adoption of mHealth Technologies by Community Health Workers to Improve the Use of Maternal Health Services in Sub-Saharan Africa: Systematic Review.
被引量：- 发表：1970
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The Impact of Air Pollution Information on Individuals' Exercise Behavior: Empirical Study Using Wearable and Mobile Devices Data.
Physical exercise and exposure to air pollution have counteracting effects on individuals' health outcomes. Knowledge on individuals' real-time exercise behavior response to different pollution information sources remains inadequate. This study aims to examine the extent to which individuals avoid polluted air during exercise activities in response to different air pollution information sources. We used data on individuals' exercise behaviors captured by wearable and mobile devices in 83 Chinese cities over a 2-year time span. In our data set, 35.99% (5896/16,379) of individuals were female and 64% (10,483/16,379) were male, and their ages predominantly ranged from 18 to 50 years. We further augmented the exercise behavior data with air pollution information that included city-hourly level measures of the Air Quality Index and particulate matter 2.5 concentration (in µg/m3), and weather data that include city-hourly level measures of air temperature (ºC), dew point (ºC), wind speed (m/s), and wind direction (degrees). We used a linear panel fixed effect model to estimate individuals' exercise-aversion behaviors (ie, running exercise distance at individual-hour, city-hour, or city-day levels) and conducted robustness checks using the endogenous treatment effect model and regression discontinuity method. We examined if alternative air pollution information sources could moderate (ie, substitute or complement) the role of mainstream air pollution indicators. Our results show that individuals exhibit a reduction of running exercise behaviors by about 0.50 km (or 7.5%; P<.001) during instances of moderate to severe air pollution, and there is no evidence of reduced distances in instances of light air pollution. Furthermore, individuals' exercise-aversion behaviors in response to mainstream air pollution information are heightened by different alternative information sources, such as social connections and social media user-generated content about air pollution. Our results highlight the complementary role of different alternative information sources of air pollution in inducing individuals' aversion behaviors and the importance of using different information channels to increase public awareness beyond official air pollution alerts.
被引量：- 发表：1970
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Real-World Outcomes of a Digital Behavioral Coaching Intervention to Improve Employee Health Status: Retrospective Observational Study.
被引量：- 发表：1970
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Efficacy of the mHealth-Based Exercise Intervention re.flex for Patients With Knee Osteoarthritis: Pilot Randomized Controlled Trial.
Exercise therapy is recommended by international guidelines as a core treatment for patients with knee osteoarthritis. However, there is a significant gap between recommendations and practice in health care. Digital exercise apps are promising to help solve this undersupply. This study aims to evaluate the efficacy of a 12-week fully automated app-based exercise intervention with and without a supporting knee brace on health-related outcomes, performance measures, and adherence in patients with knee osteoarthritis. This closed user group trial included participants with moderate to severe unicondylar painful knee osteoarthritis. Randomization was 1:1:2 into an intervention group (IG) with 2 subgroups (app-based training [IG A] and app-based training and a supportive knee brace [IG AB]) and a control group (CG). The intervention included a 12-week home exercise program with 3 sessions per week. Instructions for the exercises were given via the app and monitored using 2 accelerometers placed below and above the affected knee joint. Participants in the CG did not receive any study intervention but were allowed to make use of usual care. Osteoarthritis-specific pain (Knee Injury and Osteoarthritis Outcome Score) was defined as the primary outcome, and secondary outcomes included all other Knee Injury and Osteoarthritis Outcome Score subscales, general health-related quality of life (Veterans RAND 12-item Health Survey), psychological measures (eg, exercise self-efficacy), performance measures (strength and postural control), and the monitoring of adherence and safety. Outcomes were assessed at baseline and after 12 weeks. Intervention effects were calculated using baseline-adjusted analysis of covariance for the joint comparison of IG A and IG AB versus the CG using a per-protocol approach. Subgroup analyses were conducted for each IG separately. A total of 61 participants were included (IG: n=30, 49%; CG: n=31, 51%; male: n=31, 51%; female: n=30, 49%; mean age 62.9, SD 8.5 years; mean BMI 27.7, SD 4.5 kg/m2). Analysis revealed statistically significant effects in favor of the IG for pain reduction (P<.001; effect size [ES]=0.76), improvements in physical function (P<.001; ES=0.64), improvements in symptoms (P=.01; ES=0.53), improvements in sport and recreation activities (P=.02; ES=0.47), improvements in knee-related quality of life (P<.001; ES=0.76), and improvements in the physical component of general health-related quality of life (P<.001; ES=0.74). Mean differences ranged from 6.0 to 13.2 points (scale range 0-100). ESs indicated small to medium effects. No effects were found for psychological and performance measures. Participants adhered to 92.5% (899/972) of all scheduled exercise sessions. Individuals with knee osteoarthritis undergoing a 12-week sensor-assisted app-based exercise intervention with or without an additional knee brace experienced clinically meaningful treatment effects regarding pain relief and improvements in physical function as well as other osteoarthritis-specific concerns compared to controls. German Clinical Trials Register (DRKS) DRKS00023269; https://drks.de/search/de/trial/DRKS00023269.
被引量：- 发表：1970
