1. Association between job burnout, depressive symptoms, and insomnia among employees in electronic manufacturing industry
- Author
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Xiaoyi LI, Yao GUO, Rong ZHAO, Xiaodong JIA, Jin WANG, Huiqing CHEN, and Xiaoman LIU
- Subjects
electronic manufacturing industry ,job burnout ,depressive symptom ,insomnia ,Medicine (General) ,R5-920 ,Toxicology. Poisons ,RA1190-1270 - Abstract
BackgroundThe high-quality development of manufacturing in China has spurred industrial transformation and upgrading, placing higher demands on the skills of employees in the electronic manufacturing industry. This situation may induce psychological health problems such as job burnout and depressive symptoms in the employees, and also lead to insomnia, which has become a public health problem that urgently needs attention and solution. ObjectiveTo investigate the relationship between job burnout, depressive symptoms, and insomnia among employees in the electronic manufacturing industry. MethodsA total of 3034 employees from four electronic manufacturing companies in Beijing City, Shanghai City, and Guangdong Province were selected using judgment sampling from September to November 2019. The Maslach Burnout Inventory-General Survey, Patient Health Questionnaire-9, and Self-Administered Sleep Questionnaire were used to collect data. The correlation between job burnout, depressive symptoms, and insomnia was evaluated by hierarchical regression. ResultsA total of 3034 survey questionnaires were distributed, and 2614 valid questionnaires were collected, with a response effectiveness rate of 86.2%. The reporting rates of job burnout, depressive symptoms, and insomnia among employees in the electronic manufacturing industry were 47.2%, 19.5%, and 29.1%, respectively. The reporting rates of insomnia of employees in the job burnout group and depressive symptoms group were higher than those in the non-job burnout group and non-depressive symptoms group (35.3% vs. 23.6%, 47.2% vs. 24.7%, P<0.001). The results of hierarchical regression showed that job burnout explained 2.8% of the variation of insomnia (P
- Published
- 2024
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