测量精神病理学层次模型的机会

JCPP advances Pub Date : 2023-07-22 DOI:10.1002/jcv2.12187
Erik Pettersson
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摘要

所有的精神现象都是正相关的,有几种不同的模型可以解释这一观察结果。这些包括相关因素、网络、作为结果的一般精神病理和层次模型。由一个一般因素和几个(一般因素-残差)特定因素组成的分层模型的优点是,一般因素提供了一个可靠地衡量整体痛苦和损害的机会,而特定因素可能提高区分具有不同问题的个体的能力。尽管如此,其他模型也有各自的优势,并且从经验上确定哪种模型最能解释精神病学中的积极因素仍然具有挑战性。相反,我提出了两个支持分层模型的非经验论点。首先,通过孤立地测量一般因素,具体因素往往包括有利和不利的相关因素,这可能会减少耻辱,而精神病诊断总体上只与不利的结果相关。第二,一般精神病理因素表现出一种不同寻常的心理测量特性,如果它们具有相似的效价,它就包括了意义相反的症状(例如,自我报告的症状,如易受骗和偏执,懒惰和工作狂,以及恐惧和冷漠的负荷在同一方向),人们可能希望将其与捕获症状内容的方差隔离开来进行测量。我的结论是推测基于层次模型设计的测试可能有助于临床评估。
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Opportunities of measuring hierarchical models of psychopathology

All psychiatric phenomena are positively associated, and several different models can account for this observation. These include the correlated factors, network, general psychopathology as outcome, and hierarchical models. Advantages of hierarchical models, which consist of one general and several (general factor-residualized) specific factors, is that the general factor provides an opportunity to reliably measure global distress and impairment, while the specific factors might improve the ability to discriminate between individuals with different kinds of problems. Nevertheless, other models also have their respective advantages, and it remains challenging to empirically determine which model best accounts for the positive manifold in psychiatry. Instead, I present two non-empirical arguments in favor of hierarchical models. First, by measuring the general factor in isolation, the specific factors tend to include both favorable and unfavorable correlates, which might reduce stigma compared to psychiatric diagnoses that by and large are associated with only unfavorable outcomes. Second, the general psychopathology factor displays an unusual psychometric property in that it includes symptoms of opposite meaning if they have similar valence (e.g., self-reported symptoms such as gullible and paranoid, lazy and workaholic, and terrified and apathetic load in the same direction), which one might want to measure in isolation from variance capturing the content of symptoms. I conclude by speculating that tests designed based on hierarchical models might help clinical assessment.

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