Abstract
The rising digital technology of artificial intelligence (AI) and large language models (LLM) has opened new opportunities for personalized support in healthcare contexts. This study systematically retrieved 2,197 citations through database searching and synthesized findings from 21 empirical quantitative studies using both systematic review and meta- analytic techniques. Relying on theoretical foundations, including the Computers Are Social Actors (CASA) paradigm, social presence theory, social penetration theory, and social exchange theory, this article proposes an integrated theoretical model. Through meta- analysis, the study quantitatively summarizes the existing knowledge on self-disclosure and critically identifies the major factors that contribute to self-disclosure in human-AI interactions in healthcare contexts, as well as the potential AI-related and health-related psychological outcomes. Contributions and limitations are discussed.
| Original language | English |
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| Publication status | Published - Jun 2025 |
| Event | 75th Annual International Communication Association Conference, ICA 2025 - Hyatt Regency Denver, Denver, United States Duration: 12 Jun 2025 → 16 Jun 2025 https://www.icahdq.org/mpage/ICA25 (Conference website) https://cdn.ymaws.com/www.icahdq.org/resource/resmgr/conference/2025/ICA25_Abstracts_Program.pdf (Conference program) |
Conference
| Conference | 75th Annual International Communication Association Conference, ICA 2025 |
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| Country/Territory | United States |
| City | Denver |
| Period | 12/06/25 → 16/06/25 |
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