LLMs for health: Perceived benefits, risks, intention to use AI chatbots, and willingness to self-disclose across sensitive health topics

• URL: http://arxiv.org/abs/2607.09253v1
• Date: Fri, 10 Jul 2026 10:07:35 GMT
• Title: LLMs for health: Perceived benefits, risks, intention to use AI chatbots, and willingness to self-disclose across sensitive health topics
• Abstract summary: This study examines the role of topic type and individual characteristics on perceived benefits and risks.<n>We conducted an online experiment with a 2 (topic type: physical versus psychological, between-subjects) x 2.<n> participants reported higher usage intentions for low-sensitive topics compared to high-sensitive topics.
• Score: 1.4898183413499773
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: AI chatbots are increasingly used for answering health-related questions. This study examines the role of topic type discussed with an AI chatbot and individual characteristics on perceived benefits and risks, intention to use an AI chatbot, and willingness to self-disclose health information. We conducted an online experiment with a 2 (topic type: physical versus psychological, between-subjects) x 2 (topic sensitivity: low versus high, within-subjects) mixed design among a Dutch representative sample (N = 1,388). Results showed that perceived benefits were positively associated with intention and willingness to self-disclose, while perceived risks were negatively associated. Moreover, participants reported higher usage intentions for low-sensitive topics compared to high-sensitive topics. Furthermore, perceptions, intention, and willingness to self-disclose varied by individual characteristics. Overall, our findings suggest that intentions to use AI chatbots and self-disclosure of health-related information are primarily related to perceived benefits and risks and to personal characteristics rather than to topic type.

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