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A network analysis bridging the gap between the big five personality traits and burnout among medical staff

Authors :
Yifei Wang
Lin Wu
Chang Liu
Kuiliang Li
Mei Wang
Tingwei Feng
Qingyi Wang
Wu Chao
Lei Ren
Xufeng Liu
Source :
BMC Nursing, Vol 23, Iss 1, Pp 1-9 (2024)
Publication Year :
2024
Publisher :
BMC, 2024.

Abstract

Abstract Background Burnout is a common issue among medical professionals, and one of the well-studied predisposing factors is the Big Five personality traits. However, no studies have explored the relationships between these traits and burnout from a trait-to-component perspective. To understand the specific connections between each Big Five trait and burnout components, as well as the bridging effects of each trait on burnout, we employed network analysis. Methods A cluster sampling method was used to select a total of 420 Chinese medical personnel. The 15-item Chinese Big Five Personality Inventory-15 (CBF-PI-15) assessed the Big Five personality traits, while the 15-item Maslach Burnout Inventory-General Survey (MBI-GS) assessed burnout components. Network analysis was used to estimate network structure of Big Five personality traits and burnout components and calculate the bridge expected influence. Results The study revealed distinct and clear relationships between the Big Five personality traits and burnout components. For instance, Neuroticism was positively related to Doubt significance and Worthwhile, while Conscientiousness was negatively related to Accomplish all tasks. Among the Big Five traits, Neuroticism displayed the highest positive bridge expected influence, while Conscientiousness displayed the highest negative bridge expected influence. Conclusions The network model provides a means to investigate the connections between the Big Five personality traits and burnout components among medical professionals. This study offers new avenues for thought and potential targets for burnout prevention and treatment in medical personnel, which can be further explored and tested in clinical settings.

Details

Language :
English
ISSN :
14726955
Volume :
23
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Nursing
Publication Type :
Academic Journal
Accession number :
edsdoj.17e8194c01ff4757a8a67bbdb448db03
Document Type :
article
Full Text :
https://doi.org/10.1186/s12912-024-01751-0