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一种用于研究精神分裂症患者心理理论复杂性的机器学习方法。

A machine-learning approach to investigating the complexity of theory of mind in individuals with schizophrenia.

作者信息

Bosco Francesca Marina, Colle Livia, Salvini Rogerio, Gabbatore Ilaria

机构信息

University of Turin, Department of Psychology, GIPSI Research Group, Italy.

Terzo Centro di Psicoterapia Cognitiva, Roma.

出版信息

Heliyon. 2024 May 3;10(9):e30693. doi: 10.1016/j.heliyon.2024.e30693. eCollection 2024 May 15.

Abstract

Individuals with schizophrenia have difficulty attributing mental states to themselves and to others - Theory of Mind (ToM). ToM is a complex, multifaceted theoretical construct comprising first and second order, first and third person, egocentric and allocentric perspective, and cognitive and affective ToM. Most studies addressing ToM deficit in people with schizophrenia consider it an "all-or-nothing" ability and use a classical statistical methodology to test a null hypothesis. With the present study, we investigated ToM in individuals with schizophrenia, considering its complex nature and degrees of impairment. To do this, we used a machine-learning approach to detect patterns in heterogeneous and multivariate data. Our findings highlight the complex nature of ToM deficit in individuals with schizophrenia and reveal the relationship between various different aspects of ToM.

摘要

精神分裂症患者在将心理状态归因于自己和他人方面存在困难——心理理论(ToM)。心理理论是一个复杂的、多方面的理论结构,包括一阶和二阶、第一和第三人称、自我中心和异我中心视角,以及认知和情感心理理论。大多数针对精神分裂症患者心理理论缺陷的研究将其视为一种“全或无”的能力,并使用经典统计方法来检验零假设。在本研究中,我们考虑到心理理论的复杂性质和损伤程度,对精神分裂症患者的心理理论进行了调查。为此,我们使用机器学习方法来检测异构和多变量数据中的模式。我们的研究结果突出了精神分裂症患者心理理论缺陷的复杂性质,并揭示了心理理论各个不同方面之间的关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81d1/11096895/24461a663a68/gr1.jpg

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