Abstract

Background

Several factors are associated with the incidence of burnout, including alexithymia, social support, and depression. The relative importance of these three key parameters as mediators of burnout, however, is not well understood. In addition, there have been few studies to date specifically examining the association between alexithymia and burnout among nurses in China.

Purpose

To evaluate the relationship of burnout with alexithymia, social support, and depression across emergency department nurses in China.

Methods

This descriptive, cross-sectional survey was conducted using a convenience sampling methodology to survey nurses responsible for direct emergency care (n = 413) from 18 tertiary hospitals in Western, Eastern, Northern, and Southern China between May 2020 and June 2020. A structural equation modeling approach was then used to assess a hypothetical model wherein alexithymia both directly and indirectly affects burnout among emergency nurses via impacting the incidence of depression and perceived social support.

Results

Results supported all driving hypotheses. Alexithymia was positive direct correlated with burnout (β = 0.35; P < 0.001) and depression (β = 0.50; P < 0.001), and exhibited a negative direct effect on social support (β = − 0.14; P = 0.041). Depression was associated with burnout, both directly (β = 0.24; P < 0.001) and indirectly (β = 0.15; P < 0.001) through its relationship with social support. Alexithymia was the factor most strongly associated with burnout, and it was able to affect burnout indirectly through depression and social support.

Conclusions

We found that among emergency nurses in China, alexithymia was correlated with burnout, depression, and social support. Alexithymia was the factor most strongly associated with burnout. These data suggest that providing better social support and alleviating alexithymia may decrease rates of burnout among emergency nurses.

Details

Title
Alexithymia, social support, depression, and burnout among emergency nurses in China: a structural equation model analysis
Author
Pei, Juhong; Wang, Xinglei; Chen, Haixia; Zhang, Hongchen; Ruiling Nan; Zhang, Jing; Dou, Xinman
Pages
1-10
Section
Research article
Publication year
2021
Publication date
2021
Publisher
BioMed Central
e-ISSN
14726955
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2583081830
Copyright
© 2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.