J Eval Clin Pract. 2026 Apr;32(3):e70421. doi: 10.1111/jep.70421.
ABSTRACT
AIM: This study aims to evaluate the mediating role of artificial intelligence (AI) anxiety in the effect of nurses' attitudes toward health technologies on their readiness for medical artificial intelligence (MAI).
METHODS: A cross-sectional design was used. The study was conducted between May and September 2023, involving 844 nurses at a university hospital in Türkiye. Working units were used as strata, and a proportionally stratified sample of 265 nurses was selected; convenience sampling was then applied within each stratum. Data were collected using the Health Personnel Health Technologies Assessment Attitude Scale, the Artificial Intelligence Anxiety Scale, and the Medical Artificial Intelligence Readiness Scale. Pearson correlation analysis and mediation analyses were performed. The mediation effect was tested using Model 4 in PROCESS Macro (version 4.2) in SPSS.
RESULTS: Participants were predominantly female (78.9%), with a mean age of 31.30 ± 7.32 years. Nurses exhibited positive attitudes toward health technologies, moderate AI anxiety, and high readiness for MAI. Attitudes toward health technologies were significantly associated with readiness for MAI (B = 0.3315, 95% CI [0.1677, 0.4989], p < 0.001) and AI anxiety (B = -0.2205, 95% CI [-0.3635, -0.0815], p < 0.05). However, AI anxiety was not significantly associated with readiness for MAI (B = 0.0966, 95% CI [-0.0585, 0.2604], p > 0.05). Mediation analysis indicated that AI anxiety did not significantly mediate the relationship between attitudes and readiness.
CONCLUSION: Positive attitudes toward health technologies are associated with higher readiness for MAI; however, AI anxiety did not function as a mediator in this relationship. These findings underscore the importance of integrating structured AI education, ethical awareness, and digital literacy training into nursing curricula and continuing professional development programs to support preparedness for AI-supported healthcare environments.
PMID:41911439 | DOI:10.1111/jep.70421