Journal of Medical Internet Research

Digital therapeutics (DTx) are software-driven interventions that provide personalized, evidence-based treatments for various medical conditions. China’s rapid technological adoption, large population, and supportive government policies position it as a potential global leader in DTx. However, challenges remain in clinical trial standardization, regulatory approval, product development, and reimbursement models. A comprehensive assessment of clinical evidence, commercialization trends, and regulatory frameworks is essential for understanding China’s evolving DTx ecosystem and its global implications.

Fetal growth restriction (FGR) is a common complication of preeclampsia. FGR in patients with preeclampsia increases the risk of neonatal-perinatal mortality and morbidity. However, previous prediction methods for FGR are class-biased or clinically unexplainable, which makes it difficult to apply to clinical practice, leading to a relative delay in intervention and a lack of effective treatments.

Assessment of cognitive decline in the earliest stages of Alzheimer disease (AD) is important but challenging. AD is a neurodegenerative disease characterized by gradual cognitive decline. Disease stages range from preclinical AD, in which individuals are cognitively unimpaired, to mild cognitive impairment (MCI) and dementia. Digital technologies promise to enable detection of early, subtle cognitive changes. Although the field of digital cognitive biomarkers is rapidly evolving, a comprehensive overview of the reporting of psychometric properties (ie, validity, reliability, responsiveness, and clinical meaningfulness) is missing. Insight into the extent to which these properties are evaluated is needed to identify the validation steps toward implementation.

Potentially inappropriate prescribing in outpatient care contributes to adverse outcomes and health care inefficiencies. Clinical decision support systems (CDSS) offer promising solutions, but their effectiveness is often constrained by incomplete medical records.

Hispanic communities have been disproportionately affected by the COVID-19 pandemic. In addition to elevated health risks and burdens, these populations have faced persistent barriers to accessing accurate, timely information regarding the pandemic’s trajectory, including vaccine-related updates. To address these challenges, it is crucial to examine the conditions under which Hispanics are most likely to seek information about COVID-19 vaccinations.

Clinical operative skills training is a critical component of preclinical education for dental students. Although technology-assisted instruction, such as virtual reality and simulators, is increasingly being integrated, direct guidance from instructors remains the cornerstone of skill development. ChatGPT, an advanced conversational artificial intelligence model developed by OpenAI, is gradually being used in medical education.

Rigorous evaluation of generalist medical AI (GMAI) is imperative to ensure their utility and safety before implementation in health care. Current evaluation strategies rely heavily on benchmarks which can suffer from issues with data contamination and cannot explain how GMAI might fail (lacking explanatory power) or in what circumstances (lacking predictive power). To address these limitations we propose a new methodology to improve the quality of GMAI evaluation using construct-oriented processes. Drawing on modern psychometric techniques, we introduce approaches to construct identification and present alternative assessment formats for different domains of professional skills, knowledge, and behaviours that are essential for safe practice. We also discuss the need for human oversight in future GMAI adoption.

Mental health issues have emerged as a global challenge, particularly affecting middle-aged and older adults. Research has shown that internet use can potentially promote mental health. Substantial research investigated the relationship between mental health and internet usage time or purposes. However, few studies have examined the association between internet usage time trajectories and mental health.

Digital tools for communication, coordination, cooperation, and collaboration (D4C), including electronic health records and specialized apps, are increasingly used in health care to ensure continuity of care across professional boundaries. Despite their growing adoption, there is a lack of precise and clear definitions, and no common understanding of D4C within health care.

Chronic obstructive pulmonary disease (COPD) exacerbations cause physiological and psychological distress, affecting overall health and quality of life. Early diagnosis of exacerbations is crucial for preserving lung function, preventing hospitalizations, and reducing health care costs. While remote patient monitoring (RPM) offers the potential for early exacerbation detection, challenges remain in recognizing symptoms in a timely manner. A noninvasive breath analysis device is under development to monitor patients with COPD and detect exacerbations before symptoms arise by measuring breath biomarkers through volatile organic compounds. This study encompassed the initial cocreation phase to align the use of the breath analysis device and corresponding care process with current COPD exacerbation management and user needs.

Vital signs monitoring (VSM) is used in clinical acuity scoring systems (APACHE [Acute Physiology and Chronic Health Evaluation], NEWS2 [National Early Warning Score 2], and SOFA [Sequential Organ Failure Assessment]) to predict patient outcomes for early intervention. Current technological advances enable convenient remote VSM. While the role of VSM for ill, hospital ward–treated patients is clear, its role in the community for acutely ill patients in the hospital at home (HAH) or postacute setting (patients who have just been discharged from an acute hospital stay and at increased risk of deterioration) is less well defined.

Chronic obstructive pulmonary disease (COPD), marked by dyspnea, cough, and sputum production, significantly impairs patients’ quality of life and functionality. Effective management strategies, particularly those empowering patients to manage their condition, are essential to reduce this burden and health care use. Digital health interventions—such as mobile apps for symptom tracking, wearable sensors for vital sign monitoring, and web-based pulmonary rehabilitation programs—can enhance self-efficacy and promote greater patient engagement. By improving self-management skills, these interventions also help alleviate pressure on health care systems.