Why do I use generative artificial intelligence (GenAI) to seek health information? A perceptual perspective of GenAI users

Bibliographic Data

ID22088974
AuthorsHui Zhu (0000-0002-3159-8549, Anhui Medical University), Jianfei Ding (Anhui Medical University, corresponding author)
Year2026
Volume14
Pages1827765-1827765
Publication date2026-05-22
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2026.1827765
PMID42254636
OpenAlexW7162129750
LanguageEN
References cited59

Introduction: " initiative, as a core component of social security system optimization for improving residents' health welfare, furnishes a robust impetus for the integration of Generative Artificial Intelligence (GenAI) within the healthcare sector, particularly in the domain of health information provision, where GenAI is widely acknowledged to harbor substantial transformative potential. Nevertheless, empirical research specifically probing the modalities through which users adopt GenAI for health information seeking remains limited in extant scholarly literature. Methods: This study garnered primary data via a structured online survey and employed partial least squares structural equation modeling (PLS-SEM) to dissect the antecedent factors and underlying mechanisms governing users' health information seeking intention via GenAI, grounded in the perspective of user perceptions. Results: PLS-SEM results indicate that user perceptions of GenAI (perceived competence, perceived convenience, and perceived anthropomorphism) positively influence on both user trust in GenAI and subjective norms, which in turn positively affect users 'health information seeking intention through GenAI. Moreover, digital health literacy significantly moderates the relationship between user perceptions of GenAI and their health information seeking intention. Discussion: These findings yield valuable empirical insights for facilitating the optimized and scaled adoption of GenAI in health information services, enhancing the public health output of digital health policies, improving residents' health welfare, and further alleviating the operational burdens borne by traditional healthcare resources

Digital health · Empirical research · Health belief model · Health care · Health communication · Information seeking · Perception · Public health · Transformative learning · AI in Service Interactions · Artificial Intelligence in Healthcare and Education · Health Literacy and Information Accessibility

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