Journal of Medical Internet Research

Cognitive decline in older adults imposes a major global burden, with physical inactivity a leading modifiable risk factor for dementia. Digital physical exercise interventions offer scalable alternatives to traditional programs, but comparative effectiveness across cognitive domains remains unclear.

Digital health technologies, including telemedicine, electronic medical records, digital health tools (DHTs), and AI, are transforming European primary care, but evidence on how general practitioners (GPs) experience these tools remains fragmented.

Community-based management of exacerbations in high-risk patients with chronic obstructive respiratory diagnoses remains a major challenge. Hybrid care interventions, combining digital support with in-person, patient-centered care, have shown efficacy to reduce unplanned hospitalizations in controlled trials. However, an efficacy-effectiveness gap remains, indicating the complexities of its deployment and sustainable adoption in real-world scenarios.

AI-based models for predicting mortality have shown potential for intensive care unit (ICU) patients, but evidence regarding their cost-effectiveness remains limited.

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children and adolescents. Digital therapeutics (DTx) show promise as nonpharmacological interventions, but the comparative efficacy of different DTx modalities remains unclear.

Automated multimedia analysis of remotely recorded tasks offers a scalable approach to screening and remote monitoring of movement disorders such as Parkinson disease (PD). However, unsupervised recordings often suffer from quality issues that compromise model reliability. General multimedia quality checks may not detect task-specific failures, such as poor hand visibility during finger-tapping, inadequate facial framing during smile tasks, or background noise during speech tasks.

Patients increasingly use generative AI to interpret symptoms and seek health information, yet limited evidence shows how AI-assisted self-diagnosis is integrated into care-seeking and related to clinical interactions and patient–physician relationships.

AI has shown significant potential in intensive care unit (ICU) nursing practice, enhancing efficiency, decision-making, and patient safety. However, evidence regarding the implementation factors of AI in ICU nursing remains limited, particularly from the perspective of nursing leadership.

Policymakers are increasingly seeking to reduce the accessibility of internet-based pornography to children and young people. In 2026, the Australian government implemented mandatory age verification for access to pornography and some other online content.

Accurate and up-to-date medicinal product information is essential for the safe and effective use of medicines. Electronic labeling (e-labeling) has emerged as a potential alternative to paper-based package inserts by enabling timely updates, improving accessibility, and supporting integration with digital health systems. However, regulatory approaches to pharmaceutical e-labeling remain fragmented across jurisdictions.

Postoperative neurological complications (PNCs) after acute type A aortic dissection (ATAAD) surgery are clinically emergent and require multidimensional perioperative risk assessment. Large language models (LLMs) have shown potential in clinical prediction, but the incremental value of structured multiagent collaboration remains unclear.

The application of AI in clinical settings is becoming increasingly widespread, exerting a profound impact on health care professionals’ work patterns, decision-making efficiency, and clinical practice. However, there is currently a lack of systematic research on health care professionals’ actual experiences, barriers to use, and attitudes toward the clinical application of AI. AI has shown great potential to streamline clinical workflows and improve service quality, yet its real-world adoption faces notable obstacles.