Key Predictors of Generativity in Adulthood: A Machine Learning Analysis.

IF 4.8 2区医学 Q1 GERIATRICS & GERONTOLOGY

Journals of Gerontology Series B-Psychological Sciences and Social Sciences Pub Date : 2025-03-12 DOI:10.1093/geronb/gbae204

Mohsen Joshanloo

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引用次数: 0

Abstract

Objectives: This study aimed to explore a broad range of predictors of generativity in older adults. The study included over 60 predictors across multiple domains, including personality, daily functioning, socioeconomic factors, health status, and mental well-being.

Methods: A random forest machine learning algorithm was used. Data were drawn from the Midlife in the United States (MIDUS) survey.

Results: Social potency, openness, social integration, personal growth, and achievement orientation were the strongest predictors of generativity. Notably, many demographic (e.g., income) and health-related variables (e.g., chronic health conditions) were found to be much less predictive.

Discussion: This study provides new data-driven insights into the nature of generativity. The findings suggest that generativity is more closely associated with eudaimonic and plasticity-related variables (e.g., personal growth and social potency) rather than hedonic and homeostasis-oriented ones (e.g., life satisfaction and emotional stability). This indicates that generativity is an inherently dynamic construct, driven by a desire for exploration, social contribution, and personal growth.

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成年期生育能力的关键预测因素：机器学习分析。

目的：本研究旨在探索老年人生育能力的广泛预测因素。这项研究涵盖了多个领域的60多个预测因素，包括个性、日常功能、社会经济因素、健康状况和心理健康。方法：本研究采用了一种称为随机森林的机器学习算法。数据来自美国中年调查。结果：社会潜能、开放性、社会融合、个人成长和成就取向是生成性的最强预测因子。值得注意的是，许多人口（如收入）和健康相关变量（如慢性健康状况）的预测性要低得多。讨论：这项研究为生成性的本质提供了新的数据驱动的见解。研究结果表明，创造性与幸福感和可塑性相关的变量（如个人成长和社会效力）的关系更密切，而与享乐和自我平衡相关的变量（如生活满意度和情绪稳定性）的关系更密切。这表明，生成是一种内在的动态结构，由探索、社会贡献和个人成长的欲望驱动。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journals of Gerontology Series B-Psychological Sciences and Social Sciences 医学-老年医学

CiteScore

11.60

自引率

8.10%

发文量

178

审稿时长

6-12 weeks

期刊介绍： The Journal of Gerontology: Psychological Sciences publishes articles on development in adulthood and old age that advance the psychological science of aging processes and outcomes. Articles have clear implications for theoretical or methodological innovation in the psychology of aging or contribute significantly to the empirical understanding of psychological processes and aging. Areas of interest include, but are not limited to, attitudes, clinical applications, cognition, education, emotion, health, human factors, interpersonal relations, neuropsychology, perception, personality, physiological psychology, social psychology, and sensation.