Exploring Factors Influencing the Life Satisfaction of the People with Disabilities Using Random Forest Machine Learning Techniques

This study aimed to provide basic data on how to establish policies to improve the life satisfaction of the people with disabilities by exploring major factors affecting the life satisfaction of the people with disabilities. For this purpose, data from 4,254 people with disabilities who participated in the 4th (2021) survey of Disability and Life Dynamics Panel of Korea Disabled people’s Development Institute were used for analysis. The random forest machine learning technique was used, and a total of 88 explanatory variables were put in for the analysis, including 8 demographic factors, 19 physical health factors, 7 economic factors, 42 socio-cultural factors, and 12 psychological factors. The main results are as follows. First, the most important factor affecting the life satisfaction of the people with disabilities was the subjective effect of disability on life, a psychological factor. And it was found that the more positively thinking about the effect of disability on one’s life, the higher life satisfaction. Second, the top 20 explanatory variables did not include demographic factors, and socio-cultural factors accounted for the largest portion, with two physical health factors, four economic factors, eight socio-cultural factors, and six psychological factors. Third, of the seven economic factors put in, four economic factors were included in the top 20 explanatory variables, which were economic difficulties, average monthly household income, average monthly household living expenses, and effect of disability on employment. Conclusions and discussions based on the results were presented.

Publication Details

Journal
The Korea Academy of Case Management
Published
2024-08-31
DOI
https://doi.org/10.38019/kacm.15.2.103
Primary Topic
Health and Wellbeing Research
Type
article
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article

Exploring Factors Influencing the Life Satisfaction of the People with Disabilities Using Random Forest Machine Learning Techniques

The Korea Academy of Case Management
Health and Wellbeing Research
article

Exploring Factors Influencing the Life Satisfaction of the People with Disabilities Using Random Forest Machine Learning Techniques

article en

Abstract

This study aimed to provide basic data on how to establish policies to improve the life satisfaction of the people with disabilities by exploring major factors affecting the life satisfaction of the people with disabilities. For this purpose, data from 4,254 people with disabilities who participated in the 4th (2021) survey of Disability and Life Dynamics Panel of Korea Disabled people’s Development Institute were used for analysis. The random forest machine learning technique was used, and a total of 88 explanatory variables were put in for the analysis, including 8 demographic factors, 19 physical health factors, 7 economic factors, 42 socio-cultural factors, and 12 psychological factors. The main results are as follows. First, the most important factor affecting the life satisfaction of the people with disabilities was the subjective effect of disability on life, a psychological factor. And it was found that the more positively thinking about the effect of disability on one’s life, the higher life satisfaction. Second, the top 20 explanatory variables did not include demographic factors, and socio-cultural factors accounted for the largest portion, with two physical health factors, four economic factors, eight socio-cultural factors, and six psychological factors. Third, of the seven economic factors put in, four economic factors were included in the top 20 explanatory variables, which were economic difficulties, average monthly household income, average monthly household living expenses, and effect of disability on employment. Conclusions and discussions based on the results were presented.

The Korea Academy of Case ManagementVol. 15(2)
Openalex Percentile: Top 72%
Health and Wellbeing Research
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Exploring Factors Influencing the Life Satisfaction of the People with Disabilities Using Random Forest Machine Learning Techniques · The Korea Academy of Case Management (2024) | TGRS Research Map | TGRS