인공지능 시대의 의료정보 소통: 일반인의 리터러시 실태와 국제 연구동향

초록

Background : The rapid proliferation of Large Language Models has transformed health information dissemination, yet empirical evidence regarding public perception and utilization remains scarce. This study investigates the current status of health information literacy and global research trends in the AI era to address the gap between technological potential and public acceptance. Methods : A mixed-methods design was employed, integrating a cross-sectional online survey of 208 Korean adults with a bibliometric analysis of 275 PubMed-indexed studies (2019–2025). To identify the gap between technological potential and public reality, we synthesized empirical data on user behavior with structural thematic clusters derived from global research trends. Results : Bibliometric analysis revealed an exponential surge in research since 2023, primarily focusing on AI-based patient education and information safety. However, the survey showed significant structural asymmetry: while 79.8% of participants used internet portals, trust in AI models (2.95 ± 1.02) was notably lower than in healthcare providers (4.57 ± 0.61). Furthermore, 93.2% of respondents expressed a critical need for services translating medical terminology into everyday language. Despite low perceived reliability, 54.3% reported changing lifestyle habits based on online information, and 38.9% prioritized internet searches over emergency services during crises. Conclusions : Health information literacy must transition from passive understanding to an active “verification literacy” that empowers users to critically evaluate AI-generated content within a user-centric education system.

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