JMIR Formative Research

There is evidence of rapid adoption of large language models (LLMs) in undergraduate medical education, with medical students using them to support their learning. This raises concerns about the accuracy of LLM-generated information that students are learning from. Retrieval-augmented generation (RAG), which grounds an LLM in curated materials, may be a strategy to improve the accuracy of this information.

Millions of people now use general-purpose large language models (LLMs) for mental health support, yet how these models respond to emotional disclosures and whether their responses functionally resemble established therapeutic practices remain uncharacterized.

Little is known about the composition and function of the social networks of adolescent and young adult survivors of cancer, despite the importance of social health for adolescent and young adult development. For adolescent and young adult survivors of cancer, social networks may be particularly important sources of support and coping. Understanding this group’s social health through understanding their social networks can inform intervention development to improve various facets of health and life productivity.

We recently completed the efficacy testing of an instructor-led yoga program for patients with thoracic cancer undergoing radiotherapy and their family caregivers. Translating an instructor-led intervention to a mobile app–based delivery model may facilitate the implementation of this yoga program in routine oncological clinical care.

Childhood obesity remains a public health concern in the United States, disproportionately affecting Hispanic/Latino and rural populations. Despite this disparity, there is a lack of culturally relevant programs specifically designed to reach this population. To address this gap, our team culturally adapted a technology-based childhood obesity intervention, Hispanic Family Connections (HFC), targeting Hispanic/Latino families living in rural areas. The intervention comprises 2 main components: interactive voice response (IVR) calls and a workbook with at-home activities to promote family engagement.

Discharge mobility after osteoporotic vertebral fractures is heterogeneous and difficult to predict at admission. Machine learning offers structured approaches for multiclass functional outcome prediction, but existing models predominantly address binary end points and report global performance metrics without explicit analysis of the error structure.

Online platforms are increasingly used to deliver training and implementation resources for large-scale, school-based physical activity initiatives, and understanding behavioral engagement with these platforms is important because it provides an early indicator of initiative uptake; yet, few studies have examined engagement during real-world scale-up.

Climate-related disasters increasingly affect community health, health care access, and disaster preparedness, particularly in disaster-prone Gulf Coast communities. Although climate dashboards have expanded access to environmental data, many function primarily as static repositories with limited integration of health data or operational decision support capabilities.

Nearly 1 in 5 students aged 12-18 years report being bullied in the United States. Both targets and students who witness bullying experience negative mental health outcomes. School-based programs are effective in decreasing negative outcomes associated with bullying; however, significant implementation barriers associated with in-person programs limit program adoption, fidelity, and sustainability. STAC-T (Stealing the Show; Turning it Over; Accompanying Others; Coaching Compassion; Technology Version), an interactive bullying bystander app, was developed to reduce implementation barriers. However, little is known about what will be required to successfully translate STAC-T into routine practice in schools. As a first step, we examined school personnel perspectives on school-specific implementation strategies that would be both highly important and feasible (“go-zone” strategies) for delivering STAC-T. Identifying specific implementation strategies can further support implementation and program outcomes. Although researchers have developed a taxonomy of 33 school-specific “go-zone” implementation strategies, there is no research examining these strategies specifically for STAC-T.

Digital health tools were widely adopted during the COVID-19 pandemic and helped to strengthen surveillance, risk communication, and health education. The government of Malawi launched the Malawi COVID-19 WhatsApp Chatbot on May 29, 2020. It remains unclear whether tools like this are acceptable and usable enough to warrant deployment in future epidemic responses.

The Dietary Approaches to Stop Hypertension Diet (DASH) diet supports heart health; yet, many find it difficult to follow in community settings. Mindful eating can improve adherence, but in-person programs are time-consuming and not always accessible. eHealth offers an accessible, scalable alternative that may increase engagement and compliance.

Difficulties with emotion regulation (ER) have widely been associated with the development and persistence of poor mental health, such as depression, anxiety, self-harmful thoughts, behaviors, and suicide attempts. Despite the importance of ER as a transdiagnostic risk factor, few interventions directly target ER. The impact of one such intervention, Purrble (a socially assistive robot; developed by Sproutel and Committee for Children), was recently evaluated when compared to treatment-as-usual (TAU) within a randomized controlled trial (RCT) with sexual orientation and gender identity minorities, that is, lesbian, gay, bisexual, transgender, queer, or questioning (LGBTQ+) youth, who had self-harm experiences. However, while RCTs are well suited to evaluating effectiveness, they offer limited insight into how participants engage with, integrate, and perceive the value of interventions, like Purrble, in their everyday lives. Consequently, complementary qualitative process evaluation is needed to fully understand participants’ experiences and contextualize trial outcomes.