Journal of Medical Internet Research

Childhood anxiety disorders are common and lead to substantial negative long-term outcomes in various life domains. Although digital interventions for preventing childhood anxiety problems have been increasingly used in the recent decade, there is limited evidence documenting their cost-effectiveness (CE).

Aphasia, an acquired language disorder that affects the ability to understand and produce language, significantly impairs effective communication. Large language models (LLMs) such as ChatGPT may help by generating fluent and coherent text, offering new ways to support communication for people with aphasia.

As the population of survivors of cancer grows and new information technologies become widespread in Hong Kong, survivors of cancer increasingly seek ongoing care and support information from large language models (LLMs). While these tools provide immediate conversational responses, they carry substantial risks of generating inaccurate, unsafe, or generic medical advice. Evaluating LLM response performance is particularly critical in Hong Kong’s bilingual health care context.

Carotid ultrasound is traditionally confined to specialist settings because examination quality and diagnostic reliability are highly dependent on the operator’s technical skill and experience. Recent advances in AI-assisted ultrasound may enable task shifting to primary care staff and support the integration of personalized visual risk communication into routine preventive care. Visualization of subclinical atherosclerosis has been shown to strengthen cardiovascular risk communication and support preventive engagement. However, limited evidence exists on how such technology can be practically integrated into routine primary care workflows and what conditions are required to support use by nonexpert operators.

Theoretical perspectives offer contrasting predictions regarding how inequalities in health technology adoption evolve over time. While classical diffusion of innovations theory suggests that early adoption gaps may narrow as technologies such as telemedicine become widespread, the inverse equity hypothesis posits that such disparities are likely to persist or even widen. Longitudinal evidence on the long-term evolution of individual telemedicine adoption, however, remains scarce.

AI-enabled clinical decision support systems (CDSS) are being used in primary care, but their effects on clinical decisions and patient outcomes remain uncertain.

Fully remote online health research is vulnerable to fraudulent participation that can threaten data validity and divert study resources. Although fraud mitigation is increasingly necessary in online research, mitigation efforts are rarely described systematically or evaluated transparently across studies.

The journey to parenthood involves significant physical, emotional, and psychosocial changes. Mental health challenges impact both maternal and fetal health, potentially leading to obstetric complications and developmental risks for children. Access to needed perinatal support is often limited due to individual and structural barriers. Digital health solutions can offer opportunities to provide low-threshold, personalized, and scalable support. We developed a digital navigator offering personalized guidance and connecting users to relevant support services with interactive follow-ups to self-assess their well-being. However, evidence regarding the feasibility of digital solutions in high-risk patients is limited.

Chronic musculoskeletal pain is a major public health problem, and access to continuous, long-term care remains challenging. Digital health interventions may extend care beyond conventional settings; however, their comparative effects across delivery modalities and core therapeutic components remain uncertain.

Digital health increasingly depends on data exchange across institutions, technologies, and jurisdictions, creating persistent challenges for the governance of access, consent, interoperability, provenance, and accountability. Blockchain and distributed ledger technology (DLT) systems have been proposed as mechanisms for coordinating and verifying governance processes across distributed actors. However, existing research has examined individual applications or technical domains, leaving unclear how blockchain/DLT systems function as governance infrastructure across health care, and whether these systems have progressed toward real-world implementation.

National surveillance of commercial retail environments remains limited by data sources that are updated infrequently and capture narrow dimensions of food access. The Google Places API provides continuously updated and programmatically accessible information on business locations across the United States, but its use as a population-level built-environment exposure measure has not been systematically evaluated.

Retinopathy of Prematurity (ROP) is a leading cause of preventable childhood blindness; yet, a global shortage of experienced pediatric ophthalmologists impedes timely diagnosis and treatment. While emerging AI chatbots are promising clinical decision-support tools in some ophthalmic diseases, their performance in ROP diagnosis and providing treatment suggestions remains uncertain.