독거노인의 우울 발생 예측요인에 관한 연구: 의사결정 나무분석을 중심으로
Predictors of Depression of Elderly Living Alone: Focusing on Decision Tree Analysis
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초록
본 연구는 독거노인의 우울발생을 예측하는 요인을 탐색하는 목적으로 하는 연구로 2020년 한국 노인실 태조사 원시자료를 활용하였다. 연구 대상자는 65세 이상의 독거노인으로 최종 분석에서 3,117명이 선정되었다. 독거노인의 우울발생에 영향을 미치는 요인들의 병합 및 관계조합을 확인하고자 데이터마 이닝 기법 중 의사결정 나무분석 알고리즘을 통해 분석을 실시하였다. 연구결과 독거노인의 우울을 예측하는 가장 높은 변수 관계 조합은 주관적 건강상태에 있어 부정적으로 평가하는 경우, 장애요인과 관련하여 장애가 있다고 응답한 독거노인 집단에서 우울 발생 가능성이 가장 높게 예측되었다. 이어, 성별 요인에서는 남성 독거노인, 기초생활수급권 유무에 있어 비수급 독거노인인 경우 우울 발생이 유의미하게 예측됨을 확인 하였다. 연구 결과를 바탕으로 독거노인의 우울을 감소하고 관리할 수 있는 실천적 제언을 제공하였다.
Abstract
The purpose of this study is to explore the factors predicting the occurrence of depression in elderly individuals living alone. people were selected in the final analysis 3,117 elderly people aged 65 or older who are living alone from the raw data of the 2020 National Survey of Older Koreans. A decision tree analysis algorithm, one of the data mining techniques, was used to identify the combinations and relationships of factors affecting the occurrence of depression in elderly individuals living alone. The results of the study indicated that the highest probability of depression was predicted in elderly individuals living alone who gave a negative evaluation of their subjective health status and reported having a disability. Additionally, Men were identified as a significant influencing factor in gender factorsr and Non-basic living security were identified as significant influencing factors. Based on the study results, suggestions for managing depression in elderly individuals living alone were provided.
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