{
  "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.\n\nAim: 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).\n\nMethods: 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.\n\nResults: 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.\n\nConclusion: 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.",
  "abstract_shown": true,
  "affiliations": [
    "Party Committee Office, Xinghua People's Hospital Affiliated to Yangzhou University",
    "Department of Infection Control, The First Affiliated Hospital with Nanjing Medical University",
    "Department of Epidemiology and Infection Control, Xinghua People's Hospital Affiliated to Yangzhou University",
    "Science and Education Department, Xinghua People's Hospital Affiliated to Yangzhou University",
    "Human Resources Department, Xinghua People's Hospital Affiliated to Yangzhou University"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Lidan Zhu"
    },
    {
      "affs": [
        1
      ],
      "name": "Feng Zang"
    },
    {
      "affs": [
        2
      ],
      "name": "Guangxu Mao"
    },
    {
      "affs": [
        3
      ],
      "name": "Xiang Li"
    },
    {
      "affs": [
        4
      ],
      "name": "Xiaofang Shen"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9tbwnyr9mh1cs.bib",
  "cited_by": 0,
  "doi": "10.3389/fpubh.2026.1982743",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13736730/",
  "id": "9tbwnyr9mh1cs",
  "issns": [
    "2296-2565"
  ],
  "landing_url": "https://www.frontiersin.org/articles/10.3389/fpubh.2026.1982743/full",
  "language": "en",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Original Research"
    ],
    [
      "openalex",
      "2911|Healthcare Education and Workforce Issues"
    ]
  ],
  "openalex": "W7223185415",
  "pdf_url": "https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2026.1982743/pdf",
  "pmcid": "PMC13736730",
  "pmid": "42991725",
  "published": "2026-10-22",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/9tbwnyr9mh1cs.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:24Z",
      "native_id": "10.3389/fpubh.2026.1982743",
      "source": "crossref",
      "url": "https://www.frontiersin.org/articles/10.3389/fpubh.2026.1982743/full"
    },
    {
      "first_seen": "2026-11-09T12:22:07Z",
      "native_id": "PMC13736730",
      "source": "pmc",
      "url": "https://doi.org/10.3389/fpubh.2026.1982743"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "issn:2296-2565",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "Artificial intelligence (AI) anxiety and nurses’ turnover intention during healthcare digital transformation: the mediating role of occupational fatigue",
  "title_text": "Artificial intelligence (AI) anxiety and nurses’ turnover intention during healthcare digital transformation: the mediating role of occupational fatigue",
  "type": "peer-reviewed",
  "updated_at": "2026-11-09T12:22:07Z",
  "url": "https://research.draconitic.com/paper/9tbwnyr9mh1cs",
  "venue": "Frontiers in Public Health",
  "versions": []
}