Analyzing the influencing factors of occupational burnout among disease control and prevention staffs in Sichuan Province
10.20001/j.issn.2095-2619.20250608
- VernacularTitle:四川省疾病预防控制工作人员职业倦怠影响因素分析
- Author:
Chaoxue WU
1
;
Shuang DONG
;
Liang WANG
;
Xunbo DU
;
Lin ZHAO
;
Dan SHAO
;
Quanquan XIAO
;
Lijun ZHOU
;
Chongkun XIAO
;
Heng YUAN
Author Information
1. Sichuan Center for Disease Control and Prevention, Chengdu, Sichuan 610041, China
- Publication Type:Journal Article
- Keywords:
Disease control and prevention;
Staff;
Occupational burnout;
Status survey;
Influencing factors
- From:
China Occupational Medicine
2025;52(3):288-292
- CountryChina
- Language:Chinese
-
Abstract:
Objective To assess the situation and influencing factors of occupational burnout among the staff at the Center for Disease Control and Prevention (CDC) in Sichuan Province. Methods A total of 1 038 CDC staff members in Sichuan Province were selected as the study subjects using the stratified random sampling method. Occupational burnout of the staff was assessed using the Maslach Burnout Inventory General Survey via an online questionnaire. Results The detection rate of occupational burnout was 42.3% (439/1 038). Binary logistic regression analysis result showed that, after controlling for confounding factors such as education level and alcohol consumption, CDC staffs aged at 20-<31, 31-<41, and 41-<51 years were at higher risk of occupational burnout compared with those ≥51 years (all P<0.05). CDC staffs with 5-<10 or ≥10 years of service had higher occupational burnout risk compared with those with <5 years (both P<0.05). CDC staffs with poor or fair health status, irregular diet, and poor sleep quality had higher risk of occupational burnout compared with those healthy, have regular diet, and good sleep quality (all P<0.05). The risk of occupational burnout increased with higher overtime frequency (all P<0.05). Conclusion Occupational burnout among CDC staffs in Sichuan Province is relatively high. Age, years of service, health status, diet, sleep quality, and overtime frequency are key influencing factors.
