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Hierarchical Bayesian models of social inference for probing persecutory delusional ideation.
Journal of Psychopathology and Clinical Science ( IF 4.6 ) Pub Date : 2020-08-01 , DOI: 10.1037/abn0000500
Andreea Oliviana Diaconescu 1 , Katharina V Wellstein 1 , Lars Kasper 1 , Christoph Mathys 2 , Klaas Enno Stephan 1
Affiliation  

While persecutory delusions (PDs) have been linked to fallacies of reasoning and social inference, computational characterizations of delusional tendencies are rare. Here, we examined 151 individuals from the general population on opposite ends of the PD spectrum (Paranoia Checklist [PCL]). Participants made trial-wise predictions in a probabilistic lottery, guided by advice from a more informed human and a nonsocial cue. Additionally, 2 frames differentially emphasized causes of invalid advice: (a) the adviser's possible intentions (dispositional frame) or (b) the rules of the game (situational frame). We applied computational modeling to examine possible reasons for group differences in behavior. Comparing different models, we found that a hierarchical Bayesian model (hierarchical Gaussian filter) explained participants' responses better than other learning models. Model parameters determining participants' belief updates about the adviser's fidelity and the contribution of prior beliefs about fidelity to trial-wise decisions, respectively, showed significant Group × Frame interactions: High PCL scorers held more rigid beliefs about the adviser's fidelity across both experimental frames and relied less on advice in situational frames than low scorers. These results suggest that PD tendencies are associated with rigid beliefs and prevent adaptive use of social information in "safe" contexts. This supports previous proposals of a link between PD and aberrant social inference. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

中文翻译:

用于探索被害妄想观念的社会推理的分层贝叶斯模型。

虽然被害妄想(PD)与推理和社会推理的谬误有关,但妄想倾向的计算特征却很少见。在这里,我们检查了 151 名来自 PD 频谱两端的普通人群(偏执狂检查表 [PCL])。参与者在概率彩票中做出了明智的预测,由更知情的人和非社会线索的建议指导。此外,2 个框架不同地强调了无效建议的原因:(a)顾问的可能意图(处置框架)或(b)游戏规则(情境框架)。我们应用计算建模来检查群体行为差异的可能原因。比较不同的模型,我们发现分层贝叶斯模型(分层高斯滤波器)解释了参与者的 关于顾问忠诚度的信念更新和关于忠诚度的先前信念对试验决策的贡献分别显示出显着的组×框架相互作用:高 PCL 得分者在两个实验框架中对顾问的忠诚度持有更严格的信念,并且较少依赖于建议情境框架比低分者。这些结果表明,PD 倾向与僵化的信念相关,并阻止在“安全”环境中适应性地使用社会信息。这支持了先前关于 PD 与异常社会推理之间联系的提议。(PsycInfo 数据库记录 (c) 2020 APA,保留所有权利)。关于顾问忠诚度的信念更新和关于忠诚度的先前信念对试验决策的贡献分别显示出显着的组×框架相互作用:高 PCL 得分者在两个实验框架中对顾问的忠诚度持有更严格的信念,并且较少依赖于建议情境框架比低分者。这些结果表明,PD 倾向与僵化的信念相关,并阻止在“安全”环境中适应性地使用社会信息。这支持了先前关于 PD 与异常社会推理之间联系的提议。(PsycInfo 数据库记录 (c) 2020 APA,保留所有权利)。与低分者相比,PCL 得分高的人对顾问在两个实验框架中的忠诚度抱有更严格的信念,并且在情境框架中对建议的依赖程度较低。这些结果表明,PD 倾向与僵化的信念相关,并阻止在“安全”环境中适应性地使用社会信息。这支持了先前关于 PD 与异常社会推理之间联系的提议。(PsycInfo 数据库记录 (c) 2020 APA,保留所有权利)。与低分者相比,PCL 得分高的人对顾问在两个实验框架中的忠诚度抱有更严格的信念,并且在情境框架中对建议的依赖程度较低。这些结果表明,PD 倾向与僵化的信念相关,并阻止在“安全”环境中适应性地使用社会信息。这支持了先前关于 PD 与异常社会推理之间联系的提议。(PsycInfo 数据库记录 (c) 2020 APA,保留所有权利)。
更新日期:2020-08-01
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