JMIR mHealth and uHealth

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

Editor-in-Chief:

Lorraine R. Buis, PhD, MSI, Associate Professor, Department of Family Medicine, University of Michigan, USA


Impact Factor 4.31

Recent Articles

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Fitness Trackers and Smart Pedometers/Accelerometers

Wearable activity trackers are popular devices used to motivate behavior change. Wearable activity trackers are especially beneficial for encouraging light physical activity such as walking, which is an ideal behavior for older adults or individuals who cannot be physically active at moderate and vigorous levels. A common problem is that people do not continue to use these wearable devices, with initial behavioral change gains eroding as people disengage. Limited research is available regarding the continued use of wearable activity trackers. The habit formation literature may provide insights into the long-term use of wearables and other health informatics devices.

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Fitness Trackers and Smart Pedometers/Accelerometers

Continuous tracking of ambulatory activity in real-world settings using step activity monitors has many potential uses. However, feasibility, accuracy, and correlation with performance measures in stroke patients have not been well-established.

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Reviews

It is unclear why some physical activity (PA) mobile health (mHealth) interventions successfully promote PA whereas others do not. One possible explanation is the variety in PA mHealth interventions—not only do interventions differ in the selection of persuasive strategies but also the design and implementation of persuasive strategies can vary. However, limited studies have examined the different designs and technical implementations of strategies or explored if they indeed influenced the effectiveness of the intervention.

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Design and Formative Evaluation of Mobile Apps

Substance use among adolescents and emerging adults continues to be an important public health problem associated with morbidity and mortality. Mobile health (mHealth) provides a promising approach to deliver just-in-time adaptive interventions (JITAIs) to prevent escalation of use and substance use–related consequences.

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Text-messaging (SMS, WeChat etc)-Based Interventions

Digital health usability assessments can help explain how well mobile health (mHealth) apps targeting young people with sexual and reproductive health (SRH) information performed and whether the intended purpose was achieved. However, few digital health assessments have been conducted to evaluate young people’s perceptions regarding mHealth system interactions and content relevance on a wide range of SRH topics. In addition, the majority of randomized controlled trials (RCTs) have focused on push messaging platforms; therefore, the mHealth field lacks sufficient RCTs investigating on-demand mHealth SRH platforms.

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mHealth for Health Administration

Integrated care can generate health and social care efficiencies through the defragmentation of care and adoption of patient-centered preventive models. eHealth can be a key enabling technology for integrated care.

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mHealth for Wellness, Behavior Change and Prevention

Syrian refugees residing in Germany often develop posttraumatic stress as a result of the Syrian civil war, their escape, and postmigration stressors. At the same time, there is a lack of adequate treatment options. The smartphone-based app Sanadak was developed to provide cognitive behavioral therapy–based self-help in the Arabic language for Syrian refugees with posttraumatic stress.

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mHealth for Wellness, Behavior Change and Prevention

Technological advancements have enabled nutrient estimation by smartphone apps such as goFOOD. This is an artificial intelligence–based smartphone system, which uses food images or video captured by the user as input and then translates these into estimates of nutrient content. The quality of the data is highly dependent on the images the user records. This can lead to a major loss of data and impaired quality. Instead of removing these data from the study, in-depth analysis is needed to explore common mistakes and to use them for further improvement of automated apps for nutrition assessment.

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mHealth in the Developing World/LMICs, Underserved Communities, and for Global Health

Mobile phones may help young people (YP) access health information and support health service engagement. However, in low-income settings there is limited knowledge on YP’s phone and internet access to inform the feasibility of implementing digital health interventions.

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Ecological Momentary Assessment (EMA)

Older adults who experience pain are more likely to reduce their community and life-space mobility (ie, the usual range of places in an environment in which a person engages). However, there is significant day-to-day variability in pain experiences that offer unique insights into the consequences on life-space mobility, which are not well understood. This variability is complex and cannot be captured with traditional recall-based pain surveys. As a solution, ecological momentary assessments record repeated pain experiences throughout the day in the natural environment.

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mHealth for Wellness, Behavior Change and Prevention

Many older adults choose and prefer to exercise at home, but to attain the greatest benefits, the correct type and dose of exercise should be prescribed and adherence maintained. Advances in digital health technologies now provide the opportunity for exercise professionals to deliver and monitor personalized, evidence-based exercise programs to anyone at any time.

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Articles Open for Peer-Review

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