AI Chatbot Use Among Sexual and Gender Minority Youth: Utilization Patterns, Attitudes, and Implications for Culturally Affirming Digital Interventions

Background and Purpose

Generative AI chatbots are rapidly reshaping how young people seek health and social information, yet virtually no research examines their use among sexual and gender minority youth (SGMY). SGMY face disproportionate barriers to affirming, culturally competent support and may increasingly turn to AI tools to fill these gaps. This study examined: (1) rates and demographic patterns of AI chatbot use among SGMY across health, mental health, sexual health, and social support domains; (2) SGMY attitudes and perceptions toward AI chatbots; and (3) qualitative experiences, including perceived benefits and barriers.

Methods

From December 2025 to January 2026, 294 SGMY ages 14–21 completed a cross-sectional survey. Participants were recruited from an established research pool of sexual minority youth engaged in prior team studies. The survey assessed chatbot utilization for information or advice across eight domains (physical health, mental health, sexual health, dating/relationships, school, homework, friendships, and family), attitudes using Likert-scale agreement items, and open-ended qualitative feedback. Descriptive statistics and chi-square tests examined demographic patterns; qualitative responses were analyzed thematically.

Results

Half of SGMY (50.3%) reported using AI chatbots for information or advice, with 23.1% doing so at least weekly. No significant differences emerged by age, sexual orientation, urbanicity, region, or socioeconomic status. However, significant racial/ethnic disparities were found: utilization was highest among Asian (74%) and Black (69%) SGMY and lowest among white (49%) and multiracial (31%) youth. A marginally significant pattern showed higher use among males (55.0%) than females (48.7%). Despite frequent engagement, SGMY expressed deep skepticism: only 5% believed chatbots kept information private, 6% felt understood, and 9% trusted their accuracy. Yet many valued chatbots for being non-judgmental (34%), easier to talk to than adults (27%), and available and helpful when needed (21%). Across information-seeking domains, youth who used chatbots were 2–9 times more likely to endorse positive attitudes than non-users. Qualitative themes revealed a striking duality: some youth described chatbots as critical lifelines for sensitive needs—including confidential sexual health access and mental health crisis support—while many others cited accuracy failures, ethical and environmental impact concerns, and cultural incompetence.

Conclusions and Implications

SGMY are actively engaging with general-purpose AI chatbots despite significant reservations, particularly for health topics where affirming human support is limited or inaccessible. Racial/ethnic disparities in usage suggest potential digital health equity concerns. These findings establish a foundation for developing purpose-built, culturally affirming AI systems co-created with SGMY, digital safety experts, and social work clinicians—systems designed to address recognized limitations, such as privacy, environmental impact, and cultural competence. By centering the voices of SGMY, researchers and practitioners can bridge the gap between the urgent need for accessible health information and the justified skepticism of current generative AI technologies.