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 for Symptom and Disease Monitoring, Chronic Disease Management

The use of digital interventions by patients for remote monitoring and management of health and disease is increasing. This observational study examined the feasibility, use, and safety of a digital smartphone app for routine monitoring of blood pressure (BP), medication, and symptoms of COVID-19 during the COVID-19 pandemic.

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Wearables and MHealth Reviews

The use of Smart technology in the management of all forms of diabetes mellitus has grown significantly in the past ten years. Technologies such as the SmartWatch have been proposed as a method of assisting in the monitoring of blood glucose levels as well as other alert prompts such as medication adherence and daily physical activity targets. These important outcomes reach across all forms of diabetes and have the potential to increase compliance of self-monitoring with the aim of improving long term outcomes such as HbA1c.

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Digital Biomarkers and Digital Phenotyping

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in school-aged children. The lack of objective biomarkers for ADHD often results in missed diagnoses or misdiagnoses, which lead to inappropriate or delayed interventions. Eye-tracking technology provides an objective method to assess children’s neuropsychological behavior.

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Ubiquitous Health (uHealth)

Living with a diagnosis of dementia can involve managing certain behavioural and psychological symptoms. Alongside cognitive decline, this cohort express a suppression in melatonin production which can negatively influence their alignment of sleep/wake timings with the 24 hour day/night cycle. As a result, their circadian rhythms become disrupted. Since daylight has the capacity to stimulate the circadian rhythm and humans spend approximately 90% of their time indoors, research has shifted towards the use of indoor lighting to achieve this same effect. This type of lighting is programmed in a daylight-simulating manner; mimicking the spectral changes of the sun throughout the day. As such, this paper focuses on the use of a dynamic lighting and sensing technology used to support the circadian rhythm, behavioural and psychological symptoms and wellbeing of people living with dementia.

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mHealth for Wellness, Behavior Change and Prevention

The increasing prevalence of sedentary lifestyles has prompted the development of innovative public health interventions, such as smartphone applications that deliver personalised exercise programs. The widespread availability of mobile technologies (e.g., smartphone apps and wearable activity trackers) provide a cost-effective, scalable way to remotely delivering personalised exercise programs to users. Utilising machine learning, specifically reinforcement learning (RL), may enhance user engagement and effectiveness of these programs by tailoring them to individual preferences and needs.

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mHealth in a Clinical Setting

Technological advances allow for recording and sharing health-related data in a patient-centric way using smartphones and wearables. Secure sharing of such patient-generated data with physicians would enable close management of individual health trajectories, monitoring of risk factors, and asynchronous feedback. However, most remote patient monitoring (RPM) systems currently available are not fully integrated into hospital IT systems or lack a patient-centric design.

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

Maternal mortality remains a persistent challenge in low- and middle-income countries, where evidence-based interventions of obstetric triage and prehospital communication remain sparse. There is limited implementation evidence for technology-based approaches to improve obstetric care in such contexts. Liberia struggles with maternal mortality, particularly in rural areas where deaths are attributable to delays from absent triage and interfacility communication. We implemented a Mobile Obstetric Referral Emergency System (MORES) in rural Bong County to improve prehospital transfer, health worker attentiveness, and patient care for critical obstetric patients. MORES consisted of triage training and a 2-way, templated WhatsApp communication system to reduce delays among patients transferred from rural health facilities (RHF) to hospitals.

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Fitness Trackers and Smart Pedometers/Accelerometers

Consumer-based wearables are becoming more popular and provide opportunities to track individual’s clinical parameters remotely. However, literature about their criterion and known groups validity is scarce.

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Wearable Devices and Sensors

ViSi Mobile has the capability of monitoring a patient’s posture continuously during hospitalization. Analysis of ViSi telemetry data enables researchers and healthcare providers to quantify an individual patient’s movement and investigate collective patterns of many patients. However, erroneous values can exist in routinely collected ViSi telemetry data. Data must be scrutinized to remove erroneous records before statistical analysis.

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Wearables and MHealth Reviews

Personal safety is a widespread public health issue that affects people of all demographics. There is a growing interest in the use of mobile apps for enhancing personal safety, particularly for children and youth at risk, who are among the most vulnerable groups in society.

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

As the most malignant type of cancer in the female reproductive system, ovarian cancer (OC) has become the second leading cause of death among Chinese women. Chemotherapy is the main treatment for OC patients, and its numerous adverse effects can easily lead to malnutrition. It is difficult to centrally manage OC patients in the intervals between chemotherapy. The utility of WeChat, an effective mobile tool, in chronic disease management has been highlighted.

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Preprints Open for Peer-Review

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