Abstract
The purpose of this study is to classify the types of depression in single-personelderly households, analyze the personal characteristics of the elderly and predictive variablessuch as drinking, smoking, and social relationships that affect this, and then determine howthe types of depression and predictors affect life satisfaction. For this purpose, data from the 8th (2020) KLoSA Research Panel Survey was used. As a result of the analysis, first, thedepression types of single-person elderly households were classified into ‘low depressiongroup’ (56.6%), ‘moderate depression group’ (35.3%), and ‘high depression group’ (8.1%). Second, among the sub-factors of depression, the factors ‘depressed feelings’, ‘interpersonalrelationships’, and ‘physical behavior’ were high in the order of ‘low depression group’ <‘moderate depression group’ < ‘high depression group’, and positive emotions were ‘highdepression group’. It was significantly higher in the order of ‘highly depressed group’ <‘moderately depressed group’ < ‘lowly depressed group’. Positive emotions, a positivedepression subfactor, were significantly higher in the ‘low depression group’. Third, when the‘highly depressed group’ is set as the reference group and the ‘low depressed group’ is thecomparison group, the better the health status and the more encounters with close people, the‘low depressed group’ rather than the ‘highly depressed group’. There was a high probabilityof belonging to. Fourth, It was analyzed that the better the economic status of single elderlyhouseholds, the better their health, and the more they met with close people, the morepositive (+) they had on life satisfaction, and the more they belonged to the “middledepression group” and “high depression group” had a negative (-) effect on life satisfactioncompared to the “low depression group”. Based on these analysis results, policy and practicalimplications were presented.
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