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

Detalles Bibliográficos
Publicado en:BMC Nursing Vol. 24; no. 1; pp. 1 - 14
Autores principales: Rocha, Ana, Costeira, Cristina, Barbosa, Raul, Gonçalves, Florbela, Castelo-Branco, Miguel, Viana, Joaquim, Gaudêncio, Margarida, Ventura, Filipa
Formato: research tables/charts Journal Article
Publicado: BioMed Central 7/1/2025
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Burnout protective patterns among oncology nurses: a cross-sectional study using machine learning analysis.
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          Rocha, Ana
          Costeira, Cristina
          Barbosa, Raul
          Gonçalves, Florbela
          Castelo-Branco, Miguel
          Viana, Joaquim
          Gaudêncio, Margarida
          Ventura, Filipa
        affil: https://ror.org/03c3y8w73 Health Sciences Research Unit: Nursing (UICISA: E), Nursing School of Coimbra (ESEnfC), 3004-011, Coimbra, Portugal
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        subj:
          Burnout, Professional Evaluation
          Burnout, Professional Prevention and Control
          Oncology Nurses Psychosocial Factors
          Job Characteristics
          Sociodemographic Factors
          Machine Learning
          Occupational Health
          Portugal
          Human
          Male
          Female
          Adult
          Middle Age
          Cross Sectional Studies
          Secondary Analysis
          Questionnaires
          Random Forest
          Machine Learning Algorithms
          Contracts
          Work-Life Balance
          Work Environment
          Hardiness
          Job Security
          Job Satisfaction
          Summated Rating Scaling
          Coefficient alpha
          Data Analysis Software
          Descriptive Statistics
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Male
          Female
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
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    language: English
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