JMIR Formative Research

Despite promising developments in eHealth, a critical gap remains in understanding how to design and implement digital self-management interventions that effectively align with users’ needs and the complex context of recovery after treatment in the intensive care unit (ICU).

Hard flaccid syndrome (HFS) is a rare and poorly described andrological condition characterized by a persistent semirigid penis in the flaccid state and frequently accompanied by erectile dysfunction, sensory disturbances, urinary symptoms, and psychosocial distress. Due to the absence of standardized diagnostic and therapeutic guidelines, patients increasingly seek health information from AI-based tools such as ChatGPT. However, the reliability of such tools in rare diseases remains uncertain.

AI-powered digital mental health interventions (DMHIs) are increasingly deployed to support employee mental health, yet evaluations have focused predominantly on pretest-posttest symptom outcomes. The emotional states that unfold within real-world AI-assisted sessions remain largely uncharacterized, limiting understanding of how and when these tools may support users in distress.

Anhedonia is a core, clinically consequential feature of depression, and its motivational and behavioral features may be difficult to observe through self-report alone. Speech is an effortful, dynamic, and socially contingent behavior that may index the motivational disruptions central to anhedonia, but few studies have examined anhedonia specifically using a broad, multimodal set of voice features.

Conversational AI systems are increasingly used for web-based mental health support, yet evidence on sustained engagement, therapeutic alliance, and longitudinal outcomes remains limited. Baseline data from 527 self-referred users of the large language model–enabled chatbot Clare indicated high psychological distress and early development of a subjective working alliance.

Respiratory syncytial virus (RSV) is the leading cause of infant hospitalization in the United States. Although maternal RSV vaccination and infant RSV monoclonal antibody products are recommended to protect infants during their first RSV season, uptake has remained modest. Understanding how pregnant individuals make decisions about these products is critical for informing strategies that support timely immunization.

In resource-limited countries, most patients with type 1 diabetes (T1DM) use basal-bolus insulin therapy. Optimal dosing requires matching insulin to carbohydrate intake, premeal blood glucose levels, and physical activity—a complex process prone to error, particularly for patients with limited health literacy.

Sub-Saharan Africa faces challenges with collecting maternal and perinatal data because of poor documentation in paper-based systems and inadequate infrastructure for digital utilization. The electronic health record system-ULTRA (EHRS-ULTRA) was developed and piloted in the Kilimanjaro region from October 2022 to August 2024 to improve data management.

Miners are essential rural workers who may work in close proximity to others in inadequately ventilated environments and cannot telecommute or work flexible hours, rendering them vulnerable to SARS-CoV-2 transmission. Exposure to particulate air pollution may also be associated with an increased risk of SARS-CoV-2 infection and mortality. Chronic exposure to particulate matter causes overexpression of the alveolar angiotensin-converting enzyme 2 receptor, facilitating SARS-CoV-2 entry into lung epithelial cells.

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Each year, family caregivers help the 2 million patients newly diagnosed with cancer manage their symptoms; however, few interventions have been developed and proven efficacious to enhance their symptom-support role. The recent expansion of electronic patient-reported outcomes (ePROs), including remote symptom monitoring, presents an opportunity to explore novel approaches to supporting caregiver symptom management by leveraging patient ePRO data.

Atrial fibrillation (AF) is one of the most common arrhythmias and is associated with multiple risk factors, including stroke and heart failure. Therefore, it is important that accurate and comprehensive educational resources on AF are available. Artificial intelligence (AI) platforms such as Google Gemini and ChatGPT are emerging tools for medical education. To our knowledge, this is the first study to assess the quality of these platforms for AF education.