The predictive effect of nursing students' attitudes and acceptance towards artificial intelligence on their clinical competencies

Abstract

Background: AI integration in education is gaining interest, including in nursing, as students seek formal training on its healthcare applications and limitations. Aim: To evaluate the predictive effect of nursing students' attitudes and acceptance of artificial intelligence on their clinical competencies. Methods: This descriptive-correlational study was conducted at 2 universities (February–June 2024) with 441 nursing students. Full-time students in clinical practice participated; those absent or on leave were excluded. The Nursing Students Competency Scale, General Attitudes to Artificial Intelligence Scale, and Generative Artificial Intelligence Acceptance Scale were used. Descriptive statistics and linear regression were used. Results: The main factors affecting nursing students' clinical competence were “facilitating conditions,” “social influence,” and “negative attitudes” toward AI. A weak correlation was found between positive AI attitudes and acceptance, which explained 8.6% of the competency levels. Conclusion: Positive perceptions of AI may increase competence, while skepticism may deepen engagement and critical learning. Strategies to improve the acceptance and use of AI are crucial to maximize its benefits in nursing education and practice.