Trust Drives LLM Adoption Among Chinese Healthcare
A multicenter, cross-sectional mixed-methods study in five Chinese tertiary hospitals in 2025 surveyed 240 health care professionals and 480 patients/caregivers, with 30 semistructured interviews, to assess willingness to adopt large language models (LLMs) for medical information and decision support. Researchers found trust was the dominant predictor (HCP OR 3.78; PCs OR 36.34), with perceived usefulness, digital readiness, prior use, and legal clarity also increasing willingness, and models achieving AUCs 0.83–0.96.
Key Points
- 1Identify trust as dominant predictor of LLM willingness (HCP OR 3.78; PC OR 36.34).
- 2Show perceived usefulness, digital readiness, and legal clarity significantly increase adoption intentions across user groups.
- 3Recommend role-sensitive interfaces, plain-language communication, and transparent accountability to build trustworthy LLM systems.
Scoring Rationale
Strong multicenter empirical evidence and actionable governance guidance; limited to Chinese tertiary settings and cross-sectional design.
Sources
Public references used for this report.
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