心理因素在预测自我评估健康中的作用:机器学习模型的含义
Jeong Ha Steph Choi1, Daniel Hong Jung2
1Department of Psychology, Georgia State University, Atlanta, GA, USA.
Psychology, health & medicine
|January 8, 2025
概括
心理因素,包括情绪和个性,显著预测自我评价健康 (SRH). 结合这些因素的机器学习模型可以增强对主观健康评估的理解和预测.
科学领域:
- 心理学 心理学 心理学
- 健康科学 卫生科学 卫生科学
- 机器学习 机器学习
背景情况:
- 自评健康 (SRH) 预测未来的健康结果.
- 以前用于SRH预测的机器学习模型主要集中在健康因素上,忽视了心理影响.
研究的目的:
- 通过机器学习,使用一组全面的生物,心理和社会人口统计因素来预测SRH.
- 调查心理变量在SRH评估中的预测重要性.
主要方法:
- 使用了美国中年 (MIDUS 2) 数据集.
- 使用后勤回归,LASSO回归,随机森林和XGBoost机器学习模型.
- 分析了SRH的生物,心理和社会人口学预测因素.
主要成果:
- 所有机器学习模型都显示出强大的预测性能 (AUPRC>0.90).
- 与情绪相关的变量被确定为关键预测因素,与传统的健康因素一起.
- 心理健康,人格特征和情绪状态显著影响了主观健康评级.
结论:
- 将心理因素纳入其中,可以更全面地了解SRH.
- 在评估主观健康观念时,情绪健康与身体健康同样重要.
- 研究结果支持针对性干预,解决身体和情绪健康问题,以改善SRH和长期结果.
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