Factors Influencing Depression in Older Adults According to Family Structure (Older Adults Living with Adult Children, a Spouse, or Alone): Data from the 2020 National Older Koreans Data

Yun, Kyoungsun; Lee, Yu-Jin

doi:10.17079/jkgn.2022.24.1.1

Cited by 4 publications

(4 citation statements)

References 12 publications

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“…It was found that the higher the risk of depression, especially for women, the smaller the number of household members, the lower the satisfaction level of leisure life, the lower the family support and social support, and the lower the level of subjective health awareness. These results were aligned with the same context as previous studies 18 , 35 – 37 . The level of depression according to income level can also be examined.…”

Section: Discussionsupporting

confidence: 91%

“…Another study reported that life satisfaction and subjective health awareness have the most significant influence 34 . Depression in the elderly has been shown to have a significant psychological impact, and decision trees are reported to be a highly effective method 35 , 36 . In order to prevent and manage depression in the elderly, it is necessary to recognize the need for policy support considering psychological factors (subjective health awareness, leisure life satisfaction, family support, and social support).…”

Section: Discussionmentioning

confidence: 99%

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Development of a prediction model for the depression level of the elderly in low-income households: using decision trees, logistic regression, neural networks, and random forest

Kim

Rhee

et al. 2023

Sci Rep

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Korea is showing the fastest trend in the world in population aging; there is a high interest in the elderly population nationwide. Among the common chronic diseases, the elderly tends to have a high incidence of depression. That said, it has been vital to focus on preventing depression in the elderly in advance. Hence, this study aims to select the factors related to depression in low-income seniors identified in previous studies and to develop a prediction model. In this study, 2975 elderly people from low-income families were extracted using the 13th-year data of the Korea Welfare Panel Study (2018). Decision trees, logistic regression, neural networks, and random forest were applied to develop a predictive model among the numerous data mining techniques. In addition, the wrapper’s stepwise backward elimination, which finds the optimal model by removing the least relevant factors, was applied. The evaluation of the model was confirmed via accuracy. It was verified that the final prediction model, in the case of a decision tree, showed the highest predictive power with an accuracy of 97.3%. Second, psychological factors, leisure life satisfaction, social support, subjective health awareness, and family support ranked higher than demographic factors influencing depression. Based on the results, an approach focused on psychological support is much needed to manage depression in low-income seniors. As predicting depression in the elderly varies on numerous influencing factors, using a decision tree may be beneficial to establish a firm prediction model to identify vital factors causing depression in the elderly population.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Development of a prediction model for the depression level of the elderly in low-income households: using decision trees, logistic regression, neural networks, and random forest

Kim

Rhee

et al. 2023

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Depression increased over time among older individuals living alone according to the study. This finding aligns with previous research on depression in individuals living alone [19,27,28,34], as well as the literature on depression changes in older adults [36][37][38][39]. The results of these studies highlight the need for social attention and intervention for depression among older individuals living alone.…”

Section: Discussionsupporting

confidence: 89%

“…Another study on social isolation suggested that living alone can easily result in social isolation and that may have a detrimental effect on cognitive function [33]. In the case of South Korea, research indicates that older individuals living alone suffer from a greater degree of depression than older individuals living with their children or older couples [34]. There has been a steady increase in the percentage of older people living alone in South Korea, reaching 34.9% in 2022, and this percentage is projected to continue to rise in the future [35].…”

Section: Introductionmentioning

confidence: 99%

A Study on the Longitudinal Relationship between Changes in Depression and Cognitive Function among Older Adults Living Alone

Park,

Jeong,

Lee

2023

Healthcare

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Background: As South Korea faces unprecedented population aging, this longitudinal study examined the relationship between depression and cognitive function changes in older individuals living alone. Methods: The study used data from the Korean Longitudinal Study of Aging (KLoSA). A total of 1354 participants with data available over a period of at least three years, from 2016 (wave 1) to 2020 (wave 8), were included, and latent growth modeling (LGM) was used for analysis. Results: Depression levels increased gradually among older individuals living alone and cognitive function declined over time among older adults living alone. Moreover, higher initial depression levels were associated with lower initial cognitive function levels and a more rapid cognitive decline over time. Therefore, it is imperative that depression be addressed as a potential cause of cognitive impairment and dementia. Furthermore, rapid increases in depression corresponded to rapid declines in cognitive function, indicating the need for continuous monitoring and intervention in cases of escalating depression, as it may negatively affect cognitive abilities. Conclusions: These findings highlight the complex interplay between depression and cognitive function among older individuals living alone. Policy support to encourage participation in these programs is crucial to enhance the well-being of this vulnerable population.

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Factors influencing intention to use life-sustaining treatment of community-dwelling older adults using the 2020 national survey of older Koreans: Secondary analysis research

Hwang¹,

Jun²,

Park³

2022

J Korean Gerontol Nurs

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Purpose: The purpose of this study was to identify the intention to use life-sustaining treatment for older adults living in a local community, and the factors that influence the intention to use life-sustaining treatment. Methods: A total of 9,555 older adults were selected and analyzed using 2020 National Survey of Older Koreans data. A Rao-Scott test was conducted to evaluate the differences in sociodemographics, health status, death preparation education experience, and life satisfaction according to intention to use life-sustaining treatment. Results: Economic status (odds ratio [OR]=1.38, 95% confidence interval [CI]=1.00~1.90), social support (OR=4.78, 95% CI=1.16~19.74), and life satisfaction (OR=1.53, 95% CI=1.12~2.09) were identified as significant influencing factors in the older adults’ life-sustaining treatment intentions. In other words, when satisfaction with economic conditions is moderate or low, when there is social support, and when life satisfaction is moderate, life-sustaining treatment intention was high. Conclusion: Education programs for life-sustaining treatment should be provided for older adults living in this community.

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Factors Influencing Depression in Older Adults According to Family Structure (Older Adults Living with Adult Children, a Spouse, or Alone): Data from the 2020 National Older Koreans Data

Cited by 4 publications

References 12 publications

Development of a prediction model for the depression level of the elderly in low-income households: using decision trees, logistic regression, neural networks, and random forest

Development of a prediction model for the depression level of the elderly in low-income households: using decision trees, logistic regression, neural networks, and random forest

A Study on the Longitudinal Relationship between Changes in Depression and Cognitive Function among Older Adults Living Alone

Factors influencing intention to use life-sustaining treatment of community-dwelling older adults using the 2020 national survey of older Koreans: Secondary analysis research

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