Abstract
BACKGROUND: Artificial intelligence literacy is essential for nursing students to become competent in navigating contemporary healthcare complexities and to ensure safe patient care. This literacy is needed urgently due to the rapid integration of artificial intelligence into the clinical, educational, and research domains. This integration requires immediate adaptation in order to mitigate ethical risks in tech-driven healthcare. OBJECTIVE: The aim of this study was to examine both the level and determinants of artificial intelligence literacy among nursing students. DESIGN: A cross-sectional study was conducted from April 1 to April 20, 2025. SETTINGS: This study was conducted at a public higher education institution that offered a Master of Science in Nursing program. PARTICIPANTS: Four hundred and twenty-three nursing students were enrolled in the study using convenience sampling. METHODS: Anonymous, self-administered online questionnaires were completed by the participants. Descriptive statistics including means, standard deviations, frequencies, and percentages were computed to characterize the sample. Multivariable linear regression analysis with adjustment for relevant covariates was then performed to examine potential associations between the variables. RESULTS: Moderate but uneven artificial intelligence literacy was observed among the nursing students, with a mean artificial intelligence literacy scale score of 59.67 (SD = 8.52). The ethics dimension was the least developed, in contrast to better performance in operational usage. Significant predictors of artificial intelligence literacy included frequency of artificial intelligence use, attitudes toward artificial intelligence, and digital literacy. Dimension-specific associations were identified and included correlation of awareness with gender, attitudes toward artificial intelligence, interest in artificial intelligence and digital literacy; usage with age, frequency of artificial intelligence use, and attitudes toward artificial intelligence; evaluation with attitudes toward artificial intelligence; and ethics with gender. CONCLUSIONS: This study identified key determinants that influenced the artificial intelligence literacy of nursing students and showed that artificial intelligence ethics was the most deficient domain among Chinese nursing cohorts. Notably, the frequency of artificial intelligence use, attitudes toward artificial intelligence, interest in artificial intelligence, and digital literacy collectively shaped the artificial intelligence literacy profiles of nursing students. Practical implications including developing and implementing targeted interventions such as artificial intelligence ethics workshops and digital literacy curricula are necessary to enhance ethical competencies and promote digital readiness. These interventions will equip nursing students for artificial intelligence -integrated healthcare environments and inform policy reforms in nursing education.