Generative AI dependency and self-perceived clinical decision-making in nursing students: A three-wave longitudinal study of metacognitive awareness as a mediator.
BACKGROUND Generative artificial intelligence tools are increasingly used in nursing education, but excessive reliance on externally generated reasoning may be associated with reduced cognitive engagement. Evidence remains limited on whether within-person changes in generative artificial intelligence dependency are prospectively associated with nursing students' metacognitive awareness and self-perceived clinical decision-making. OBJECTIVES To examine longitudinal within-person associations among generative artificial intelligence dependency, metacognitive awareness, and self-perceived clinical decision-making, and to test whether metacognitive awareness mediates these associations. DESIGN A three-wave prospective longitudinal panel study. SETTINGS Nursing schools at three medical universities in China. PARTICIPANTS A convenience sample of 687 undergraduate nursing students completed the baseline survey; 618 students completed the third wave, yielding a retention rate of 90.0%. METHODS Data were collected at the beginning, middle, and end of one academic semester. A random-intercept cross-lagged panel model was used to separate stable between-person differences from within-person fluctuations. Missing data were handled using full-information maximum likelihood. Common method bias was examined using Harman's single-factor test and an unmeasured latent method construct. RESULTS At the within-person level, higher generative artificial intelligence dependency was prospectively associated with lower metacognitive awareness at the subsequent wave (β = -0.18 to -0.21, p < .001). Higher metacognitive awareness was prospectively associated with higher self-perceived clinical decision-making (β = 0.22 to 0.25, p < .001). The indirect pathway from dependency to self-perceived clinical decision-making through metacognitive awareness was significant (standardized indirect effect = -0.045, 95% bootstrap confidence interval [-0.074, -0.019]), whereas the direct pathway was not statistically significant. CONCLUSIONS Generative artificial intelligence dependency was prospectively associated with students' self-perceived clinical decision-making through metacognitive awareness. Because the study was observational and the outcome was self-reported, the findings indicate an educational risk pathway rather than demonstrated clinical harm. Nursing educators may benefit from pairing artificial intelligence use with metacognitive scaffolding, verification routines, and reflective assessment.