JMIR Research Protocols

Crisis helplines are a vital component of a robust public health approach to suicide prevention as they are often free, accessible, and provide immediate support to individuals in distress. AI presents an opportunity for novel applications to support and improve crisis line services across a variety of functions, including assessing suicide risk, identifying issues, tracking responder behaviors, and providing prompts and reminders. However, the use of AI in the crisis sector also raises critical questions regarding safety, ethics, privacy, efficacy, feasibility, and acceptability among interest holders. The extent to which AI is currently being explored and implemented in crisis line contexts is unknown.

Survivors of childhood cancer have an increased risk of cardiovascular disease (CVD), but that risk may be reduced by healthy lifestyle behaviors.

Progressive neurological diseases (PNDs) such as Parkinson disease and multiple sclerosis cause profound motor and nonmotor symptom burdens that significantly impair health-related quality of life. Beyond physical challenges, patients face profound psychospiritual distress driven by prognostic uncertainty, loss of autonomy, and existential concerns. While palliative care can address these multidimensional needs, it remains underused in neurological populations, where conventional care predominantly focuses on motor symptom management.

Objective structured clinical examinations (OSCEs) are a common assessment tool used to evaluate the application of clinical knowledge, clinical reasoning, competency-based performance, and professional behavior in health care education. Their development and facilitation are often included under the broader umbrella of simulation pedagogies. Despite their widespread adoption and the availability of guidelines, variability exists in approaches specific to OSCE development, implementation, and evaluation.

Children’s mental health is a critical public health priority, with approximately 8% of children aged 10 years or younger experiencing mental, behavioral, or emotional disorders. Despite evidence supporting early intervention, access to mental health services remains limited, particularly for socioeconomically disadvantaged populations. Art-based interventions have emerged as promising approaches to support mental health and socioemotional development. However, significant gaps persist in understanding their efficacy, scalability, and long-term impact.

Heart disease remains a leading cause of death for women in the United States. Despite this burden, awareness that heart disease is the leading cause of death among women declined from 65% in 2009 to 44% in 2019, with the largest declines observed among Hispanic, Black, and younger women. Thus, innovative, scalable, and cost-effective educational strategies are needed to improve women’s awareness of heart attack symptoms and appropriate care-seeking behaviors.

Advance care planning (ACP) involves proactive communication about end-of-life care preferences among patients, families, and health care providers. In Chinese culture, older adults commonly delegate such care decisions to adult children, yet family reluctance—rooted in beliefs that aggressive treatments are beneficial—remains a major barrier to ACP participation. Existing interventions improve documentation and communication through education, hypothetical scenarios, and physician engagement, but few target family members specifically or use a theoretical framework. The transtheoretical model is particularly underused for assessing family readiness. Infographics, videos, and large language models demonstrate strong potential for engagement, highlighting the need for tailored, theory-driven family empowerment interventions.

Orthokeratology is a nonsurgical corneal reshaping technique used for the temporary correction of myopia and for myopia control. Nighttime use induces central epithelial thinning and midperipheral thickening, altering corneal asphericity and higher-order aberrations.

Idiopathic multicentric Castleman disease (iMCD) is a rare lymphoproliferative disorder that is associated with a broad range of symptoms, including constitutional, gastrointestinal, neuropsychiatric, dermatologic, respiratory, and hematologic or lymphoreticular problems. These broad symptoms can impact the daily lives of people living with iMCD, creating a high symptom burden. Despite this, no robust, disease-specific patient-reported outcome measure (PROM) for subjective iMCD symptom burden exists. This limits accurate symptom monitoring, impacts sensitive end point selection in clinical trials, and represents a regulatory gap in patient-centered evidence generation when evaluating iMCD treatments.

Large language models (LLMs) are increasingly used in health care by nonprofessionals (ie, individuals without formal training in health-related professions). These applications must be evaluated in an appropriate manner to prevent misinformation and harmful decisions. To date, guidance to evaluate LLM-based applications for nonprofessional users remains limited and fragmented, leaving researchers and developers without a scientifically grounded set of quality dimensions, metrics, and measurement tools to guide them.

Patient-centered care, emphasizing autonomy and shared decision-making, is essential in palliative cancer care. The increasing prevalence of cancer requires optimized health care use, and given patients’ preference for home-based care, traditional time-based follow-up appointments may not adequately address their needs. We have developed a digital patient-controlled follow-up intervention at the acute palliative care unit in Norway. The digital app is integrated into the existing national health service platform, MyHealth, and facilitates symptom monitoring, self-management support, and patient-controlled access to palliative care services.

Hypermobile Ehlers-Danlos syndrome (hEDS) is a multisystemic hereditary connective tissue disorder characterized by generalized joint hypermobility, chronic pain, and a complex spectrum of comorbidities. Diagnosis relies on complex clinical criteria, leading to poor recognition by clinicians and fragmented care. Consequently, patients navigate the health care system for an average of 22.1 years before receiving a diagnosis, which substantially delays appropriate management. Electronic health records (EHRs) contain rich longitudinal data that, if systematically analyzed, could identify patients whose clinical histories are highly suggestive of hEDS.