A Study on the Determinants of Social Isolation Among the Elderly Living Alone: Focused on Machine Learning-Based Importance Analysis

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Key Points

This study investigates the multidimensional factors influencing social isolation among the elderly living alone, aiming to derive intervention strategies.
Analyzed data from 1,473 elderly care service users to identify factors affecting isolation.
Utilized machine learning techniques, specifically XGBoost and SHAP analysis, for variable importance and interaction studies.
Focused on defining an early warning system for isolation risk based on the quality of social relationships.
The absence of community networks (friends and neighbors) is identified as the strongest predictor of social isolation.
Physical visits and availability of help during emergencies are found to significantly contribute to reducing isolation from familial relationships.
Nonlinear patterns reveal a sharp drop in willingness to engage in social activities as isolation worsens, highlighting structural limitations.

Analyzes factors affecting social isolation in the elderly, suggesting intervention strategies for prevention.

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Kim et al. (2026) studied this question.

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