Cross-Cultural adaptation and psychometric evaluation of the Chinese version of the artificial Intelligence attitude scale for nurses

Background With the rapid application and development of artificial intelligence technology in the global nursing field, nurses' attitudes towards it have become a key factor influencing the implementation and effectiveness of the technology. The artificial Intelligence attitude scale in nurses (AIASN) compiled by Turkish scholars has good reliability and validity, but it needs to be cross-cultural adapted and verified in different cultural backgrounds. Purpose The localization and cross-cultural adaptation of AIASN were carried out, and its psychometric characteristics were tested among Chinese clinical nurses, providing a standardized assessment tool for AI-related research and practice in the domestic nursing field. Methods Following the Beaton guidelines for cross-cultural adaptation, the Chinese version of the AIASN was developed through a process comprising forward translation, synthesis, back-translation, expert review, pre-testing, and finalization. By using the convenience sampling method, a questionnaire survey was conducted among 450 clinical nurses in a tertiary grade A hospital in Liaoning Province from October to November 2025. The validity of the scale was tested through content validity, construct validity, convergent validity and discriminant validity, and the reliability of the scale was tested through internal consistency reliability and test-retest reliability. Results The Chinese version of AIASN consists of 32 entries, covering four dimensions: nursing care, organization, ethics, and artificial intelligence readiness. Item analysis showed that the discrimination of all items was good, with CR values all > 3.000 and the correlation item-total score all > 0.400. The content validity index S-CVI = 0.941, and I-CVI = 0.875-1.000. Exploratory factor analysis extracted four factors, and the cumulative variance interpretation rate was 72.524%. Confirmatory factor analysis showed good model fitting, CMIN/DF = 2.110, RMSEA = 0.070, CFI = 0.920, TLI = 0.913. The overall Cronbach's α coefficient of the scale was 0.908, and the McDonald's ω coefficient was 0.877. The test-retest reliability ICC was 0.925 (95% CI: 0.874–0.963), indicating that the scale has high reliability and stability. Conclusion After cross-cultural adaptation, the Chinese version of AIASN has good reliability, validity and construct stability. It is suitable for evaluating the attitudes of Chinese clinical nurses towards artificial intelligence and can provide reliable tool support for nursing management, education and policy research.