JMIR Human Factors

Stress is a widespread public health concern associated with cardiovascular disease, depression, anxiety, and reduced quality of life. Digital mental health interventions (DMHIs), delivered through smartphones, web platforms, and wearables, offer scalable support for stress management but often struggle to sustain user engagement. Evidence describing how adaptive, conversational, and context-aware mechanisms function together within stress-focused DMHIs remains fragmented.

Effective patient portal access and use require both digital navigation and understanding of clinical information. Health literacy and eHealth literacy reflect these different demands. Although the 2 constructs overlap, prior research often treats them as interchangeable. It remains unclear whether health literacy and eHealth literacy are associated differently across stages of portal engagement and patterns of portal use. A systematic review is therefore needed to identify consistent patterns across studies.

The competencies required of life sciences graduates to participate in clinical trial research teams are poorly defined.

Chronic obstructive pulmonary disease (COPD) is characterized by acute exacerbations that frequently result in hospitalization, highlighting the need for improved follow-up care. Hybrid care incorporates digital health strategies such as remote patient monitoring (RPM). This could offer the opportunity to detect early signs of disease worsening by remotely tracking selected health indicators. However, it is unknown how RPM can effectively be integrated into current practice.

Real-world behavioral and physiological functioning, including heart rate, daily mobility, and sleep patterns, may provide information about aging and early neurodegenerative changes that is not captured by periodic clinical visits. Wrist-worn wearable devices offer a promising approach for continuous, passive monitoring of these domains. However, evidence regarding feasibility, usability, and acceptability in real-world observational settings among community-dwelling older adults in China remains limited.

Older people who receive aged care services at home experience high rates of depression, anxiety, and loneliness, yet have poor access to services to support their well-being. Digital interventions are widely available, but research is required to determine whether they are acceptable to the in-home aged care population.

Digital microinterventions are increasingly used to support stress self-management in everyday life. While previous research has examined their feasibility, adherence, and preliminary effectiveness, much less is known about how these interventions are experienced over extended periods of real-world use.

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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.