Abstract
OBJECTIVE: To systematically investigate the key determinants influencing health information quality in social media environments and elucidate their hierarchical relationships, thereby providing evidence-based guidance for quality improvement. METHODS: This study employed an innovative integration of meta-ethnography and Decision-Making Trial and Evaluation Laboratory-Interpretive Structural Modeling (DEMATEL-ISM) methodologies. Through systematic extraction and multi-dimensional analysis of influencing factors-including centrality metrics, causal relationships, and hierarchical structures-we developed a comprehensive mechanism model clarifying factor interactions and their cumulative impacts on health information quality enhancement. RESULTS: Our analysis identified 18 critical factors affecting health information quality, which were categorized into six distinct hierarchical levels through rigorous computational modeling. The results revealed complex cross-level interactions and mutual influences among these determinants. Nine core factors emerged as pivotal: information accuracy, authority orientation, platform reputation, creator expertise, information utility, health information literacy, content originality, source authority, and health concepts. CONCLUSION: The findings establish a hierarchical quality improvement framework, suggesting that targeted interventions focusing on the nine core factors can significantly enhance health information quality in social media ecosystems. This study provides both theoretical foundations and practical insights for multi-stakeholder collaborative governance in digital health communication.