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KMID : 1023720230780010119
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Journal of Welfare for the Aged
2023 Volume.78 No. 1 p.119 ~ p.143
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Analysis of Branched Pathways on COVID-19 and on Depression of the Elderly: Focused on Decision Tree Model
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Seo Yang-Mi
Kim Kyoung-Ho
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Abstract
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The purpose of this study was to investigate the predictors and importance of COVID-19 and the decision tree model for the depression of the elderly through branch path analysis. Jamovi and R(ver.4.1.0)/R-studio analysis tools were analyzed using 「2020 Community Health Survey」 data. In this study, two groups were classified through UtilMax to set up a wide range of latent groups. The results of the study showed that women are more likely to be a potential depressed group when their health is poor and their daily life is stopped, and men are more likely to become a potential depressed group if their health is poor.
Discussions are as follows: First, the subjective health status of the elderly and the depression of the elderly were 171.56, which was significantly higher than other variables. Second, the change of daily life was shown to be 11.316 in importance, and the depression latent group was derived when the daily life was almost stationary as a predictor variable affecting depression while the elderly experienced changes in daily life with COVID-19. Third, anxiety about COVID-19 infection is 7.731, which is a predictor that affects depression of the elderly. As the situation of COVID-19 becomes longer, anxiety is increasing. Fourth, although socio-demographic characteristics such as gender, age, marital status, education level, and type of each generation were found to be predictors of depression of the elderly, it was confirmed that the correlation with depression of the elderly could not be determined by one or two variables.
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KEYWORD
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COVID-19, depression of the elderly, branch path analysis, decision tree
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