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Artificial intelligence (AI) anxiety and nurses’ turnover intention during healthcare digital transformation: the mediating role of occupational fatigue

Year: 2026

Type: article

Abstract: Background The rapid integration of artificial intelligence (AI) into healthcare is associated with new psychological challenges. However, the extent of its impact on nursing workforce stability is unclear. Aim To explore the relationship between AI anxiety and turnover intention of clinical nurses, and the mediating effect of occupational fatigue and the moderating effect of emotional intelligence (EI). Methods A cross-sectional survey was conducted from March to June 2026 among 404 clinical nurses from four hospitals in Jiangsu Province, China. Data were collected using the AI Anxiety Scale (AIAS), Health Workers’ Occupational Fatigue Scale (HWOFS), Turnover Intention Scale (TIS) and Wong and Law Emotional Intelligence Scale (WLEIS). Mediation was tested using structural equation modelling with bootstrap resampling, while moderation was tested using moderated regression analysis. Results Differences in baseline turnover intentions across age, department, and professional title level were statistically significant (all p < 0.001). Path analysis showed that AI anxiety was positively associated with occupational fatigue (β = 0.611, p < 0.001) and turnover intention (β = 0.530, p < 0.001). Occupational fatigue partially mediated the association between AI anxiety and turnover intention (indirect effect = 0.299, 95% CI: 0.129, 0.379). EI had a significant negative main effect on occupational fatigue (b = −0.257, p < 0.001), but it did not significantly moderate the association between AI anxiety and occupational fatigue. Conclusion AI anxiety is significantly correlated with the turnover intention of clinical nurses, and occupational fatigue may represent a potential pathway linking AI anxiety and turnover intention. Although EI is associated with lower levels of occupational fatigue, it fails to cushion the impact of AI anxiety, a specific stressor. Hospital administrators should focus on targeted AI literacy improvement plans and specific fatigue relief strategies to retain clinical nursing staff.

Source: Frontiers in Public Health

DOI: 10.3389/fpubh.2026.1982743

Authors: Lidan Zhu, Feng Zang, Guangxu Mao, Xiang Li, Xiaofang Shen

Institutions: Xinghua People's Hospital Affiliated to Yangzhou University, Jiangsu Province Hospital, Nanjing Medical University

Language: English

Topic: Healthcare Education and Workforce Issues

Subfield: Leadership and Management

Field: Nursing

Domain: Health Sciences

SDGs: Good health and well-being, Decent work and economic growth

Open Access status: gold

Estimated APC paid: $3,801