Journal of Medical Internet Research

The prevalence of mental health difficulties among young people has risen in recent years, with 75% of mental disorders emerging before the age of 24 years. The identification and treatment of mental health issues earlier in life improves later-life outcomes. The COVID-19 pandemic spurred the growth of digital mental health interventions (DMHIs), which offer accessible support. However, young people of different ethnicities face barriers to DMHIs, such as socioeconomic disadvantage and cultural stigma.

Chronic obstructive pulmonary disease (COPD) is a progressive respiratory condition characterized by persistent airflow obstruction. Pulmonary rehabilitation (PR) is a cornerstone of COPD management but remains underutilized due to barriers such as low motivation and accessibility issues. Virtual reality (VR)–complemented PR offers a novel approach to overcoming these barriers by enhancing patient engagement and rehabilitation outcomes.

Stroke is a leading cause of long-term disability, often resulting in upper extremity dysfunction. Traditional rehabilitation methods often face challenges such as limited patient access to resources and lack of sustained motivation. Home-based virtual reality (VR) training is gaining traction as an innovative, sustainable, and interactive alternative. However, the effect of home-based VR, specifically for upper extremity recovery in patients with stroke, remains insufficiently explored.

Due to the complicated nature of Parkinson disease (PD), a number of subjective considerations (eg, staging schemes, clinical assessment tools, or questionnaires) on how best to assess clinical deficits and monitor clinical progression have been published; however, none of these considerations include a comprehensive, objective assessment of all functional areas of neurocognition affected by PD (eg, motor, memory, speech, language, executive function, autonomic function, sensory function, behavior, and sleep). This paper highlights the increasing use of digital health technology (eg, smartphones, tablets, and wearable devices) for the classification, staging, and monitoring of PD. Furthermore, this Viewpoint proposes a foundation for a new staging schema that builds from multiple clinically implemented scales (eg, Hoehn and Yahr Scale and Berg Balance Scale) for ease and homogeneity, while also implementing digital health technology to expand current staging protocols. This proposed staging system foundation aims to provide an objective, symptom-specific assessment of all functional areas of neurocognition via inherent device capabilities (eg, device sensors and human-device interactions). As individuals with PD may manifest different symptoms at different times across the spectrum of neurocognition, the modernization of assessments that include objective, symptom-specific monitoring is imperative for providing personalized medicine and maintaining individual quality of life.

Artificial intelligence (AI) is rapidly transforming health care, offering substantial advancements in patient care, clinical workflows, and nursing education.

Artificial intelligence (AI)–enabled decision support systems are critical tools in medical practice; however, their reliability is not absolute, necessitating human oversight for final decision-making. Human reliance on such systems can vary, influenced by factors such as individual psychological factors and physician experience.

Virtual patients (VPs) are computer screen–based simulations of patient-clinician encounters. VP use is limited by cost and low scalability.

The COVID-19 pandemic disrupted behavior within populations, affecting physical activity (PA), heart rate (HR), and sleep characteristics in particular. Activity trackers provide unique insights into these changes, enabling large-scale, real-time monitoring.

The health care sector contributes notably to environmental harms, impacting human and ecosystem health. Hence, countries increasingly set ambitions to transition to environmentally sustainable health care, focusing on resource use, energy consumption, and patient travel. Telemedicine is often considered a promising solution to reduce travel-related carbon emissions. However, underlying environmental impact assessments lack important components such as staff travel and fail to adhere to standardized conduct and reporting. Moreover, assessments of telemedicine use in primary care are scarce.

The global aging population faces great challenges. Wearable activity trackers have emerged as tools to promote physical activity among older adults, potentially improving health outcomes. However, the effectiveness of such interventions on physical activity, body composition, and physical function among community-dwelling older adults remains debated.

Large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities in various natural language processing tasks, particularly in text generation. However, their effectiveness in summarizing radiology report impressions remains uncertain.