Validity and Reliability of the Medical Artificial Intelligence Readiness Scale, Korean Version: A Methodological and Cross-Sectional Study.

Abstract

This study aimed to translate and culturally adapt the Medical Artificial Intelligence Readiness Scale for Medical Students into Korean and to examine its validity and reliability among nursing students. The scale designed in this methodological and cross-sectional study was translated and adapted using standard procedures and validated with 317 nursing students in South Korea. Experts reviewed the content validity. Structural validity was examined through exploratory and confirmatory factor analyses. Construct validity was evaluated through hypothesis testing using an external criterion measure. Reliability was evaluated using Cronbach's alpha and the split-half method. The final Korean version of the Medical Artificial Intelligence Readiness Scale (K-MAIRS) comprised 15 items across four factors-cognition, ability, vision, and ethics-explaining 66.88% of the variance. The K-MAIRS can be a valid and reliable instrument for assessing artificial intelligence readiness among Korean nursing students. This instrument supports global initiatives to incorporate artificial intelligence competencies into nursing education using culturally tailored assessment tools. It also supports educators and institutions in designing targeted strategies for artificial intelligence education within nursing curricula that enhance nurses' preparedness in artificial intelligence-driven healthcare environments.