开发韩国COVID-19患者中自杀倾向的预测模型,使用来自国家灾害和创伤中心的及时数据
Hyejin Kim1,2, Youngrong Lee2, Euihyun Kwak3
1Department of Public Health, Graduate School, Yonsei University, Seoul, Korea.
Journal of Korean medical science
|August 19, 2025
概括
这项研究使用机器学习开发了近期冠状病毒病2019 (COVID-19) 患者自杀倾向的预测模型. 该模型基于及时的数据,有助于早期查心理健康支持.
科学领域:
- 精神病学是一个精神病学.
- 公共卫生 公共卫生
- 数据科学数据科学数据科学
背景情况:
- 没有先前的模型使用来自2019年冠状病毒病 (COVID-19) 患者的及时数据预测了自杀倾向.
- 这项研究解决了对COVID-19幸存者的心理健康风险早期查工具的需求.
研究的目的:
- 开发和验证在过去一个月内被诊断患有COVID-19的患者自杀倾向的预测模型.
- 创建基于及时的患者数据的查工具,用于公共心理健康应用.
主要方法:
- 对96,694名韩国COVID-19患者的数据进行分析.
- 使用分类和回归树 (CART) 和随机森林模型.
- 包括39个特征:人口统计,COVID-19因素和心理症状 (抑郁,焦虑,PTSD).
主要成果:
- 随机森林模型实现了0.85曲线下的面积,灵敏度为73.4%,特异性为83.9%.
- 自杀倾向的关键预测因素包括自杀念头,疲劳,焦虑和抑郁情绪.
- 根据表现最好的模型,开发了一个分数卡和截止分数.
结论:
- 成功开发了一种高性能模型,用于预测韩国COVID-19患者的自杀倾向.
- 开发的得分卡增强了该模型在公共心理健康环境中的实际应用.
- 这项研究为早期识别和干预COVID-19患者的心理健康问题提供了宝贵的工具.
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