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Examining the relationship between nursing students' general attitudes toward artificial intelligence and their self efficacy in clinical performance

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2025
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Abstract Aim: This study was conducted to examine the relationship between nursing students' general attitudes toward artificial intelligence and their self efficacy in clinical performance. Material and Method: The study was conducted between 02 December 2024 and 31 January 2025 with 338 nursing students enrolled in the second, third, and fourth years at Dicle University Atatürk Faculty of Health Sciences, Department of Nursing. No sampling method was employed; the study was applied to students who had successfully completed at least one clinical practice during the specified period and voluntarily agreed to participate. Data were collected using the "Descriptive Information Form", the "General Attitudes toward Artificial Intelligence Scale (GAAIS)", and the "Self-Efficacy in Clinical Performance Scale (SECP)". Results: It was determined that the mean age of the nursing students was 21.73 ± 2.38 years and that 68.9% of them were female. Among the students, 68.9% had previously used an artificial intelligence application, 74.6% reported being ready for clinical practice, 48.5% had used artificial intelligence in clinical practice, and 56.2% believed that artificial intelligence would contribute to clinical skills. In our study, the mean total score of the General Attitudes toward Artificial Intelligence Scale (GAAIS) was 65.95 ± 10.48, and the mean total score of the Self-Efficacy in Clinical Performance Scale (SECP) was 69.45 ± 15.44. A statistically significant, weak positive correlation was found between the mean scores of GAAIS and SECP (r = 0.14; p = 0.01). Conclusion: This study revealed that as nursing students' general attitudes toward artificial intelligence (AI) increased, their self-efficacy in clinical performance also improved. It was found that factors such as gender, knowledge of AI, the belief that AI contributes to clinical skills, and following AI applications in nursing significantly affected both their attitudes toward AI and their perceptions of self-efficacy in clinical performance. These findings suggest that the use of AI technologies in nursing education may support the development of clinical skills. Therefore, the integration of AI into nursing education can be recommended. Key Words: Nursing, Students, Artificial Intelligence, Clinical Performance, Self-Efficacy

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Muhammed Ali Duman

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Muhammed Ali Duman (Master Thesis). Examining the relationship between nursing students' general attitudes toward artificial intelligence and their self efficacy in clinical performance, 2025, Dicle University.

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