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Does lifelong learning matter for the subjective wellbeing of the elderly? A machine learning analysis on Singapore data

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Publicado en:PLoS One vol. 19, no. 6 (Jun 2024), p. e0303478
Autor principal: Zheng, Fang
Otros Autores: Sim, Nicholas
Publicado:
Public Library of Science
Materias:
Singapore
Older people
Machine learning
Quality of life
Behavior
Lifelong learning
Socioeconomic factors
Personality
Aging
Psychological factors
Unsupervised learning
Decision trees
Attitudes
Social sciences
Learning algorithms
Socioeconomic status
Well being
Life satisfaction
Social
Acceso en línea:Citation/Abstract
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Resumen:Our study explores whether lifelong learning is associated with the subjective wellbeing among the elderly in Singapore. Through a primary survey of 300 individuals aged 65 and above, we develop a novel index to capture three different aspects of subjective wellbeing, which we term “Quality of Life”, “Satisfaction with Life” and “Psychological Wellbeing”. Utilizing both supervised and unsupervised machine learning techniques, our findings reveal that attitudes towards lifelong learning are positively associated with quality of life, while participation in class activities is positively associated with all three measures of wellbeing. Although the study does not establish causality, it highlights a connection between lifelong learning and the perceived wellbeing of the elderly, offering support for policies that encourage lifelong learning among this population.
ISSN:1932-6203
DOI:10.1371/journal.pone.0303478
Fuente:Health & Medical Collection