Medical undergraduate students' readiness and anxiety toward artificial intelligence: a systematic review and meta-analysis
Abstract
Background: Artificial intelligence (AI) is transforming healthcare, yet medical undergraduates often lack adequate AI training. This study systematically evaluated their readiness and anxiety toward AI.
Methods: We searched seven databases from the creation date of databases to July 2025. Studies using validated scales (MAIRS-MS or AIAS) to assess medical undergraduates' AI readiness or anxiety were included. Subgroup analysis comparing AI readiness between clinical and dental students and nursing students (including midwifery) was performed.
Results: A total of 25 studies were included, of which 2 studies reported both MAIRS-MS scores and AIAS scores, and 1 study reported only MAIRS-MS and AIAS total scores without subdimension scores. The AI readiness analysis indicated a high level in the Ethics subdimension, but only moderate levels in the total score as well as the Cognition, Ability, and Vision subdimensions. For AI Anxiety, the Learning subdimension scored low, whereas the overall score and the Job replacement, Sociotechnical blindness, and AI configuration subdimensions scored moderate. Subgroup analysis showed that nursing students' overall MAIRS-MS scores, as well as their scores in the Ability (p < 0.001), Vision (p = 0.0486), and Ethics (p = 0.0134) subdimensions, were significantly higher than those of clinical and dental students. However, due to only 1 study investigating AI anxiety in clinical and dental students, subgroup comparisons for AIAS scores were…
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Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
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