ArticleNursing open2023
Factors influencing the burnout dimensions among nurses: A cross-sectional study in South Korea.
Article in Nursing open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- AI-Assisted Tailored Intervention for Nurse Burnout: A Three-Group Randomized Controlled Trial.Worldviews on evidence-based nursing · 2025Trial
- Differential Predictors of Turnover Intention Among Registered Nurses and Nursing Assistants: A Cross-Sectional Study in South Korea.International nursing review · 2026Article
- The Effects of Grit, Emergency Nursing Competency, and Positive Nursing Organisational Culture on Burnout Among Nurses in the Emergency Department.Behavioral sciences (Basel, Switzerland) · 2025Article
- Affective Commitment Influences Occupational Stressors Among Maternal and Child Health Nurses via Job Burnout as a Mediator.Journal of multidisciplinary healthcare · 2025Article
- Survey of psychological resilience among university students majoring in long-term-care-related disciplines in Taiwan.BMC psychology · 2024Article
- The association between occupational stress, sleep quality and premenstrual syndrome among clinical nurses.BMC nursing · 2024Article
- The independent and interactive effects of changes in overtime and night shifts during the COVID-19 pandemic on burnout among nurses: a longitudinal study.Scandinavian journal of work, environment & health · 2024Article
- The Level and Outcomes of Emotional Labor in Nurses: A Scoping Review.Journal of nursing management · 2024Article
- Factors influencing the burnout dimensions among nurses: A cross-sectional study in South Korea.Nursing open · 2023Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
aimTo investigate the factors influencing three dimensions of burnout among clinical nurses in South Korea.
designDescriptive, correlational and cross-sectional study.
methodsWe recruited 300 clinical nurses to participate in an online survey conducted in June 2021. Purposive sampling was used for the survey. Multiple linear regression was used for data analysis.
resultsThe regression models explained 55.8%, 45.8% and 34.3% variances in emotional exhaustion, depersonalization and personal accomplishment respectively. Emotional exhaustion was influenced by experience in the current department, working overtime, shift type, depression, job stress and emotional labour. Depersonalization was influenced by gender, hospital size, the associated department, overtime, coping strategies, depression and emotional labour. Personal accomplishment was influenced by clinical experience, shift type, resilience and the perceived threat of coronavirus disease 2019.
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Registered trials
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