Examining the relationship between nursing students' readiness, literacy and attitudes toward medical artificial intelligence

Abstract

Aim: This study examined the relationships among nursing students' readiness for medical AI, AI literacy and their attitudes toward AI within digitalization in healthcare. Background: The rapid integration of AI into healthcare highlights the need to assess future professionals' preparedness. Nursing students' readiness, literacy and attitudes toward medical AI are key to its effective and ethical use. Design: This study is a cross-sectional, descriptive and correlational research conducted to assess nursing students' readiness for medical AI, AI literacy and their attitudes toward AI in Turkiye. Methods: Using an online survey, this cross-sectional, descriptive and correlational study was conducted with 438 nursing students from various universities in Turkiye. Data were collected using the Medical Artificial Intelligence Readiness Scale (MAIRS), the Artificial Intelligence Literacy Scale (AILS) and the General Attitudes Toward Artificial Intelligence Scale (GAAIS). Results: The results revealed that student nurses reported high familiarity with AI (88.6 %). MAIRS was significantly correlated with AILS (r = .50), Positive GAAIS (r = .53) and inversely with Negative GAAIS (r = -.17). AILS subdimensions Awareness, Usage, Evaluation and Ethics significantly predicted MAIRS (R-2=.25, p < .001). Furthermore, Usage and Evaluation significantly predicted Positive GAAIS (R-2=.24, p < .001), while Usage, Evaluation and Ethics significantly predicted Negative GAAIS (R-2 =.06, p < .001). Conclusion: The findings underscore the importance of enhancing nursing students' AI literacy and ethical competence to foster readiness for medical AI. Education programs should incorporate targeted content to improve students' abilities to evaluate and ethically apply AI in healthcare settings.