JMIR Formative Research

Adolescents waiting for mental health treatment often experience significant unmet psychological needs, including severe psychological distress, increased use of maladaptive coping strategies, and feelings of abandonment. However, current wait time support offerings across the mental health sector are sparse and lack clear evidence of effectiveness.

Evidence-based psychological interventions are usually not accessed by marginalized groups such as refugees. Culturally adapted psychological interventions have reported larger effect sizes than nonadapted psychological interventions. However, the cultural adaptation of interventions is a lengthy process, entailing a challenge. One potential solution to overcome this challenge is the use of artificial intelligence (AI).

Digital health and connected technologies may support better health outcomes among older adults, including those with multiple chronic conditions or low engagement in health behaviors. However, initial experiences with technology, including during unboxing, setup, and first use, can influence emotional reactions and perceptions and can ultimately determine sustained, meaningful use. Older adults with low technology experience or poor health may be particularly vulnerable to frustration, stress, or abandonment of devices when early interactions are negative.

Stigmatized women’s health issues, such as polycystic ovary syndrome (PCOS) and endometriosis, are often marginalized or dismissed in traditional clinical settings. This drives individuals to seek peer support in anonymous online communities such as Reddit. While these digital platforms host critical discussions, they are often designed as static information repositories, failing to account for the complex emotional, temporal, and cultural dynamics that shape users’ support needs. There is a disconnect between the lived experiences of users—particularly feelings of clinical dismissal and the need for culturally specific advice—and the design of the sociotechnical systems they rely on.

Sleep quality declines with age and is a known contributor to multiple chronic health conditions, including Alzheimer disease. Emerging evidence suggests that certain electroencephalography (EEG) neural signatures measured during sleep may be predictive of cognitive decline in older adults. Sleep EEG signals are traditionally measured using bulky, rigid, and uncomfortable equipment in an unfamiliar laboratory setting, which can negatively impact sleep signals. Due to these limitations, sleep EEG data acquisition is typically limited to a single night.

The increasing reliance on patient portals for electronic health records has widened the digital health care access gap, particularly among low-income and Medicaid-insured populations. However, resources exist to assist low-income patients with portal enrollment; in obtaining a free smartphone; and, in New York, in obtaining low-cost internet. Automated bidirectional SMS text messaging offers a scalable and cost-effective strategy for identifying low-income patients’ digital health needs and eligibility for resources by using screening questions and providing tailored information on how to access available resources.

Curiosity plays a fundamental role in human learning, development, and motivation, and emerging evidence suggests that reduced curiosity is linked to poorer mental health outcomes, including depressive symptoms (DS). However, to date, the majority of curiosity research relies on self-report assessments and thus risks biased reporting. Virtual reality (VR), a novel tool increasingly used within mental health research and treatment, might represent a potent tool for offering ecologically valid insights into curiosity-driven behaviors while circumventing issues related to self-report assessments, including demand characteristics and recall bias.

Depression is a pervasive global mental health issue, yet access to trained professionals remains severely limited. With the rapid advancement of artificial intelligence (AI), digital tools are increasingly seen as a viable way to address this shortage. However, questions remain about how digital platforms for mental health care can be effectively designed.

HIV incidence has continued to increase among men who have sex with men (MSM) in Peru, despite intervention efforts. Addressing stigma, risky behaviors, and low medication adherence is key to reducing incidence rates. Ecological momentary assessment (EMA) allows for collection of discrete, real-time data on stigmatized, risky behaviors while reducing recall bias.

Conversational agents (artificial intelligence [AI]–based chatbots) offer a novel approach to health interventions by providing personalized, adaptive interactions that improve over time based on user engagement. In nutrition education, given the wide variation in knowledge, skills, and abilities across participants, AI-based chatbots have the potential to enhance accessibility, engagement, and behavior change. Food is Medicine (FIM) interventions, which aim to improve food security and diet quality among multicultural, at-risk populations, often face challenges related to sustained engagement and use.

The transition from adolescence to adulthood (18 to 25 years) is associated with an increased risk of suicidal ideation and behaviors. Suicide-focused cognitive behavioral therapies (CBTs) have been shown to significantly reduce suicidal ideation and behaviors but are not widely available to high-risk individuals. Digital therapeutics could improve access to these treatments.

This study develops an open-source large language model–based chatbot tailored for Korean health consultations. The chatbot was implemented using the retrieval-augmented generation (RAG) technique alongside metadata filtering to enhance its performance.