ArticleInternational journal of environmental research and public health2023
Predictive Models of Life Satisfaction in Older People: A Machine Learning Approach.
Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Shared reading interventions to promote psychosocial well-being in older adults: a systematic review.Health promotion international · 2025Pooled it
- Using Machine Learning to Analyze the Predictors of Life Satisfaction: Focus on Lifestyle Attitudes and Psychological Factors.International journal of methods in psychiatric research · 2026Article
- Machine learning in mental health promotion for older adults: a scoping review.BMC geriatrics · 2026Article
- Development of a machine learning-based screening model for the risk of depression among the elderly in China.BMC geriatrics · 2026Article
- An arithmetic method algorithm optimizing k-nearest neighbors compared to regression algorithms and evaluated on real world data sources.Scientific reports · 2026Article
- Automated machine learning for classification and regression: A tutorial for psychologists.Behavior research methods · 2025Article
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- A hybrid self-supervised model predicting life satisfaction in South Korea.Frontiers in public health · 2024Article
- Social Interaction and Life Satisfaction among Older Adults by Age Group.Healthcare (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Studies of life satisfaction in older adults have been conducted extensively through empirical research, questionnaires, and theoretical analysis, with the majority of these studies basing their analyses on simple linear relationships between variables. However, most real-life relationships are complex and cannot be approximated with simple correlations. Here, we first investigate predictors correlated with life satisfaction in older adults. Then, machine learning is used to generate several predictive models based on a large sample of older adults (age ≥ 50 years;
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Registered trials
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