This study aimed to determine the levels of resistance to change and artificial intelligence (AI) anxiety among nursing and midwifery students and to examine the association between these variables. This cross-sectional, descriptive-correlational study was conducted with 413 nursing and midwifery students enrolled at a state university during the 2024–2025 academic year. Data were collected using a Personal Information Form, the Resistance to Change Scale, and the Artificial Intelligence Anxiety Scale. Descriptive statistics, independent samples t-tests, one-way ANOVA, Pearson correlation analysis, and multiple linear regression analysis were performed. Students demonstrated moderate levels of resistance to change (Mean = 39.15 ± 7.99) and moderate levels of AI anxiety (Mean = 44.62 ± 11.04). Based on the recommended cut-off score of 48, 45.8% of participants (n = 189) were classified as experiencing high AI anxiety, while 54.2% (n = 224) had low-to-moderate levels of AI anxiety. Among AI anxiety subdimensions, the highest mean score was observed in sociotechnical blindness. Resistance to change was positively associated with AI anxiety (r = 0.296, p < 0.01). In the regression model, resistance to change showed the strongest association with AI anxiety (B = 0.47, p < 0.001), while gender and academic department were also significantly associated. The final model explained 14.1% of the variance in AI anxiety (R² = 0.141). Higher levels of resistance to change are associated with increased AI anxiety among nursing and midwifery students. These findings suggest that resistance to change represents a modifiable psychological factor that may be addressed through educational interventions, alongside technical AI skill development, within digital transformation initiatives in health professions education.
Güner et al. (Thu,) studied this question.