Journal of Medical Internet Research

The leading peer-reviewed journal for digital medicine and health and health care in the internet age. 

Editor-in-Chief:

Gunther Eysenbach, MD, MPH, FACMI, Founding Editor and Publisher; Adjunct Professor, School of Health Information Science, University of Victoria, Canada


Impact Factor 6.0 CiteScore 11.7

The Journal of Medical Internet Research (JMIR) is the pioneer open access eHealth journal, and is the flagship journal of JMIR Publications. It is a leading health services and digital health journal globally in terms of quality/visibility (Journal Impact Factor 6.0, Journal Citation Reports 2025 from Clarivate), ranking Q1 in both the 'Medical Informatics' and 'Health Care Sciences & Services' categories, and is also the largest journal in the field. The journal is ranked #1 on Google Scholar in the 'Medical Informatics' discipline. The journal focuses on emerging technologies, medical devices, apps, engineering, telehealth and informatics applications for patient education, prevention, population health and clinical care.

JMIR is indexed in all major literature indices including National Library of Medicine(NLM)/MEDLINE, Sherpa/Romeo, PubMed, PMCScopus, Psycinfo, Clarivate (which includes Web of Science (WoS)/ESCI/SCIE), EBSCO/EBSCO Essentials, DOAJ, GoOA and others. Journal of Medical Internet Research received a Scopus CiteScore of 11.7 (2024), placing it in the 92nd percentile (#12 of 153) as a Q1 journal in the field of Health Informatics. It is a selective journal complemented by almost 30 specialty JMIR sister journals, which have a broader scope, and which together receive over 10,000 submissions a year. 

As an open access journal, we are read by clinicians, allied health professionals, informal caregivers, and patients alike, and have (as with all JMIR journals) a focus on readable and applied science reporting the design and evaluation of health innovations and emerging technologies. We publish original research, viewpoints, and reviews (both literature reviews and medical device/technology/app reviews). Peer-review reports are portable across JMIR journals and papers can be transferred, so authors save time by not having to resubmit a paper to a different journal but can simply transfer it between journals. 

We are also a leader in participatory and open science approaches, and offer the option to publish new submissions immediately as preprints, which receive DOIs for immediate citation (eg, in grant proposals), and for open peer-review purposes. We also invite patients to participate (eg, as peer-reviewers) and have patient representatives on editorial boards.

As all JMIR journals, the journal encourages Open Science principles and strongly encourages 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.

Be a widely cited leader in the digital health revolution and submit your paper today!

Recent Articles

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Artificial Intelligence

Traditional ocular gaze photograph preprocessing, relying on manual cropping and head tilt correction, is time-consuming and inconsistent, limiting AI model development and clinical application.

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Artificial Intelligence

Heart failure with preserved ejection fraction (HFpEF) is a major clinical manifestation of cardiac amyloidosis (CA), a condition frequently underdiagnosed due to its nonspecific symptomatology. Electronic health records (EHRs) offer a promising avenue for supporting early symptom detection through natural language processing (NLP). However, identifying relevant clinical cues within unstructured narratives, particularly in Spanish, remains a significant challenge due to the scarcity of annotated corpora and domain-specific models.

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Artificial Intelligence

The quality and accessibility of menstrual health education in developing nations, including India, remain inadequate due to challenges such as poverty, social stigma, and gender inequality. While community-driven initiatives aim to raise awareness, artificial intelligence (AI) offers a scalable solution for disseminating accurate information. However, existing general-purpose large language models (LLMs) are ill-suited for this task, suffering from low accuracy, cultural insensitivity, and overly complex responses. To address these limitations, we developed MenstLLaMA, a specialized LLM tailored to the Indian context, designed to deliver menstrual health education empathetically, supportively, and accessible.

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Mobile Health (mhealth)

Mood disorders, including bipolar disorder (BP) and major depressive disorder (MDD), are characterized by significant psychological and behavioral fluctuations, with mobility patterns serving as potential markers of emotional states.

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Digital Mental Health Interventions, e-Mental Health and Cyberpsychology

Virtual reality (VR) stationary cycling provides a potential solution to enhance adherence and reduce depressive symptoms, particularly for people with depression. However, high-quality evidence is needed to support its implementation in clinical practice.

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Viewpoints and Perspectives

Advances in artificial intelligence (AI) promise to reshape the landscape of scientific inquiry. Amidst all these, OpenAI’s latest tool, Deep Research, stands out for its potential to revolutionize how researchers engage with the literature. However, this leap forward presents a paradox - while AI-generated reviews offer speed and accessibility with minimal effort, they raise fundamental concerns about citation integrity, critical appraisal, and the erosion of deep scientific thinking. These concerns are particularly problematic in the context of biomedical research, where evidence quality may influence clinical practice and decision-making. In this piece, we present an empirical evaluation of Deep Research and explore both its remarkable capabilities and inherent limitations. Through structured experimentation, we assess its effectiveness in synthesizing literature, highlight key shortcomings, and reflect on the broader implications of these tools for research training, and the integrity of evidence-based practice. With AI tools increasingly blurring the lines between knowledge generation and critical inquiry, we argue that while AI democratizes access to knowledge, wisdom remains distinctly human.

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Clinical Informatics

Hospital Information Systems (HIS) aim to support users in their time-critical routines on hospital wards with accurate and timely information. However, if these systems create blockages to workflows, nurses and physicians develop workarounds to provide care to the patients, nonetheless. Workarounds are both considered negatively, when associated with risks, and positively, when seen as feedback and source of innovation. Learning about the antecedents of workarounds allows for the establishment of control mechanisms, under the promise of enhanced patient safety.

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Mobile Health (mhealth)

The most common symptom of atopic dermatitis (AD) is pruritus, which is often exacerbated at night and leads to nocturnal scratching and sleep disturbance. The quantification of nocturnal scratching provides an objective measure, which could be used as a clinical trial endpoint tracking this AD-related behavior. However, it is not clear how digital health technologies (DHTs) intended to measure scratching perform in the real-world environment of patient homes.

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Chatbots and Conversational Agents

Perioperative education is crucial for optimizing outcomes in neuroendovascular procedures, where inadequate understanding can heighten patient anxiety and hinder care plan adherence. Current education models, reliant on traditional consultations and printed materials, often lack scalability and personalization. Artificial intelligence (AI)–powered chatbots have demonstrated efficacy in various health care contexts; however, their role in neuroendovascular perioperative support remains underexplored. Given the complexity of neuroendovascular procedures and the need for continuous, tailored patient education, AI chatbots have the potential to offer tailored perioperative guidance to improve patient education in this specialty.

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Telehealth and Telemonitoring

Healthcare systems are increasingly facing challenges posed by the aging of populations. In particular hospitalization, both initial and subsequent, which is often observed among elderly patients. Yet, research suggests that nearly 23% of all hospitalizations could be avoided. In this perspective, remote patient monitoring (RPM) systems are emerging as a promising solution, enabling professionals to detect and manage patient complexities early within home-based care settings.

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Artificial Intelligence

Clinical problem-solving requires processing of semantic medical knowledge such as illness scripts and numerical medical knowledge of diagnostic tests for evidence-based decision-making. As large language models (LLMs) show promising results in many aspects of language-based clinical practice, their ability to generate non-language evidence-based answers to clinical questions is inherently limited by tokenization.

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Preprints Open for Peer-Review

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Open Peer Review Period:

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Open Peer Review Period:

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We are working in partnership with

  • Crossref Member

  • Committee on Publication Ethics

  • Open Access

  • Open Access Scholarly Publishers Association

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  • TrendMD MemberORCID Member

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This journal is indexed in

 
  • PubMed

  • PubMed CentralMEDLINE

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  • DOAJCINAHL (EBSCO)PsycInfoSherpa RomeoEBSCO/EBSCO Essentials

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  • Web of Science - SCIE

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