JMIR Formative Research

In the digital era, smartphone technology has significantly advanced ocular imaging, allowing for high-resolution anterior segment photography (ASP) to enhance referrals, decision-making, and disease monitoring within clinical workflows.

Commercially available wearable devices, capable of measuring cardiac rhythm, are gaining popularity for convenient heart health monitoring. Accurate measurement of key intervals, specifically RR intervals for rhythm and QT and corrected QT (QTc) intervals for arrhythmia risk, is crucial for assessing potential cardiac morbidity.

Screening is important for early detection of cervical cancer in low- and middle-income countries. Visual inspection with acetic acid (VIA) is usually the method of choice in these settings. However, interpretation of VIA results is subject to interobserver and intraobserver variability. AI decision support systems (AI-DSSs) could contribute to better decisions by health workers.

Basic life support (BLS) significantly improves survival and neurological outcomes after out-of-hospital cardiac arrest (OHCA). However, bystander cardiopulmonary resuscitation (CPR) rates vary widely worldwide, reaching only 40% in Geneva, Switzerland. The European Resuscitation Council’s “Kids Save Lives” statement advocates for integrating BLS education into mandatory school curricula to improve bystander CPR rates, and thus OHCA outcomes. Training medical students as BLS instructors could help address the shortage of qualified instructors needed to implement school-based BLS programs in primary schools.

Remote patient management (RPM) is a strategy to track daily health data in patients with heart failure (HF) to enable early detection and treatment of decompensation to prevent hospital readmissions. The implementation of RPM alters standard care and redistributes provider responsibilities. Although randomized controlled trials demonstrate positive clinical outcomes, the impact of implementing RPM on patients’ health care usage, as well as the care time and workload of health care providers in a real-world setting, remains unclear.

A digital clinician training module significantly improved attitudes, beliefs, and self-perceived competence in a cohort of medical students (n=87) toward working with transgender and gender diverse (TGD) people with eating disorders. Future clinician training resources can adopt this cost-effective and accessible learning model and build upon existing introductory attitude- and awareness-based programs by focusing on addressing a specific health disparity among TGD people.

Recent advances in AI, particularly large language models, have generated growing interest in their application to medical education and examination preparation. However, the accuracy, reasoning quality, and adherence to clinical guidelines of these tools in postgraduate urology assessments remain unclear.

Breast augmentation is one of the most performed aesthetic surgical procedures worldwide. Given its elective character and potential complications, clear and comprehensible informed consent is essential.

Despite widespread discussion of opportunities and risks about AI in medicine, few health care professionals routinely used AI during this study period. Physicians and men were more likely to report frequent AI use, and frequent AI users more often reported positive sentiments about AI’s future impacts on pay, enjoyment, and productivity at work. The youngest professionals (≤29 years) were less engaged and more skeptical about AI’s future benefits. These findings highlight a gap between AI’s promise and medical practice, as adoption varies by role, experience, and demographics.

AI is increasingly being explored as a tool to enhance efficiency, access, and diagnostic accuracy in mental health care. However, the perspectives of clinicians, who are central to the delivery and oversight of care, on the use of AI remain underexamined.

A multilayered fraud-mitigation approach is essential to ensure data integrity in medical survey research; basic measures alone (eg, CAPTCHA) would permit widespread fraud.

National digital health systems are increasingly recognized as a key tool for strengthening health care systems and improving patient outcomes. Global guidance from the World Health Organization and European Union initiatives emphasizes interoperability, robust data governance, and secure exchange of health information as prerequisites for system-wide benefits. However, translating these principles into operational national digital health infrastructures remains challenging, and empirical evidence on long-term, centralized implementation models is limited. Lithuania is among a small number of European countries that have implemented a fully centralized national digital health platform (DHP), providing a valuable case for examining the development, structure, and performance of such systems.