一个理想化和值的社会推理模型
Giles W Story1, Ryan Smith2, Michael Moutoussis3
1Division of Psychiatry, University College London.
Psychological review
|August 21, 2023
概括
这项研究引入了贝叶斯的二分论思维模型,或"分裂",解释了"好"或"坏"的坚硬信念如何形成和更新. 该模型量化了分裂易感性,并显示了边界性人格障碍与健康个体之间的明显模式.
科学领域:
- 认知心理学 认知心理学
- 计算精神病学是一种计算精神病学.
- 精神疾病 精神疾病
背景情况:
- 两极化的信念,称为二分论思维或"分裂",是常见的,是几种精神疾病的特征.
- 现有的理论是描述性的;需要一个定量模型来解释这些刚性信念的出现和更新.
研究的目的:
- 引入贝叶斯分裂模型,量化将个人或对象分类为严格"好"或"坏"的倾向.
- 预测二分论信念是如何根据新信息形成和更新的,考虑到上下文依赖性和时间稳定性.
- 测量分裂易感性及其在临床群体中的表现的个体差异.
主要方法:
- 开发了贝叶斯计算模型,以参数化对象的严格分类,将其分类为"好"或"坏".
- 模拟了对外部因素的反证据的归因,以巩固理想化或值的信念.
- 将模型与健康参与者和边缘性人格障碍患者的经验数据相匹配.
主要成果:
- 该模型展示了分裂如何依赖上下文,但随着时间的推移而稳定,由足够的反证据引发的信念转变.
- 健康的参与者在持有"好"信念时表现出不太容易变化的性格印象,而边缘性人格障碍患者则表现出更高,对称的分裂.
- 该模型成功地量化了个人对关系不稳定性的敏感性.
结论:
- 建议的贝叶斯框架提供了对二分论思维及其更新机制的定量解释.
- 在健康个体和边缘性人格障碍患者之间,分裂动态有显著的差异,突出了临床相关性.
- 生成模型在心理治疗中的关系和情感动态的理解和建模方面有潜在的应用.
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