开发一个风险因素框架,以告知机器学习对年轻人的心理健康问题的预测:Delphi研究
Katherine Parkin1,2,3, Ryan Crowley4, Rachel Sippy2
1Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, United Kingdom.
一个新的理论框架确定了287个年轻人的心理健康风险因素. 这份路线图有助于开发准确的预测模型,用于早期识别心理健康问题.
科学领域:
- 精神病学和心理健康 精神病学和心理健康
- 发展心理学 发展心理学
- 公共卫生 公共卫生
背景情况:
- 年轻人的心理健康问题越来越令人担忧.
- 早期干预需要准确的预测模型.
- 现有的框架可能缺乏全面性或发展视角.
研究的目的:
- 开发心理健康风险因素的理论框架.
- 为青年心理健康问题的预测模型的创建提供信息.
- 在整个生命过程中建立一个全面的风险因素清单.
主要方法:
- 进行了25名专家的3轮Delphi研究.
- 文献搜索和利益相关者讨论为最初的框架提供了信息.
- 风险因素按生命阶段的预测重要性排名.
主要成果:
- 建立了一个共识框架,包括8个领域和5个生命阶段的287个风险因素.
- 社会,环境,心理和心理健康领域的排名最高.
- 热图说明了风险因素在不同生命阶段的影响.
结论:
- 该框架作为建设更准确的心理健康预测模型的路线图.
- 它有助于有针对性地纳入发育风险因素.
- 优先考虑健康公平性和多学科视角,以实现稳健的模型开发.
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