Recent Articles
Since 2019, firearm violence has remained the leading cause of death for U.S. children and adolescents ages 1–19. This crisis has spurred action from policymakers, health professionals, and advocates. However, political polarization has contributed to divergent views on the causes and appropriate responses to firearm violence. Communication by elected officials, especially on social media, plays a critical role in shaping public opinion and policy agendas. Understanding how state policymakers discuss firearm violence, including the use of causal blame, calls to action, and health-related narratives, can inform more effective public health strategies.
Physical activity is a simple, low-risk intervention that could be integrated into daily life to improve glycemic control in individuals with prediabetes and early-stage type 2 diabetes mellitus (T2DM). However, maintaining physical activity remains challenging, even when its benefits are well understood. Although digital peer support has the potential to promote and maintain physical activity, its effectiveness has not yet been sufficiently established.
High staff turnover is a widespread issue across nearly all hospital departments, often exceeding 20% annually. This constant flux disrupts continuity of care and creates a recurring challenge: how to rapidly integrate new employees into complex clinical environments, both physically and functionally. Traditional onboarding methods struggle to meet this demand, particularly in services operating 24/7 such as emergency departments (EDs).
Youth and young adult mental health concerns are rising globally, with digital mental health platforms offering a promising solution for accessible support. Among the various features these platforms provide, goal setting and achievement have been shown to positively influence behavior change and mental health outcomes. However, there is limited understanding of how user-set goals compare to those set collaboratively with a practitioner regarding their impact on user engagement and mental health outcomes in digital mental health platforms.
Artificial Intelligence (AI) has the capacity to transform healthcare by improving clinical decision-making, optimizing workflows, and enhancing patient outcomes. However, this potential remains limited by a complex set of technological, human, and ethical barriers that constrain safe and equitable implementation. This paper argues for a holistic, systems-based approach to AI integration that addresses these challenges as interconnected rather than isolated. It identifies key technological barriers including limited explainability, algorithmic bias, integration and interoperability issues, lack of generalizability, and difficulties in validation. Human factors such as resistance to change, insufficient stakeholder engagement, and education and resource constraints further impede adoption, while ethical and legal challenges related to liability, privacy, informed consent, and inequity compound these obstacles. Addressing these issues requires transparent model design, diverse datasets, participatory development, and adaptive governance. Recommendations emerging from this synthesis are: (1) establish standardized international regulatory and governance frameworks; (2) promote multidisciplinary co-design involving clinicians, developers, and patients; (3) invest in clinician education, AI literacy, and continuous training; (4) ensure equitable resource allocation through dedicated funding and public–private partnerships; (5) prioritize multimodal, explainable, and ethically aligned AI development; and (6) focus on long-term evaluation of AI in real-world settings to ensure adaptive, transparent, and inclusive deployment. Adopting these measures can align innovation with accountability, enabling healthcare systems to harness AI’s transformative potential responsibly and sustainably to advance patient care and health equity.
Experience sampling methodology (ESM) is an assessment method utilised in psychosis research. Symptom severity and gender may be associated with ESM engagement. Exploring qualitative experiences of using ESM amongst people with psychosis should aid developing more relevant, accessible digital assessments.
Information provided by health professionals can be complex and is often not well understood by healthcare consumers, leading to adverse outcomes. Clinician-led communication approaches such as ‘teach-back’ can improve consumer understanding, yet are infrequently used by clinicians. A possible solution is to build consumers’ skills to proactively check their understanding rather than waiting for the clinician to do so; however, there are few educational resources to support consumers to build these skills.
Tobacco use remains the leading cause of preventable mortality in the United States; yet, evidence-based cessation services remain underused due to staffing constraints, limited access to counseling, and competing clinical priorities. Generative artificial intelligence (GenAI) chatbots may address these barriers by delivering personalized, guideline-aligned counseling through naturalistic dialogue. However, little is known about how GenAI chatbots support smoking cessation at both outcome and communication process levels.
For decades, the measurement of sleep and wake has relied upon watch-based Actigraphy as an alternative to expensive, obtrusive, clinical monitoring. To date, we have relied upon a handful of algorithms to score actigraphy data as sleep or wake. However, these algorithms have largely been tested and validated with only small samples of young healthy individuals.
Early identification of the etiology of spontaneous intracerebral hemorrhage (ICH) could significantly contribute to planning a suitable treatment strategy. A notable radiomics-based artificial intelligence (AI) model for classifying causes of spontaneous ICH from brain computed tomography (CT) scans has been previously proposed.
