Expanding the Scope of Ai Readiness: Validation of the Mairs Scale Among Dental, Nursing, and Midwifery Students

Background Artificial intelligence (AI) is rapidly transforming healthcare. However, validated tools to assess AI readiness in non-medical health disciplines remain scarce. This study aimed to adapt and validate the MAIRS scale among dental, nursing, and midwifery students. Methods A cross-sectional study involving 376 students was conducted. Exploratory and confirmatory factor analysis, along with structural equation modeling, were used to validate the adapted scale. Internal consistency and predictive validity were evaluated. Results The adapted MAIRS scale retained a four-factor structure with excellent reliability (Cronbach’s α = 0.89–0.92). AI Usage Awareness was the strongest predictor of AI Knowledge Level (β = 1.05, p < 0.001). Students demonstrated high awareness and ethical concern but limited technical understanding. Conclusion The MAIRS scale is valid and reliable for assessing AI readiness in non-medical health education. Findings highlight the urgent need to integrate AI education into undergraduate health curricula.