Generative AI vs. Human Sources for Sexual Health Information: Credibility, Trust, and Behavioral Intentions in a U.S. College Sample.

Limited access to comprehensive sexual health education has prompted a need to consider the utility of alternative strategies, such as generative artificial intelligence (genAI), for delivering accurate and accessible sexual health information. Although genAI tools can generate health information, less is known about how perceptions of the source of information shape evaluations of content (e.g., human vs. genAI). The present study examined whether college students' perceptions of sexual health information differed based on source attribution. Participants (N = 266) were students recruited from a single university in the southeastern USA in 2025. They were randomly assigned to conditions in which they were made to believe that three sexual health passages that were identical across conditions (sexual communication, body image, and sexual pleasure and safety) were written by genAI, an academic expert, a community health professional, or a peer/social media influencer. Across outcomes-including perceived accuracy and clarity, warmth and helpfulness, trustworthiness, self-efficacy, and willingness to act-genAI-attributed information was evaluated less favorably than identical information attributed to human sources. For willingness to act, there were differences in source effects across topics, such that effects were strongest for sexual pleasure/safety and weakest for sexual communication. Findings remained significant after controlling for genAI familiarity/use and attitudes. Findings indicate that evaluations of sexual health information depend not only on informational content but also on perceived source legitimacy, suggesting that AI-based tools may be the most effective when paired with human guidance to support trust and actionability.