Leisure and Happiness of the Elderly: A Machine Learning Approach

Abstract

Leisure activities play an important role in improving happiness levels for the elderly. The purpose of this study is to explore leisure-related factors that affect the happiness of the elderly using machine learning algorithms. For this research, the 2019 National Leisure Activity Survey released by the Ministry of Culture, Sports and Tourism, Republic of Korea, was used to analyze the data of 1769 elders over the age of 65 among 10,060 men and women aged 15 years and older in 17 cities and provinces nationwide, and it went through the process of data preprocessing, data segmentation, prediction model construction and evaluation, and model tuning. According to the findings of the study, the main factors predicting the happiness index of the elderly were leisure life satisfaction, leisure time, whether to use public leisure facilities, leisure policy satisfaction, and leisure activity companionship. The overall findings of this study imply that exploring sustainable policy towards the achievement of sustainable happiness for the elderly is important. Based on these results, policy measures to improve the happiness level of the elderly were discussed.