教育水平与风险感知和行为反应之间的积极关系:一种机器学习方法
Zhipeng Wei1,2,3, Zhichun Zhang1,2,3, Liping Guo1,2,3
1Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
PloS one
|April 3, 2025
概括
教育水平显著影响人们如何感知风险和行为反应,影响意图和行动. 这一发现对于制定有效的风险管理政策至关重要.
科学领域:
- 社会心理学 社会心理学
- 风险分析 风险分析
- 行为科学 行为科学
背景情况:
- 了解影响风险感知和行为反应的因素对于公共政策至关重要.
- 教育水平是一个关键的人口变量,经常与风险感知和决策相关联.
研究的目的:
- 研究教育水平在风险感知和行为反应 (意图和准备性行为) 之间的关系中的作用.
- 使用机器学习模型识别对行为反应的关键影响因素.
主要方法:
- 利用随机森林和XGBoost算法进行预测建模.
- 员工使用SHAP (夏普利增量解释) 值来分析教育水平的影响.
- 应用非参数估计技术.
主要成果:
- 机器学习模型确定了关键的影响因素,尽管整体适应度适度 (25.71%用于准备性行为, <20%用于行为意图).
- 学历水平被认为是一个重要的因素,在不同学历水平的群体中产生不同的影响.
- 统计测试证实了教育水平在调解风险感知-行为反应联系方面的重要性.
结论:
- 教育水平在个人如何感知和应对风险方面发挥着至关重要的,细微的作用.
- 这些发现为根据教育人口统计量来定制风险沟通和管理策略提供了科学基础.
- 进一步的研究可以完善风险行为反应的预测模型.
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