Factors affecting fatigue in care and health service workers revealed by big data - the 7th Korean working conditions survey (2023) - Kim, Jung Im (Edelweiss Applied Science and Technology, 2025)
The purpose of this study was to identify factors affecting fatigue among caregivers and health service workers as reflected in big data. Data was analyzed using Statistics Korea [1]. This data set consists of 50,195 data points from Korea's public big data. The study subjects were 765 care and health service workers. The general characteristics of the subjects were analyzed by frequency analysis. Differences in fatigue according to general characteristics, occupational characteristics, and work-related health problems were analyzed using the χ2 test and Fisher's exact test. Logistic regression analysis was used to identify factors affecting fatigue. Factors influencing the subjects' fatigue were depression (5.442), marital status (4.662), anxiety (3.148), upper limb muscle pain (2.539), and lower limb muscle pain (2.228), in that order (p = < .001). In addition, back pain (1.026) and children (1.015) were also found to have an influence (p = < .05). To reduce fatigue among care and health service workers, workplaces need mental health management programs to reduce anxiety and depression and musculoskeletal disease prevention and management programs.