Current situation and influencing factors of job burnout in express industry in Xinxiang City, Henan Province

Abstract

BackgroundJob burnout is common among working populations. The current situation and influencing factors of job burnout have been studied in workers of many industries at home and abroad, except the express industry in China.ObjectiveTo understand the current situation of job burnout in express industry in a city of China, and to provide a scientific basis for developing measures to reduce the occurrence of job burnout. MethodsIn 2022, 432 express delivery workers in a city were selected by cluster random sampling, and their job burnout, anxiety symptoms, and depressive symptoms were evaluated by using the General Burnout Scale, Generalized Anxiety Disorder-7, and Patient Health Questionnaire-9. Chi-square test was used to compare inter-group positive rates of job burnout. Spearman correlation analysis was used to analyze the correlation between selected variables. Positive job burnout, high level of exhaustion, and high level of cynicism were selected as dependent variables. Single-factor analysis was firstly carried out to identify statistically significant variables for subsequent logistic regression analysis. ResultsA total of 460 questionnaires were distributed and 432 valid questionnaires were recovered, with an effective recovery rate of 93.9%. There were 286 (66.2%) express delivery workers reporting job burnout. The positive rate of anxiety symptoms was 41.0%, and the positive rate of depressive symptoms was 34.0%. The job burnout score of the express industry workers [M (P25, P75)] was 1.8 (1.0, 2.5); the scores [M (P25, P75)] of exhaustion, cynicism, and professional efficacy were 1.0 (0.0, 2.6), 1.0 (0.0, 2.2), and 3.5 (1.2, 5.8), respectively; the score [M (P25, P75)] of anxiety symptoms was 1.5 (0.0, 7.0); the score [M (P25, P75)] of depressive symptoms was 1.0 (0.0, 8.0). There were statistical differences in the positive rates of job burnout among the express industry workers grouped by gender, education, monthly income, work shift system, overtime, anxiety symptoms, and depressive symptoms (P<0.05). The Spearman correlation analysis showed that there were significant positive correlations between the score of anxiety symptoms and the scores of job burnout, exhaustion, and cynicism (rs=0.596, 0.689, 0.600, P<0.001); the score of depressive symptoms was also positively correlated with the scores of job burnout, exhaustion, and cynicism (rs=0.601, 0.680, 0.607, P<0.001). The logistic regression analysis showed that women had a lower risk of job burnout than men (OR=0.458, 95%CI: 0.273, 0.768), and the risk of reporting positive job burnout was 3.140 times higher for those who worked overtime than those who did not (OR=3.140, 95%CI: 1.732, 5.693). ConclusionThe current situation of job burnout in express industry is serious. Gender, education, monthly income, and overtime are the main influencing factors. Measures should be developed to reduce the occurrence of job burnout.

Keywords

• express industry worker
• job burnout
• anxiety symptom
• depressive symptom
• influencing factor