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 5.8 CiteScore 11.7
Recent Articles


In the context of escalating global mental health challenges, adolescent suicide has become a critical public health concern. In current clinical practices, considerable challenges are encountered in the early identification of suicide risk, as traditional assessment tools demonstrate limited predictive accuracy. Recent advancements in machine learning (ML) present promising solutions for risk prediction. However, comprehensive evaluations of their efficacy in adolescent populations remain insufficient.

The design and integration of technology within inpatient hospital rooms has a critical role in supporting nursing workflows, enhancing provider experience, and improving patient care. As health care technology evolves, there is a need to design “future-proofed” physical environments that integrate technology in ways that support workflows and maintain clinical performance. Assessing how current technologies affect nursing workflows can help inform the development of these future environments.


Industry stakeholders, academic experts, and regulatory bodies emphasize the importance of prioritizing a patient-centered experience in clinical trials to enhance retention, adherence, and trial participation. Concurrently, there has been a notable rise in the adoption of technology-mediated decentralized methodologies for conducting clinical trials. Nonetheless, is a truly patient-centric approach being achieved? The shift to decentralized approaches risks prioritizing operational efficiency and remote data collection over the nuanced and diverse needs of participants. This raises critical questions about whether the current implementation of decentralized clinical trials (DCTs) fully aligns with the principles of patient centeredness.

Teaching is often characterized as a stressful profession, with a substantial proportion of teachers experiencing chronic stress and burnout. Research indicates that teachers often experience stress upon entering the workforce, leading to detrimental effects on their health, occupational well-being, and work performance and adversely impacting student outcomes. While meta-analyses have demonstrated the efficacy of internet-based stress management interventions (iSMIs) for both experienced professionals and university students, there remains a gap in research on the efficacy of iSMIs tailored to teachers and career starters.


Infertility is defined as the inability to achieve a live birth after one year of regular sexual intercourse, affecting 1 in 6 couples in France. The use of ART for infertility issues has been steadily increasing in recent years, with in vitro fertilization being the most common type of ART. Infertility is frequently regarded as a significant life crisis for many individuals, potentially leading to depression, anxiety, social isolation, and sexual dysfunction. Couples experiencing infertility demonstrate a high prevalence of negative emotional responses and decreased life satisfaction as a result of infertility and its treatments. Social media have become key tools for finding and disseminating medical information.


Previous studies have revealed that deviant peer affiliation (DPA) and Internet gaming disorder (IGD) are highly related and often co-occur. Nevertheless, the dynamic interactions among these symptoms, their bidirectional effects, and the underlying mechanisms contributing to their persistence remain poorly understood. Most existing research relies on cross-sectional designs or examines aggregated scores, limiting the ability to detect time-dependent symptom interactions. In particular, prior studies overlook the complex bidirectional relationships between specific IGD and DPA symptoms over time. As adolescence is a developmental period marked by rapid changes in peer relationships and behavioral regulation, distinguishing temporal associations between specific DPA and IGD symptoms at both the within- and between-person levels is important for clarifying mechanisms of their co-occurrence and informing personalized intervention strategies.

Coronary computed tomography angiography (CCTA) has emerged as the first-line noninvasive imaging test for patients at high risk of coronary artery disease (CAD). When combined with machine learning (ML), it provides more valid evidence in diagnosing major adverse cardiovascular events (MACEs). Radiomics provides informative multidimensional features that can help identify high-risk populations and can improve the diagnostic performance of CCTA. However, its role in predicting MACEs remains highly debated.
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