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- Title
Factors associated with the general well‐being of nurses in a tertiary Chinese hospital: A cross‐sectional study.
- Authors
Yu, Junye; Song, Yuanyuan; Dong, Huan; Su, Xiuzhen; Zhang, Peishan
- Abstract
Background: Good general well‐being of nurses is associated with reduced burnout and improved patient safety. However, few studies explored the factors of nurses' general well‐being. Aim: The study aimed to assess general well‐being and its predictors among hospital nurses. Methods: The study recruited 573 nurses working in a tertiary Chinese hospital to complete a survey of sociodemographic characteristics, DiSC® personality profile, Self‐Rating Anxiety Scale and general well‐being. Multivariate linear regression was conducted to assess factors affecting nurses' general well‐being. Results: Marital status and clinical rank had a positive impact on general well‐being, especially when nurses were married or in the stage of assistant nursing manager. Conversely, source of stress, DiSC® profile and SAS score had a negative effect on general well‐being, especially when nurses' stress came from colleagues, nurses were characterized by steadiness and conscientiousness, and nurses had extreme anxiety. Conclusion: Marital status, clinical rank, source of stress, DiSC® profile and SAS score were main factors affecting hospital nurses' general well‐being. Implications for Nursing Management: By giving careful attention to nurses' family life, career development, personality characteristics and applying appropriate interventions, nursing managers can improve general well‐being of nurses and promote patient care.
- Subjects
CHINA; PSYCHOLOGICAL burnout prevention; ANALYSIS of variance; ANXIETY; ANXIETY testing; CONFIDENCE intervals; CONSCIENCE; EMPLOYMENT; JOB satisfaction; JOB stress; MARITAL status; MULTIVARIATE analysis; PERSONALITY; PSYCHOLOGICAL tests; QUALITY assurance; QUALITY of life; QUESTIONNAIRES; STATISTICAL sampling; SELF-report inventories; STATISTICS; T-test (Statistics); MULTIPLE regression analysis; CROSS-sectional method; DATA analysis software; DESCRIPTIVE statistics; HOSPITAL nursing staff; TERTIARY care
- Publication
Journal of Nursing Management, 2020, Vol 28, Issue 3, p540
- ISSN
0966-0429
- Publication type
Academic Journal
- DOI
10.1111/jonm.12954