Posttraumatic stress disorder (PTSD) researchers have increasingly used psychological network models to investigate PTSD symptom interactions, as well as to identify central driver symptoms. It is unclear, however, how generalizable such results are. We have developed a meta-analytic framework for aggregating network studies while taking between-study heterogeneity into account and applied this framework in the first-ever meta-analytic study of PTSD symptom networks. We analyzed the correlational structures of 52 different samples with a total sample size of n = 29,561 and estimated a single pooled network model underlying the data sets, investigated the scope of between-study heterogeneity, and assessed the performance of network models estimated from single studies. Our main findings are that: (a) We identified large between-study heterogeneity, indicating that it should be expected for networks of single studies to not perfectly align with one-another, and meta-analytic approaches are vital for the study of PTSD networks. (b) While several clear symptom-links, interpretable clusters, and significant differences between strength of edges and centrality of nodes can be identified in the network, no single or small set of nodes that clearly played a more central role than other nodes could be pinpointed, except for the symptom "amnesia" that was clearly the least central symptom. (c) Despite large between-study heterogeneity, we found that network models estimated from single samples can lead to similar network structures as the pooled network model. We discuss the implications of these findings for both the PTSD literature as well as methodological literature on network psychometrics. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

中文翻译：

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创伤后应激障碍的网络模型：荟萃分析。

创伤后应激障碍 (PTSD) 研究人员越来越多地使用心理网络模型来研究 PTSD 症状相互作用，以及识别中心驱动症状。然而，尚不清楚这些结果的普遍性如何。我们开发了一个元分析框架，用于聚合网络研究，同时考虑到研究之间的异质性，并将该框架应用于有史以来第一个 PTSD 症状网络的元分析研究。我们分析了 52 个不同样本的相关结构，总样本量为 n = 29,561，并估计了数据集背后的单个汇集网络模型，调查了研究间异质性的范围，并评估了从单个研究估计的网络模型的性能. 我们的主要发现是：(a) 我们发现了很大的研究间异质性，表明应该预期单个研究的网络不会与另一个完全一致，并且元分析方法对于 PTSD 网络的研究至关重要。(b) 虽然可以在网络中识别出几个清晰的症状链接、可解释的集群以及边缘强度和节点中心性之间的显着差异，但没有一个或一小组节点明显比其他节点发挥更重要的作用除了明显是最不重要的症状“健忘症”之外。(c) 尽管研究间存在很大的异质性，我们发现从单个样本估计的网络模型可以导致与汇集网络模型相似的网络结构。我们讨论了这些发现对 PTSD 文献以及关于网络心理测量学的方法论文献的影响。（PsycInfo 数据库记录 (c) 2021 APA，保留所有权利）。