JMIR Formative Research

In the context of COVID-19, infection spread through human contact networks remains a major public health challenge. Beyond cumulative infections and deaths, it is necessary to understand which contacts matter most, and which population segments contribute most to transmission under different social conditions. In multilayer urban networks with community structure, routine contacts coexist with incidental encounters, and it remains unclear whether incidental encounters can alter epidemic burden and the main contributors to transmission when per-layer contact caps and routine-contact minima are unchanged (for the nonrandom layers).

Care home placements offer important opportunities for student nurses to develop relational and person-centered approaches to dementia care. Digital reminiscence platforms are increasingly used to support the well-being of people living with dementia; however, little is known about how such platforms may shape student learning within practice settings. There is limited qualitative evidence examining how digital reminiscence is experienced by students and how it influences their understanding of personhood, relationships, and care practices.

Cognitive decline in aging populations underscores the need for early interventions in mild cognitive impairment (MCI), where pharmacological treatments show limited benefit. Eye-movement metrics serve as sensitive markers of cognitive deficits in MCI, and digital programs integrating these tasks offer scalable, data-driven training approaches.

The COVID-19 pandemic was marked by rapidly evolving and inconsistent public health messaging, contributing to confusion regarding recommended preventive behaviors. Knowledge, attitudes, and practices (KAP) and perceived risk frameworks offer a structured approach to examine how education, personal beliefs, and contextual factors influence health behaviors during public health emergencies. Vulnerable populations, such as patients with multiple sclerosis (MS), experience heightened risk perception compared with the general population, which may further shape behavioral responses.

Despite the notable proliferation of smoking cessation mobile apps, to date, no validated, Spanish-language, culturally tailored mobile intervention exists for Spanish speakers in the United States.

Osteoporosis poses a significant global health burden and is responsible for over 8.9 million fragility fractures annually. Despite evidence-based guidelines and treatment, a substantial care gap persists, with only a low percentage of fracture patients receiving guideline-concordant care. Primary care physicians (PCPs) are pivotal in community-based fracture prevention but face challenges in translating knowledge into practice. While hospital-based fracture liaison services are effective, their reach is limited, necessitating scalable alternatives. Virtual communities of practice and web-based learning tools offer promising avenues for PCP professional education; however, their application in osteoporosis management remains underexplored. The Community Fracture Capture (CFC) Learning Hub was developed as an interactive, case-based platform to address these gaps by enhancing PCPs’ knowledge, confidence, and engagement in osteoporosis care.

Clinical decision-making training in operative dentistry commonly relies on real or standardized patients to develop undergraduate students’ ability to deliver safe, effective, and patient-centered care. However, training with real or standardized patients can be limited in scalability, cost-effectiveness, and accessibility. Large language models, with their human-like language capabilities, may have the potential to simulate patients in clinical encounters and help overcome some limitations associated with traditional training approaches.

Growing evidence suggests that disruptions in rest-activity rhythms may serve as relevant markers of posttraumatic stress disorder (PTSD). Despite the emergence of machine learning methods applied to actigraphy and self-report data, few studies have used these approaches to identify individuals with clinically diagnosed PTSD. Prior work has focused on predicting probable PTSD based on self-report measures, yet discrepancies exist between clinical diagnoses and probable PTSD derived from self-reports.

Pediatric emergency departments see a high volume of patients. Given that children often cannot describe their condition and there is a shortage of nursing staff, it is essential to identify the early warning signs of adverse conditions among children as quickly as possible. Current targeted care needs to be improved.

In recent years, digital patient portals have become an increasingly common feature of care in various medical fields. Despite growing scientific evidence of their effectiveness and the benefits they offer to patients and caregivers, their implementation, especially in hospital mental health settings, lags behind expectations.

Traditional anatomy teaching relies on cadaveric dissection and 2D resources, which often require in-person attendance and may limit spatial understanding. Virtual reality (VR) provides an immersive, remote alternative that supports 3D visualization from home. Recent evidence suggests that while VR may yield comparable factual knowledge gains to 2D methods, its primary value lies in enhancing learner engagement, motivation, and perceived educational value.

People who are incarcerated face significantly higher health risks than the general population, yet deaths in custody remain underreported and poorly monitored by public health systems. Although the federal Death in Custody Reporting Act requires reporting of all deaths in correctional facilities to the US Department of Justice, reporting has been inconsistent, delayed, and often publicly inaccessible. Consequently, researchers have turned to press releases issued by correctional agencies as one of the few timely sources of information on deaths in custody. However, these press releases vary widely in content and structure, making standardized data extraction difficult. Crowdsourcing platforms such as Amazon Mechanical Turk (MTurk) may offer a faster, low-cost method for gathering data, but their utility in this setting remains untested.