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 5.0

JMIR mHealth and uHealth (JMU, ISSN 2291-5222; Impact Factor: 5.0) is a leading peer-reviewed journal and one of the flagship journals of JMIR Publications. JMU has been published since 2013 and was the first mhealth journal indexed in PubMed. In June 2023, JMU received a Journal Impact Factor™ from Clarivate of 5.0 (5-year Journal Impact Factor™: 5.7) and continues to be a Q1 journal in the category of ‘Healthcare Sciences and Services.’ It is indexed in all major literature indices, including MEDLINE, PubMedPubMed Central, Scopus, Psycinfo, SCIE, JCR, EBSCO/EBSCO Essentials, DOAJ, GoOA and others.

JMU 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, JMU 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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Evaluation and Research Methodology for mHealth

Mobile health (mHealth) interventions that promote healthy behaviors or mindsets are a promising avenue to reach vulnerable or at-risk groups. In designing such mHealth interventions, authentic representation of intended participants is essential. The COVID-19 pandemic served as a catalyst for innovation in remote user-centered research methods. The capability of such research methods to effectively engage with vulnerable participants requires inquiry into practice to determine the suitability and appropriateness of these methods.

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

Hypertension, a key modifiable risk factor for cardiovascular disease, is more prevalent among Black and low-income individuals. To address this health disparity, leveraging safety-net Emergency Departments for scalable mobile health (mHealth) interventions, specifically utilizing text messaging for self-measured blood pressure (SMBP) monitoring, presents a promising strategy. This study investigates patterns of engagement, associated factors, and the impact of engagement on lowering blood pressure in an underserved population.

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mHealth for Wellness, Behavior Change and Prevention

Depression acts as a significant obstacle to the overall well-being of individuals. Given the significant consequences, timely recognition and proactive steps to manage symptoms of depression become essential. Such actions not only reduce personal distress but also play a crucial role in reducing its far-reaching impact on society as a whole.

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mHealth for Data Collection and Research

Chronic pain affects approximately 30% of the general population, severely degrades quality of life and professional life, and leads to additional health care costs. Moreover, the medical follow-up of patients with chronic pain remains complex and provides only fragmentary data on painful daily experiences. This situation makes the management of patients with chronic pain less than optimal and may partly explain the lack of effectiveness of current therapies. Real-life monitoring of subjective and objective markers of chronic pain using mobile health (mHealth) programs could better characterize patients, chronic pain, pain medications, and daily impact to help medical management.

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Usability of Apps and User Perceptions of mHealth

Different kinds of mobile apps are used to promote communications between patients and doctors. Studies have investigated patients’ mobile app adoption behavior; however, they offer limited insights into doctors’ personal preferences among a variety of choices of mobile apps.

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mHealth for Symptom and Disease Monitoring, Chronic Disease Management

In emergency departments (EDs), triage nurses are under tremendous daily pressure to rapidly assess the acuity level of patients and log the collected information into computers. With self-service technologies, patients could complete data entry on their own, allowing nurses to focus on higher-order tasks. Kiosks are a popular working example of such self-service technologies; however, placing a sufficient number of unwieldy and fixed machines demands a spatial change in the greeting area and affects pretriage flow. Mobile technologies could offer a solution to these issues.

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

Young women often face substantial psychological challenges in the initial years following cancer diagnosis, leading to a comparatively lower quality of life than older survivors. While mobile apps have emerged as potential interventions, their effectiveness remains inconclusive due to the diversity in intervention types and variation in follow-up periods. Furthermore, there is a particular dearth of evidence regarding the efficacy of these apps’ intelligent features in addressing psychological distress with these apps.

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mHealth for Symptom and Disease Monitoring, Chronic Disease Management

Due to the aging of the population, the prevalence of aortic valve stenosis will increase dramatically in upcoming years. Consequently Transcatheter Aortic Valve Implantation (TAVI) procedures will also expand worldwide. Optimal selection of patients who benefit with improved symptoms and prognosis is key since TAVI is not without risk. Currently we are not able to adequately predict functional outcome after TAVI. Quality of life measurement tools and traditional functional assessment tests do not always agree and can depend on factors unrelated to heart disease. Activity tracking using wearable devices might provide a more comprehensive assessment.

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mHealth for Treatment Adherence

There are no recent studies comparing the compliance rates of both patients and observers in tuberculosis treatment between the video-observed therapy (VOT) and directly observed therapy (DOT) programs.

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Wearables and MHealth Reviews

Unaddressed early-stage mental health issues, including stress, anxiety, and mild depression, can become a burden for individuals in the long term. Digital phenotyping involves capturing continuous behavioral data via digital smartphone devices to monitor human behavior and can potentially identify milder symptoms before they become serious.

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Economic Evaluations of mHealth Programs and Infrastructures

Depressive disorder and type 2 diabetes mellitus (T2DM) are prevalent in primary care (PC). Pharmacological treatment, despite controversy, is commonly chosen due to resource limitations and difficulties in accessing face-to-face interventions. Depression significantly impacts various aspects of a person’s life, affecting adherence to medical prescriptions and glycemic control and leading to future complications and increased health care costs. To address these challenges, information and communication technologies (eg, eHealth) have been introduced, showing promise in improving treatment continuity and accessibility. However, while eHealth programs have demonstrated effectiveness in alleviating depressive symptoms, evidence regarding glycemic control remains inconclusive. This randomized controlled trial aimed to test the efficacy of a low-intensity psychological intervention via a web app for mild-moderate depressive symptoms in individuals with T2DM compared with treatment as usual (TAU) in PC.

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mHealth for Treatment Adherence

Medication nonadherence remains a significant health and economic burden in many high-income countries. Emerging smartphone interventions have started to use features such as gamification and financial incentives with varying degrees of effectiveness on medication adherence and health outcomes. A more consistent approach to applying these features, informed by patient perspectives, may result in more predictable and beneficial results from this type of intervention.

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Preprints Open for Peer-Review

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