Citation

Huang A, Liu L, Wang X, Li X, Li J, Luo C, Chen J, Zhao J. Int. J. Environ. Res. Public Health 2022; 19(24): e17098.

Copyright

(Copyright © 2022, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/ijerph192417098

PMID

36554978

Abstract

This study aimed to characterize job burnout in longitudinal trajectories among bus drivers and examine the impact of variables related to job burnout for trajectories. A longitudinal study was conducted in 12,793 bus drivers in Guangdong province, China, at 3-year follow-up assessments. Growth mixture modeling (GMM) was used to estimate latent classes of burnout trajectories and multinomial logistic regression models were applied to predict membership in the trajectory classes. In general, there was a decrease in job burnout in 3 years [slope = -0.29, 95%CI = (-0.32, -0.27)]. Among those sub-dimensions, reduced personal accomplishment accounted for the largest proportion. GMM analysis identified five trajectory groups: (1) moderate-decreased (n = 2870, 23%), (2) low-stable (n = 5062, 39%), (3) rapid-decreased (n = 141, 1%), (4) moderate-increased (n = 1504, 12%), and (5) high-stable (n = 3216, 25%). Multinomial logistic regression estimates showed that depression symptoms, anxiety symptoms, and insomnia were significant negative predictors, while daily physical exercise was a significantly positive predictor. We found an overall downward trend in bus drivers' burnout, particularly in the sub-dimension of personal accomplishment. Mentally healthier drivers and those who were usually exercising were more resilient to occupational stress and less likely to suffer burnout.

Language: en

Keywords

longitudinal; burnout; drivers; growth mixture modeling; multinomial logistic regression; trajectories