Exploring AI literacy, attitudes toward AI, and intentions to use AI in clinical contexts among healthcare students in Korea: a cross-sectional study

Abstract

As artificial intelligence (AI) becomes increasingly integrated into healthcare, AI literacy has emerged as an essential competency for future healthcare professionals. However, research exploring healthcare students’ AI literacy remains limited. This study aimed to assess AI literacy among healthcare students and examine its associations with attitudes toward AI, intention to use AI in clinical contexts, and students’ characteristics (interest in AI and previous AI training) within a Korean context. A cross-sectional survey was conducted at a Korean medical school. Of 690 invited students, 91 (67 medical, 24 nursing) participated. Variables were measured using the Scale for Non-Expert AI Literacy (SNAIL), the General Attitudes toward Artificial Intelligence Scale, and intention to use AI items adapted from the Technology Acceptance Model. Analyses included confirmatory factor analysis, descriptive statistics, t-tests, and correlation analyses. After removing seven items, the validated 24-item SNAIL-KR was used for analysis. Students demonstrated slightly below-average AI literacy, with technical understanding scoring the lowest. AI literacy was positively correlated with positive attitudes toward AI and intention to use AI. Interest in AI was more strongly correlated with AI literacy than prior AI training. No significant differences were found by gender, year of study, or major. The findings highlight the urgent need to incorporate AI literacy into healthcare curricula in a consistent and systematic manner. Fostering healthcare students’ positive attitudes toward and interest in AI is also crucial for enhancing AI literacy.

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