Translation and psychometric validation of the Medical Artificial Intelligence Readiness Scale (MAIRS-MS) for Chinese medical students

作者：Xiameng Chen, Yang‐Yi Chen, Yuhuan Xie, Linan Cheng · 发表于：BMC Nursing · 年份：2025 · DOI：10.1186/s12912-025-03852-w · 被引用次数：5 · 研究领域：Artificial Intelligence in Healthcare and Education、Ethics and Social Impacts of AI、AI in Service Interactions

BACKGROUND: With the rapid integration of artificial intelligence (AI) into medical education, assessing medical students' readiness has become critical. This readiness encompasses not only familiarity with AI tools but also the ability to apply, evaluate, and ethically reflect on them. Despite international advances, China currently lacks a validated instrument to systematically evaluate medical students' readiness for medical AI. Therefore, this study aimed to translate, culturally adapt, and evaluate the psychometric properties of the Medical Artificial Intelligence Readiness Scale (MAIRS-MS) for Chinese medical students. METHODS: The MAIRS-MS was translated into Chinese following Brislin's guidelines, with subsequent cultural adaptation informed by expert consultation. A pilot study was then conducted with 30 medical students to refine the Chinese version (C-MAIRS-MS). A cross-sectional survey was conducted among 516 undergraduate medical students from March to May 2025. The psychometric properties of the C-MAIRS-MS were evaluated through exploratory factor analysis (EFA), confirmatory factor analysis (CFA), Cronbach's α coefficient, Spearman-Brown split-half reliability, and the intraclass correlation coefficient (ICC). RESULTS: The C-MAIRS-MS included 22 items with scale content validity index (S-CVI) of 0.982. EFA extracted four factors explaining 65.274% of the total variance, with factor loadings ranging from 0.508 to 0.881. CFA results indicating that the revised 4-...