Assessment of Artificial Intelligence Attitudes, Literacy, and Self-Efficacy in Nursing Students
Perspectives in Psychiatric Care, cilt.2026, sa.1, 2026 (SCI-Expanded, SSCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 2026 Sayı: 1
- Basım Tarihi: 2026
- Doi Numarası: 10.1155/ppc/1496081
- Dergi Adı: Perspectives in Psychiatric Care
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, CINAHL, MEDLINE, Psycinfo, Academic Search Ultimate (EBSCO), Biomedical Reference Collection: Corporate Edition (EBSCO), Health Research Premium Collection (ProQuest), Pharma Collection (ProQuest), Psychology & Behavioral Sciences Collection (EBSCO)
- Anahtar Kelimeler: AI literacy, artificial intelligence, nursing student, self-efficacy
- Kocaeli Üniversitesi Adresli: Evet
Özet
Introduction: Nursing students’ AI self-efficacy and AI literacy influence their attitudes toward artificial intelligence (AI). This, in turn, may affect the use of AI in nursing practices. In this study, nursing students’ attitudes toward AI, AI literacy, and AI self-efficacy levels were examined. Methods: The study was designed as a descriptive and cross-sectional type. This study was conducted with 400 students enrolled in the nursing department. The sample was selected using a convenience sampling method based on voluntary participation. Data were collected between December 2024 and January 2025 using the Descriptive Information Form, the General Attitude Toward Artificial Intelligence Scale, and the Artificial Intelligence Literacy. Results: The mean score of students’ positive attitude toward AI was calculated as 44.65 ± 7.09, and the mean score of students’ negative attitude was calculated as 24.49 ± 5.88. While the total score mean of the AI literacy scale was 3.61 ± 1.17, the total score mean of the AI self-efficacy scale was 3.34 ± 0.61. It was determined that those studying in the 4th grade had a more positive attitude toward AI. In addition, positive attitude toward AI and AI literacy were among the variables predicting AI self-efficacy. Conclusions: While nursing students’ positive attitudes toward AI are at a high level, their literacy and self-efficacy are at a moderate level. It is thought that eliminating students’ lack of knowledge about AI will positively affect their AI self-efficacy. Implications for Practice: Despite the growing interest in AI, there are substantial gaps in nursing education. Integrating AI tools into undergraduate education will reduce the gap between theoretical knowledge and clinical practice. By bridging the gap between theoretical learning and clinical applications, it can support the development of students’ critical and clinical decision-making skills and help them become more competent and have stronger self-efficacy in using AI in patient care. It is necessary to improve nurses’ ability to use AI while providing patient care in different fields (psychiatric nursing, oncology nursing, and so on). This should be provided to nursing students during their undergraduate education.