[Relationship between job burnout and quality of life of factory staff].
OBJECTIVE
To investigate the status of job burnout and the quality of life of factory staff and analyze the their relationship.


METHODS
Questionnaires were administered to investigate the status of job burnout and quality of life of all the staff in three randomly selected state factories, and then the methods of canonical correlation and hierarchical linear regression analysis were used to analyze the relationship between job burnout and quality of life.


RESULTS
Job burnout and quality of life were somewhat different among staff in factories of different demography character. Emotional exhaustion was negatively associated with mental component summary (MCS). The predictive variables of physical component summary (PCS) were age, educational attainment, emotional exhaustion and professional efficacy and the standard partial regression coefficients of the four variables were -0.101, 0.055, -0.294, -0.058 respectively (P < 0.05). Educational level positively predicted the physical component summary, whereas age, emotional exhaustion and professional efficacy predicted physical component summary negatively. The predictive variables of mental component summary were emotional exhaustion, cynicism and professional efficacy and the standard partial regression coefficients of the three scale of job burnout were -0.546, -0.075, -0.184 (P < 0.05). All the three scales of job burnout predicted the mental component summary negatively. The emotional exhaustion was the most predictive variable for both the physical component summary and the mental component summary.


CONCLUSIONS
Job burnout is the important risk factor of quality of life of factory staff, especially influencing the staff's metal health significantly.
Zhu
Wei
W
Department of Social Medicine, College of Public Health, Zhengzhou University, Zhengzhou 450001, China.
Zhou
Cai-Liang
CL
Su
Dong-Mei
DM
D000293:Adolescent; D000328:Adult; D002055:Burnout, Professional; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011788:Quality of Life; D012044:Regression Analysis; D011795:Surveys and Questionnaires; D017132:Workplace; D055815:Young Adult