Financial Well-Being in Older Adults: A Machine Learning Analysis of 47 Potential Predictors.

IF 2 3区 医学 Q2 GERONTOLOGY
Mohsen Joshanloo
{"title":"Financial Well-Being in Older Adults: A Machine Learning Analysis of 47 Potential Predictors.","authors":"Mohsen Joshanloo","doi":"10.1177/07334648251386155","DOIUrl":null,"url":null,"abstract":"<p><p>This study examined potential predictors of financial well-being in older adults. Data were drawn from the Health and Retirement Study, focusing on psychosocial, demographic, and lifestyle variables. Random Forest analysis was performed to assess the relative importance of 47 potential predictors, offering a data-driven evaluation of which factors are most strongly associated with subjective financial well-being. Results showed that psychological variables (particularly chronic stress, life satisfaction, perceived control, and optimism) were stronger predictors than demographic indicators. Among demographic variables, education was the most important. The results suggest that financial well-being reflects individuals' ability to maintain a sense of satisfaction, optimism, and agency in the face of life challenges, rather than being determined solely by economic or demographic conditions.</p>","PeriodicalId":47970,"journal":{"name":"Journal of Applied Gerontology","volume":" ","pages":"7334648251386155"},"PeriodicalIF":2.0000,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Gerontology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/07334648251386155","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GERONTOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

This study examined potential predictors of financial well-being in older adults. Data were drawn from the Health and Retirement Study, focusing on psychosocial, demographic, and lifestyle variables. Random Forest analysis was performed to assess the relative importance of 47 potential predictors, offering a data-driven evaluation of which factors are most strongly associated with subjective financial well-being. Results showed that psychological variables (particularly chronic stress, life satisfaction, perceived control, and optimism) were stronger predictors than demographic indicators. Among demographic variables, education was the most important. The results suggest that financial well-being reflects individuals' ability to maintain a sense of satisfaction, optimism, and agency in the face of life challenges, rather than being determined solely by economic or demographic conditions.

老年人的财务状况:47个潜在预测因素的机器学习分析。
这项研究调查了老年人财务状况的潜在预测因素。数据来自健康与退休研究,重点关注社会心理、人口统计学和生活方式变量。随机森林分析评估了47个潜在预测因素的相对重要性,提供了一个数据驱动的评估,哪些因素与主观财务状况最密切相关。结果显示,心理变量(特别是慢性压力、生活满意度、感知控制和乐观主义)比人口统计指标更能预测预后。在人口统计变量中,教育是最重要的。研究结果表明,财务状况反映了个人在面对生活挑战时保持满足感、乐观感和能动性的能力,而不仅仅是由经济或人口状况决定的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
5.10
自引率
13.30%
发文量
202
期刊介绍: The Journal of Applied Gerontology (JAG) is the official journal of the Southern Gerontological Society. It features articles that focus on research applications intended to improve the quality of life of older persons or to enhance our understanding of age-related issues that will eventually lead to such outcomes. We construe application broadly and encourage contributions across a range of applications toward those foci, including interventions, methodology, policy, and theory. Manuscripts from all disciplines represented in gerontology are welcome. Because the circulation and intended audience of JAG is global, contributions from international authors are encouraged.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信