JMIR Formative Research

Behavioral and psychological symptoms of dementia (BPSD) are among the most challenging aspects of dementia care and contribute substantially to care partner burden. Family care partners, who provide most community-based dementia care, often lack access to evidence-based, nonpharmacological interventions for managing BPSD, particularly in underserved communities. Mobile health (mHealth) apps offer a promising avenue to expand care partners’ access to caregiving support. However, existing dementia caregiving apps frequently provide generalized information rather than personalized guidance based on care partners’ priorities.

Autism spectrum disorder is underdiagnosed in adults, with increasing demand on diagnostic services and prolonged waiting times. AI-powered tools may offer scalable solutions for early screening and triage.

The SimZones model is an organizational framework for simulation-based education that structures learning across 5 progressive zones, from self-directed preparatory activities (zone 0) to team-based clinical scenarios (zones 1‐4). However, empirical evidence on the impact of zone 0 regarding procedural skill acquisition and retention remains limited.

Generative AI can reduce the academic-writing burden on clinical health care professionals, but unsupervised use introduces citation hallucination (the confident fabrication or misattribution of references), which threatens research integrity. When a machine invents a source, it is termed “hallucination,” and when a person does it, it is termed “fabrication,” yet both are equally unacceptable. Existing health professions education writing workshops have rarely translated this concern into a concrete, reproducible source-verification procedure.

The prospective prescription review system can improve prescription rationality, but its effectiveness in high-volume specialty care settings is not well established.

Large language models (LLMs) are increasingly used to support digital health communication, yet their reliability in patient-facing cardiovascular imaging education remains uncertain. Cardiovascular imaging involves complex terminology and procedural details that many patients struggle to understand, creating a need for accurate, clear, and reassuring explanations. While prior evaluations of conversational AI have focused primarily on diagnostic reasoning or clinician-oriented tasks, few studies have systematically compared contemporary LLMs in their ability to communicate effectively with patients.

Home spirometry has been widely adopted in the delivery of cystic fibrosis (CF) care. While existing literature largely supports its feasibility and positive outcomes, behavior around home disease monitoring remains poorly understood. Inaccurate assumptions about home spirometry behavior may affect resource prioritization and influence clinical decisions and follow-up.

Young Black and Latino men who have sex with men and transgender women who have sex with men (YBLMT) experience disproportionate HIV-related health disparities in the United States. Digital health interventions offer scalable HIV prevention and support services for these populations. However, recruitment strategies may influence both sample demographics and participant retention, which is critical for intervention effectiveness.

Rural communities continue to experience behavioral health disparities associated with workforce shortages, digital exclusion, and fragmented coordination between trusted community-based supports and formal behavioral health systems. Although telehealth has expanded opportunities for care, less is known about how key implementation factors interact within hybrid behavioral health systems—coordinated systems that integrate trusted community-based support with formal digital behavioral health services—or how these interactions influence implementation and engagement across community and formal care settings.

Workday happiness is associated with workplace performance and burnout, but frequent questionnaire-based assessment is burdensome in real-world workplace settings. Free-text daily reports may provide a lower-burden way to monitor day-to-day changes in workday happiness.

While large language model (LLM)–assisted qualitative analysis could improve the efficiency and scalability of feedback-driven curricular refinement in medical education, how best to leverage LLMs for qualitative analysis while ensuring quality outputs remains an open question. Prior work has demonstrated the feasibility of using LLMs for inductive and deductive coding tasks, but more needs to be known about how LLM-assisted thematic coding can best be deployed in a medical education context to maximize its strengths and guard against its weaknesses.

Smartphones and wearables can continuously capture behavioral and physiological data in everyday life. Such mobile-sensing data may help track depressive symptoms more closely than occasional retrospective questionnaires, but prior findings have been mixed. Inconsistent findings do not preclude the presence of predictive relationships in specific individuals or time periods. In addition, it remains unclear which broader sensor domains, rather than single features, contribute most to prediction at the individual level.