JMIR Formative Research

Shared decision-making (SDM) is a core competency in patient-centered care, yet it is challenging for physicians. Simulation-based education with standardized patients (SPs) offers valuable practice opportunities for undergraduate medical education (UME), but is limited by cost, scalability, and variable feedback quality. Advances in large language model (LLM) technology and virtual patient (VP) design present a promising pathway toward accessible, realistic, and high-quality SDM skill training.

Amid the current primary care crisis, Canadians are increasingly turning to online resources, where misinformation is common. Launched in 2023, the web application Icanbewell provides free, reliable, evidence-based information on preventive health care.

Axial spondyloarthritis (axSpA) is a chronic inflammatory rheumatic disease affecting the axial skeleton that requires regular physical exercise in addition to pharmacotherapy. However, a significant proportion of patients do not exercise frequently enough. Axia is a digital therapeutic (DTx) that offers a solution by providing a disease-specific and patient-tailored home-based exercise program for patients with axSpA. The app combines structured exercise with patient education and disease management features and incorporates gamification and behavioral conditioning to promote user engagement. However, it has remained unclear how Axia is perceived and evaluated by patients.

Mental illness is a leading cause of disability worldwide, affecting more than 1 billion people, and suicide accounts for 720,000-800,000 deaths annually. Although AI-native mental health chatbots have the potential to help address the substantial gap between treatment needs and workforce capacity, their rapid proliferation has outpaced the development of scalable procedures for identifying and responding to suicidal ideation. Although recommendations call for human oversight to support safety monitoring and intervention in AI-based care, research on human clinical oversight and crisis-response procedures remains limited.

Triple-negative breast cancer (TNBC) is an aggressive molecular subtype of breast cancer that needs to be identified accurately from pathology reports to inform decision-making. Large language models (LLMs) have been reported to show great potential in the automatic extraction of important oncology information from unstructured medical text.

User-centered design (UCD) processes often generate extensive lists of potential software features, necessitating prioritization methods to guide development. The MoSCoW method, categorizing features as “must have,” “should have,” “could have,” or “won’t have,” is widely used in software development for its simplicity and ease of adoption. Despite its popularity, limited evidence exists on its application within health informatics. The Decision Aid Navigator (DEAN) system, a clinical decision support tool, required prioritization of features for its administrative portal to ensure usability and alignment with health information technology (HIT) professionals’ needs.

Older adults living alone are at increased risk during medical emergencies, particularly due to delayed detection, information transmission, and physical access to the home. Digital health and Internet of Things (IoT)-based technologies offer opportunities to strengthen emergency response systems; however, evidence on the real-world implementation and performance of integrated home-based emergency assistance platforms remains limited.

An exploratory survey of health care–related X (formerly Twitter) users identified perceived challenges in digital professionalism, including exposure to misinformation, collegial disagreements, and unprofessional conduct, while highlighting gaps in institutional guidance and the need for clearer policies and digital-professionalism education.

This research letter describes the development and initial validation of SAFE-Nurse, an artificial intelligence–assisted patient safety incident reporting system for nurses, which demonstrated excellent content and face validity (average scale-level content validity index [S-CVI/Ave] 0.99; average scale-level face validity index [S-FVI/Ave] 1.00) and is ready to progress to usability testing.

Latina pregnant women and mothers of infants in the United States experience elevated risk for perinatal anxiety, stress, and depression alongside persistent barriers to culturally and linguistically responsive care. AI-powered digital health tools offer a potentially scalable approach to address these gaps, yet evidence on their acceptability and effectiveness for this population remains limited.

Only approximately half of adults with hypertension, a leading cardiovascular risk factor, achieve blood pressure (BP) control, with persistent disparities among low-income and minority populations. Wireless home BP monitoring (HBPM) with remote patient monitoring can improve BP control, but evidence is limited in medically underserved, predominantly Hispanic populations served by federally qualified health centers (FQHCs).

Despite strong evidence supporting the benefits of regular physical activity (PA) for managing coronary heart disease (CHD), PA advice remains infrequent in general practice. Barriers include the limited familiarity of general practitioners (GPs) with current PA guidelines and their application to CHD patients, their insufficient skills for delivering very brief advice, and time constraints. To our knowledge, no structured, theory-informed training has been reported in Germany to support GPs in delivering very brief PA advice in routine CHD care.