ArticleFrontiers in public health2026
Ethical concerns toward medical artificial intelligence and acceptance intentions: a structural equation modeling analysis of the risk perception-trust pathway.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: With the deep integration of artificial intelligence (AI) into medical imaging, clinical decision-making, and health management, ethical concerns regarding medical AI among surveyed individuals have become increasingly prominent. This study examines the hierarchical structure of ethical concerns among surveyed participants and their associations with perceived risk, trust, attitude, and acceptance of medical AI. Methods: A questionnaire survey was conducted with 697 valid responses. SPSS and AMOS were used for reliability and validity assessment, confirmatory factor analysis, structural equation modeling, bootstrap analysis of indirect pathways, and robustness checks. Results: The results support a hierarchical multidimensional structure of ethical concern, with six first-order dimensions-privacy and data protection, responsibility and accountability, fairness and accessibility, safety and reliability, human-machine collaboration and humanistic care, and technical interpretability and transparency-collectively representing a higher-order ethical concern construct. All six dimensions are significantly associated with higher overall perceived risk of medical AI. Among them, human-machine collaboration and humanistic care ( Conclusion: Ethical concerns among surveyed participants constitute a hierarchical construct that is systematically associated with perceived risk of medical AI. Perceived risk, trust, attitude, and acceptance are interconnected through multiple statistical pathways, highlighting the complexity of medical AI evaluation processes among surveyed participants.
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