Exploring factors associated with nursing students’ artificial intelligence literacy: insights from a national mixed methods study

BACKGROUND: Integrating artificial intelligence (AI) into healthcare is rapidly expanding, yet research on nursing students' AI literacy (AIL) remains limited. This study assessed AIL levels, identified factors associated with AIL, and explored students' perceptions of AI use. METHODS: The mixed-methods study used a non-probability snowball sampling technique, involving 383 undergraduate nursing students in Türkiye, and utilized the Descriptive Characteristics Form and the Artificial Intelligence Literacy Scale (AILS). Quantitative analyses included t-tests, ANOVA, Pearson correlations, and multiple linear regression. Qualitative data underwent thematic analysis. RESULTS: The mean age of participants was 21.52 (SD ± 3.31; range, 18-40), and 83.3% of them were female. Participants' mean AILS score was 110.80 (SD ± 40.98; range = 31-216) with 41.22 ± 19.67 for technical understanding, 40.49 ± 15.57 for critical appraisal, and 29.09 ± 10.68 for practical application. Higher comfort with new technologies (β = 0.352; t = 7.06; p < 0.001) and having witnessed/experienced ethical concerns (β = 0.094; t = 1.98; p = 0.048) were significantly associated with higher AIL. Seven themes were identified: (1) Support and Convenience, (2) Time Management, (3) Learning and Academic Development, (4) Ethical and Security Concerns, (5) Misinformation and Trust, (6) Laziness and Dependency, and (7) Creativity and Thinking. CONCLUSION: Enhancing AIL skills among nursing students is essential for the ethical and rational use of AI. Educators should guide nursing students to develop strategies to improve their technical, appraisal, and practical AIL skills. The present study may contribute to identifying educational strategies to support nursing students' readiness for AI in nursing education. TRIAL REGISTRATION: Not applicable.