Wigman J T W, van Os J, Borsboom D, Wardenaar K J, Epskamp S, Klippel A, Viechtbauer W, Myin-Germeys I, Wichers M
Department of Psychiatry,University of Groningen, University Medical Center Groningen,Groningen,The Netherlands.
Department of Psychiatry and Psychology,School of Mental Health and Neuroscience, Maastricht University Medical Center,Maastricht,The Netherlands.
Psychol Med. 2015 Aug;45(11):2375-87. doi: 10.1017/S0033291715000331. Epub 2015 Mar 25.
It has been suggested that the structure of psychopathology is best described as a complex network of components that interact in dynamic ways. The goal of the present paper was to examine the concept of psychopathology from a network perspective, combining complementary top-down and bottom-up approaches using momentary assessment techniques.
A pooled Experience Sampling Method (ESM) dataset of three groups (individuals with a diagnosis of depression, psychotic disorder or no diagnosis) was used (pooled N = 599). The top-down approach explored the network structure of mental states across different diagnostic categories. For this purpose, networks of five momentary mental states ('cheerful', 'content', 'down', 'insecure' and 'suspicious') were compared between the three groups. The complementary bottom-up approach used principal component analysis to explore whether empirically derived network structures yield meaningful higher order clusters.
Individuals with a clinical diagnosis had more strongly connected moment-to-moment network structures, especially the depressed group. This group also showed more interconnections specifically between positive and negative mental states than the psychotic group. In the bottom-up approach, all possible connections between mental states were clustered into seven main components that together captured the main characteristics of the network dynamics.
Our combination of (i) comparing network structure of mental states across three diagnostically different groups and (ii) searching for trans-diagnostic network components across all pooled individuals showed that these two approaches yield different, complementary perspectives in the field of psychopathology. The network paradigm therefore may be useful to map transdiagnostic processes.
有人提出，精神病理学的结构最好被描述为一个由各成分组成的复杂网络，这些成分以动态方式相互作用。本文的目的是从网络角度审视精神病理学的概念，结合使用即时评估技术的互补性自上而下和自下而上的方法。
使用了一个来自三组人群（诊断为抑郁症、精神障碍或未诊断出疾病的个体）的汇总经验取样法（ESM）数据集（汇总样本量N = 599）。自上而下的方法探索了不同诊断类别中精神状态的网络结构。为此，比较了三组人群中五个即时精神状态（“愉悦”“满足”“低落”“不安”和“多疑”）的网络。互补性的自下而上的方法使用主成分分析来探究从经验得出的网络结构是否能产生有意义的高阶聚类。
临床诊断个体具有连接更紧密的即时网络结构，尤其是抑郁症组。与精神障碍组相比，该组在积极和消极精神状态之间也表现出更多的相互联系。在自下而上的方法中，精神状态之间的所有可能连接被聚类为七个主要成分，这些成分共同捕捉了网络动态的主要特征。
我们（i）比较三个诊断不同组的精神状态网络结构，以及（ii）在所有汇总个体中寻找跨诊断网络成分的结合表明，这两种方法在精神病理学领域产生了不同的、互补的观点。因此，网络范式可能有助于描绘跨诊断过程。
