Artificial intelligence adaptation in the future healthcare workforce: Evaluating literacy and anxiety levels.

Abstract

Background Increasing integration of artificial intelligence (AI) into clinical workflows necessitates assessing how future healthcare professionals adapt to these technologies. Objectıve This study aims to determine the artificial intelligence literacy and anxiety levels of students at a Vocational School of Health Services (VSHS) and to analyze the factors influencing these levels. Methods This cross-sectional and descriptive-predictive study invited 800 associate degree healthcare students, resulting in a final sample of 545 participants (response rate: 68.12%). Instruments included a Sociodemographic Form, the AI Literacy Scale (AILS), and the AI Anxiety Scale (AIAS). Results The mean age of participants was 20.41 ± 4.07 years. While 55.6 % of students reported partial knowledge of AI, only 44.4 % reported active use of AI-supported tools. In univariate analyses, gender ( p = .005 , η 2 = 0.015 ), prior AI knowledge ( p = .002 ), and active AI application use ( p = .007 ) showed statistically significant differences in anxiety levels. Total AI literacy was weakly negatively correlated with AI anxiety ( r = − 0.20 , p < .001 ). Multivariable regression analysis confirmed that the established model significantly predicted anxiety ( F 7 , 537 = 10.387 , p < .001 ), explaining 11.9 % of the total variance ( R 2 = .119 , Adjusted R 2 = .108 ). Within the multivariable model, cognitive literacy subdimensions—Awareness ( β = − .143 , p = .002 ), Evaluation ( β = − .116 , p = .027 ), and Ethics ( β = − .093 , p = .046 )—and male gender ( β = − .188 , p < .001