Burnout protective patterns among oncology nurses: a cross-sectional study using machine learning analysis.

Journal: BMC nursing
Published Date: Jul 1, 2025

Abstract

BACKGROUND: Oncology nurses face unique and intense demands due to the nature of their work, caring for patients with life-threatening illnesses. The emergence of professional burnout among these nurses is influenced by several factors, highlighting the importance of identifying protective and risk factors to mitigate its impact. This study aims to identify burnout profiles and protective socio-demographic and work-related patterns associated with reduced burnout among oncology nurses.

Authors

  • Ana Rocha
    Health Sciences Research Unit: Nursing (UICISA: E), Nursing School of Coimbra (ESEnfC), Coimbra, 3004-011, Portugal. anamnrocha@esenfc.pt.
  • Cristina Costeira
    Health Sciences Research Unit: Nursing (UICISA: E), Nursing School of Coimbra (ESEnfC), Coimbra, 3004-011, Portugal.
  • Raul Barbosa
    Centre for Informatics and Systems of the University of Coimbra (CISUC), Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal.
  • Florbela Gonçalves
    Faculdade de Ciências da Saúde, Universidade da Beira Interior, Covilhã, Portugal.
  • Miguel Castelo-Branco
    Institute for Nuclear Sciences Applied to Health (ICNAS), and Institute for Biomedical Imaging and Life Sciences (IBILI), Faculty of Medicine, University of Coimbra, Coimbra, Portugal.
  • Joaquim Viana
    ULS Coimbra - Centro Hospitalar e Universitário de Coimbra EPE, Coimbra, Portugal.
  • Margarida Gaudêncio
    Palliative Care Unit, Portuguese Oncology Institute of Coimbra, Coimbra, 3004, Portugal.
  • Filipa Ventura
    Health Sciences Research Unit: Nursing (UICISA: E), Nursing School of Coimbra (ESEnfC), Coimbra, 3004-011, Portugal.

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