Aug 2026· Sakarya Üniversitesi Holistik Sağlık Dergisi· 0 citations· 27 references
TL;DR
The findings underscore the notion that nursing students’ perceptions of artificial intelligence are shaped by a complex interplay of emotional, cognitive, and behavioral factors, which may facilitate the ethical and efficient integration of artificial intelligence into nursing practice.
Abstract
Objective: As the growing use of artificial intelligence in healthcare creates both new opportunities and emerging concerns for nursing practice, this study aimed to examine nursing students’ attitudes toward artificial intelligence and to explore the extent to which AI-related anxiety and technological dependency predict these attitudes.Methods: A descriptive, cross-sectional, and correlational design was employed with a sample of 373 nursing students studying at a public university in Türkiye. The data were collected using three instruments: the General Attitudes Toward Artificial Intelligence Scale, the Artificial Intelligence Anxiety Scale, and the Artificial Intelligence Dependency Scale. The statistical analyses encompassed a range of methodologies, including descriptive measures, Pearson correlation coefficients, and multiple regression models.Results: The mean score for the General Attitudes toward Artificial Intelligence Scale Positive Attitudes subscale was 42.17 ± 8.71, while the mean score for the Negative Attitudes subscale was 24.44 ± 6.69. The mean total scores for the Artificial Intelligence Anxiety Scale and the Dependence on Artificial Intelligence Scale were 73.57 ± 25.54 and 12.39 ± 4.28, respectively. Multiple regression analyses revealed that AI-related anxiety and dependency significantly predicted positive attitude scores (R² = 0.060, F = 11.722, p < 0.001) and negative attitude scores (R² = 0.349, F = 98.985, p < 0.001).Conclusions: The findings underscore the notion that nursing students’ perceptions of artificial intelligence are shaped by a complex interplay of emotional, cognitive, and behavioral factors. In accordance with a holistic nursing framework, incorporating artificial intelligence into education should extend beyond the acquisition of technical skills to encompass the maintenance of core care values, such as empathy, ethical awareness, and effective communication. Educational approaches that encourage critical engagement with technology and its balanced use may facilitate the ethical and efficient integration of artificial intelligence into nursing practice.
The findings indicate that nursing students had generally positive levels of AI literacy and attitudes toward AI, and higher AI literacy was associated with more positive attitudes toward AI.
M. Çil, Berna Eren Fidanci, D. Yıldız· Journal of Education and Res...· 0 citations
AI represents an effective supportive tool in nursing education by improving theoretical understanding and academic efficiency, however, its impact on human competencies remains limited.
Ilda Taka· INTERNATIONAL CONGRESS FROM...· 0 citations
Findings indicate that the Turkish version of the Nursing Students' Fear Toward Artificial Intelligence Scale is a valid and reliable instrument for assessing nursing students' fear of artificial intelligence.
Positive correlations were identified among all measured dimensions, with the strongest association observed between hope and adaptation, and the findings indicate that students’ evaluations of artificial intelligence involve interrelated perceptions of knowledge, anxiety, positive expectations, and educational prepara...
Introduction The primary objective of this study was to investigate undergraduate nursing students’ present level of artificial intelligence (AI) literacy and related issues, as well as to offer resources that nursing educators may use to create focused intervention methods. Methods From October to December 2025, 389 t...
Fang-Yun Li, Ke-Xin Feng, Shuang-Shuang Wang et al.· Frontiers in Public Health· 0 citations
Digital literacy was the strongest independent factor associated with attitudes towards artificial intelligence and perceptions regarding the impact of artificial intelligence on clinical reasoning, and perceptions regarding the impact of artificial intelligence on clinical reasoning were also independently associated...
N. Demirbaş, Hatice Kucukceran, O. Arık· Postgraduate medical journal· 0 citations
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