Can Artificial Intelligence Replace Nursing? Examining Nursing Students’ Attitudes, Anxiety, and Dependency

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.

Keywords

• Anxiety
• Attitude
• Artificial Intelligence
• Dependency
• Nursing Student

Ethical Statement

Ethical approval was obtained from the Ethics Committee of Muğla Sıtkı Koçman University of Health Sciences (Approval date: 02.12.2024; Approval number: 240165-148).

Thanks

Authors thank the nursing students who voluntarily participated in this study.

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