JMIR Human Factors

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Cognitive reappraisal is a widely studied emotion regulation strategy that helps individuals reinterpret stressful situations in ways that reduce their emotional impact. Digital mental health (DMH) tools often struggle to support this process because scripted templates fail to adapt to the varied and incomplete ways users describe their stressors. Large language models (LLMs) offer opportunities to increase conversational flexibility while preserving structured intervention steps.

Formative assessment plays a central role in medical education by offering low-risk practice and timely feedback, particularly in visually and practically demanding courses, such as morphology. Gamified digital tools can foster active learning; however, their educational value relies on pedagogical integration rather than technology alone. The Technological Pedagogical Content Knowledge (TPACK) model provides a framework for understanding this relationship.

Clinical guidelines recommend integrated, person-centered care with control of modifiable risk factors and coexisting conditions in patients with atrial fibrillation (AF), but many receive insufficient risk factor management. Digital health technologies may provide valuable support in addressing this gap.

Privacy concerns represent a primary barrier to the adoption of large language model (LLM) applications, particularly in sensitive domains such as health care. Although a growing body of survey-based research has examined user privacy concerns with LLMs, no standardized instrument exists for measuring this construct.

Uptake of mild cognitive impairment (MCI) and dementia screening among community-dwelling older adults remains suboptimal globally and is shaped by limited dementia literacy, fear, stigma, and difficulties navigating services. Virtual reality (VR)–assisted education may enhance engagement, but older adults’ experiences of such education and the contextual conditions shaping screening intentions require further understanding.

Probability-based surveys remain essential to epidemiology, but expanding mixed-mode data collection, which combines web self-completion and interviewer-administered surveys, raises concerns that administration mode and interviewer presence may influence health reporting. These concerns warrant further investigation of interviewer-related biases and mode differences in health reporting.

AI is increasingly prevalent within health care; however, its implementation within the hospital setting may come with its own limitations, given the high-pressure and sensitive environment. Barriers and facilitators to the implementation of AI within hospitals have been largely explored quantitatively, and there is a scarcity of qualitative research on the implementation of AI tools to improve air quality.

Cardiovascular diseases (CVDs) remain a leading cause of morbidity and mortality. In primary prevention, effective communication of individual risk and support for behavior change are crucial. Interactive risk visualizations can enhance understanding and engagement, while continuous glucose monitoring (CGM) offers immediate feedback on the physiological effects of daily choices.

In 2019, Germany introduced a unique regulatory framework for digital therapeutics (DTx), termed digital health applications (DiGAs) in Germany, with the goal of integrating evidence-based DTx into statutory health care. DTx are eligible for reimbursement by statutory health insurance if manufacturers demonstrate positive health care effects, such as improved health status or health literacy, in a controlled study setting. Although regulatory evaluation primarily relies on manufacturer-conducted studies, these studies do not fully capture how users experience and use DiGAs in everyday life.

Safe integration of AI-enabled clinical decision support requires understanding whether users’ trust and behavioral reliance are appropriately calibrated to recommendation quality.

Lung-protective ventilation (LPV) reduces complications of mechanical ventilation, yet adherence in intensive care units (ICUs) remains inconsistent. Digital dashboards may support LPV by improving situational awareness and supporting protocol adherence. However, adoption of such tools in high-acuity clinical environments depends on a range of cognitive, professional, and contextual determinants. The Measurement Instrument for Determinants of Innovations (MIDI) provides a validated framework to systematically assess these factors.