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

Abstract

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