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 5.4 CiteScore 12.6

JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a leading peer-reviewed journal and one of the flagship journals of JMIR Publications. JMIR mHealth and uHealth has been published since 2013 and was the first mhealth journal indexed in PubMed. In June 2024, JMIR mHealth and uHealth received a Journal Impact Factor™ from Clarivate of 5.4 (5-year Journal Impact Factor™: 5.6) and received a CiteScore of 12.6, placing it in the 90th percentile (#13 of 138) as a Q1 journal in the field of Health Informatics. It is indexed in all major literature indices, including MEDLINE, PubMedPubMed Central, Scopus, Psycinfo, SCIE, JCR, EBSCO/EBSCO Essentials, DOAJ, GoOA and others.

JMIR mHealth and uHealth focuses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics. 

The journal adheres to rigorous quality standards, involving a rapid and thorough peer-review process, professional copyediting, and professional production of PDF, XHTML, and XML proofs.

Like all JMIR journals, JMIR mHealth and uHealth encourages Open Science principles and strongly encourages the publication of a protocol before data collection. Authors who have published a protocol in JMIR Research Protocols get a discount of 20% on the Article Processing Fee when publishing a subsequent results paper in any JMIR journal.

Recent Articles

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

Directly observed therapy (DOT) is the standard method for monitoring adherence to tuberculosis (TB) treatment. However, implementing DOT poses challenges for both patients and providers due to limited financial and human resources. Increasing evidence suggests that emerging digital adherence technologies, such as video directly observed therapy (VDOT), can serve as viable alternatives.

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mHealth for Wellness, Behavior Change and Prevention

Nondaily smoking is a widespread and increasingly prevalent pattern of use. To date, no effective treatment approach for nondaily smoking has been identified.

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mHealth for Wellness, Behavior Change and Prevention

Gratitude interventions are used to cultivate a sense of gratitude for life and others. There have been mixed results of the efficacy of gratitude interventions’ effect on psychological well-being with a variety of populations and methodologies.

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mHealth for Symptom and Disease Monitoring, Chronic Disease Management

Depression and chronic pain are commonly comorbid, mutually reinforcing, and debilitating. Emerging approaches to mobile behavioral healthcare (mHealth) promise to improve outcomes for patients with comorbid depression and chronic pain by integrating with existing care models to bolster support and continuity between clinical visits; however, the evidence base supporting the use of mHealth to augment care for this patient population is limited.

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Wearable Devices and Sensors

Wrist-worn photoplethysmography (PPG) sensors allows continuous heart rate (HR) measurement without inconveniences of wearing a chest belt. While green light PPG technology reduces HR measurement motion artifacts, only a limited number of studies investigated the reliability and accuracy of wearables in non-laboratory controlled conditions with actual specific and various physical activity movements.

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mHealth for Screening

Mobile phone SMS text message reminders have shown moderate effects in improving participation rates in ongoing colorectal cancer screening programs.

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Quality Evaluation and Descriptive Analysis/Reviews of Multiple Existing Mobile Apps

The use of mobile technology to meet health needs, widely referred to as mobile health (mHealth), has played a critical role in providing self-management support for chronic health conditions. However, despite its potential benefits, mHealth technologies such as self-management support apps for spinal cord injury (SCI) have received little research attention, and an understanding of their public availability is lacking. Therefore, an overview of these apps is needed to complement findings from the literature for a complete understanding of mHealth self-management support tools for SCI to support the selection and improvement of existing apps and the development of new ones.

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Design and Formative Evaluation of Mobile Apps

Obsessive-compulsive disorder (OCD) is the third most prevalent mental health disorder in Singapore, with a high degree of burden and large treatment gaps. Self-guided programs on mobile apps are accessible and affordable interventions, with the potential to address subclinical OCD before symptoms escalate.

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

Mobile Health (mHealth) interventions have the potential to improve health outcomes in low- and middle-income countries (LMIC) by aiding health workers to strengthen service delivery, and patients and communities to manage and prevent diseases. It is crucial to understand how best to implement mHealth within already burdened health services to maximally improve health outcomes and sustain the intervention in LMIC.

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mHealth for Treatment Adherence

Pre-exposure prophylaxis (PrEP) is an effective strategy to reduce the risk of HIV infection. However, the efficacy of PrEP is highly dependent on adherence. Meanwhile, adherence changes over time, making it difficult to manage effectively.

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mHealth for Wellness, Behavior Change and Prevention

Smartphone apps and wearable activity trackers are increasingly recognized for their potential to promote physical activity (PA). While studies suggest that the use of commercial mobile health tools is associated with higher PA levels, most existing evidence is cross-sectional, leaving a gap in longitudinal data.

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Ecological Momentary Assessment (EMA)

Adolescence is a period characterized by an increased susceptibility to developing risky alcohol consumption habits. This susceptibility can be influenced by social and situational factors encountered in daily life, which, in conjunction with emotions and thoughts, contribute to behavioral patterns related to alcohol use even in the early stages of alcohol experimentation, when initial experiences with alcohol are formed, and regular consumption is still evolving.

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