ICF-Based Job Performance Predictors for South Korean Industrial Accident Workers: Population-Based 3-Year Longitudinal Analysis

Gayeong Eom, Seonjae Been and Haewon Byeon
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Gayeong Eom: Department of Statistics, Graduate School, Inje University, Gimhae 50834, Korea
Seonjae Been: Department of Digital Anti-Aging Healthcare (BK21), Graduate School, Inje University, Gimhae 50834, Korea
Haewon Byeon: Department of Digital Anti-Aging Healthcare (BK21), Graduate School, Inje University, Gimhae 50834, Korea

IJERPH, 2022, vol. 19, issue 13, 1-16

Abstract: Since workers who have experienced industrial accidents may have a physical impairment, their workload is very likely to be less than before the industrial accident. This epidemiological study identified ICF-based predictive factors affecting the work performance of South Korean workers who were economically active after undergoing medical treatment (rehabilitation) related to injuries caused by industrial accidents by using the Panel Study of Worker’s Compensation Insurance (2018–2020) as a reference. We analyzed 1383 subjects who were engaged in economic activities. The explanatory variables included participation factors, activity factors, personal factors, physical function factors, and rehabilitation service factors. The outcome variables were defined by subjective evaluations of current job performance (0 and 10 points). This study analyzed the trajectory of change in work performance and change function predictors over time by using latent growth modeling (LGM). This study found mental activity, indoor activity, occupational activity, disability grade, socioeconomic status, the length of recuperation, self-esteem, and self-efficacy as significant predictors. The results of this study suggested that it would be necessary to prepare a systematic program that considers activity factors to support the independent daily life activities and social participation of workers injured by industrial accidents.

Keywords: latent growth modeling; ICF; job performance; industrial accident workers (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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