Cross-sectional survey evaluates AI literacy in nursing students, revealing key demographic and educational climate influences.
Background: Artificial intelligence (AI) is transforming health care, necessitating essential AI literacy among nursing students. Understanding their literacy levels and influencing factors is essential for designing teaching strategies and learning environments that promote effective AI integration. Objective: To assess AI literacy among nursing students and identify associated demographic, experiential, and educational climate factors. Methods: A cross-sectional survey was conducted among 2430 nursing students from 14 institutions in Hunan, China. Data were collected on demographics, AI use and training, perceptions of educational climate, and AI literacy. Analyses included descriptive statistics, correlations, and multiple linear regression. Results: Nursing students showed moderate AI literacy. Higher scores were linked to male gender, bachelor-level education, advanced year level, greater AI interest and usage, prior training, and a positive educational climate. The regression model explained 38.2% of the variance ( R 2 = 0.382, P < .001). Conclusion: Targeted AI education and a supportive learning environment can enhance nursing students’ literacy for AI integration in clinical practice.
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Jiang et al. (2025) studied this question.
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