跨越数字门:一个可解释的机器学习模型对中国老年人的生活满意度
Dabu Xilatu1, Dan Li1, Qingyue Song1
1School of Public Administration, Sichuan University, Chengdu, China.
Applied psychology. Health and well-being
|December 19, 2025
概括
数字能力,而不仅仅是访问,显著提高了老年人在数字社会中的生活满意度. 质量承诺,特别是达到熟练度门,是幸福的关键.
科学领域:
- 老年学是一门学科.
- 数字社会研究 数字社会研究
- 人与计算机的交互
背景情况:
- 人口老龄化和快速数字化需要了解老年人的生活满意度.
- 数字沟对福祉的影响需要细微的调查,而不仅仅是访问.
研究的目的:
- 确定中国数字社会中老年人生活满意度的关键决定因素.
- 评估和比较机器学习模型在预测生活满意度方面的表现.
- 用可解释的方法解释数字参与影响生活满意度的机制.
主要方法:
- 调查数据来自1,102名中国老年人.
- 对四种机器学习算法的比较分析:规范后勤回归,随机森林,XGBoost和支持向量机.
- 应用可解释机器学习 (IML) 框架 (XGBoost-SHAP-PDP) 进行特征重要性和影响分析.
主要成果:
- XGBoost成为了表现最好的预测模型.
- 生活满意度的关键预测因素包括经济状况,数字能力,数字自我效能和使用强度.
- 数字能力对生活满意度产生积极影响,而使用强度则显示出值效应,作为对低使用的惩罚.
结论:
- 生活满意度是由数字参与的质量,特别是数字能力驱动的,而不是使用的数量.
- 必须达到一个功能能力值才能获得数字参与的好处.
- 未来的干预措施应侧重于强化培训,以提高老年人的数字能力,超越基本访问促进.
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