Citation

Lee J, Park H, Oh J, Sim J, Lee C, Kim Y, Yun B, Yoon JH. Int. J. Environ. Res. Public Health 2022; 20(1): e575.

Copyright

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

DOI

10.3390/ijerph20010575

PMID

36612903

Abstract

A replacement driver is a type of gig worker who provides driving services to the target point with the drunk driver's own car. This study aimed to examine the association of replacement drivers (ref: paid workers) with depressive symptoms. Information on replacement drivers was collected through online/offline surveys. Data from the 8th Korea National Health and Nutrition Examination Survey were applied to construct the control group. The Patient Health Questionnaire-9; ≥5 points was defined as depressive symptoms. Adjusted odds ratios (aOR) and 95% confidence intervals (CI) were calculated by performing multivariable logistic regression analysis. The mean age of replacement drivers was 56.11. The prevalence of depressive symptoms in replacement drivers and controls were 49.63% and 12.64%, respectively. Replacement drivers showed a higher association with depressive symptoms than paid workers (aOR 7.89, 95% CI [5.53-11.26]). This relationship was prominent in the older, low-education, and low-income groups. Linear discriminant analysis was the most effective in predicting depressive symptoms among the machine learning models. Using the replacement driver feature increased the AUC values of the models. Given the strong association between depressive symptoms and replacement drivers, in-depth studies to establish guidelines to prevent mental diseases among replacement drivers are required.

Language: en

Keywords

machine learning; depressive symptoms; gig worker; paid workers; replacement driver