捕捉危机动态:一种新的个性化方法,使用多层次隐藏的马尔科夫建模.
Emmeke Aarts1, Barbara Montagne2, Thomas J van der Meer3
1Department of Methodology and Statistics, Utrecht University, Utrecht, Netherlands.
Frontiers in psychiatry
|January 29, 2025
概括
了解危机动态是预防的关键. 这项研究确定了不同的认知,情感和行为 (CAB) 危机状态,揭示了个性化的轨迹和需要量身定制的干预措施.
科学领域:
- 心理学 心理学 心理学
- 精神病学是一个精神病学.
- 数据科学数据科学数据科学
背景情况:
- 危机是一个复杂的,多维的现象,时间动态的理解很差.
- 有效的预防需要更深入地了解危机如何随着时间的推移而演变.
- 现有的模型缺乏细节性,无法捕捉危机期间因素的相互作用.
研究的目的:
- 通过聚合认知,情感和行为 (CAB) 因素的波动来澄清危机动态.
- 识别潜伏状态,代表个体内的不同危机轨迹.
- 为制定个性化危机预防策略提供信息.
主要方法:
- 使用了生态瞬间评估 (EMA) 频繁的自我报告问卷 (每天3次).
- 在长时间内从26名患者收集了5种CAB症状的数据 (每名患者60次测量).
- 应用多层次隐藏的马尔科夫模型 (HMM) 来隔离危机状态和动态.
主要成果:
- 确定了四个不同的,上升的基于CAB的危机状态.
- 发现保持当前状态是最有可能的,随着更高的状态而下降.
- 在状态过渡和持久性方面观察到显著的患者异质性,难以回到较低的状态.
结论:
- 多级HMM有效量化和可视化个人危机轨迹.
- 患者的异质性凸显了个性化危机预防的需要.
- 未来的统计模型应该促进对心理健康危机的个性化方法.
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