Network Models of Post-traumatic Stress Disorder: A Meta-analysis

Abstract

Post-traumatic 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 to the first-ever meta-analytic study of network models. 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 datasets, investigated the scope of between-study heterogeneity, and assessed the performance of network models estimated from single studies. Our main findings are that: (1) While several clear symptom-links and interpretable clusters can be identified in the network, most symptoms feature very similar levels of centrality. To this end, aiming to identify central symptoms in PTSD symptom networks may not be fruitful. (2) 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. (3) Nonetheless, we found evidence that networks estimated from single studies may give rise to generalizable results, as our results aligned with previous descriptive analyses of reported network studies, and network models estimated from single samples 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.

Meta-analytic Gaussian Network Aggregation

“…We assess the performance of MAGNA in large-scale simulation studies. Finally, we exemplify the method using four datasets of posttraumatic stress disorder (PTSD) symptoms (Fried et al, 2017), and summarize findings from a larger meta-analysis of PTSD symptoms (Isvoranu et al, 2020).…”

A General Monte Carlo Method for Sample Size Analysis in the Context of Network Models

“…We select three values for the number of nodes, namely P = {10, 15, 20}. These values result in three network structures (see Figure 5), which serve as our true models, and reasonably cover typical networks encountered in the psychological literature (e.g., Isvoranu et al, 2020). Each network resulted in 17, 45, and 74, respectively, edge weights parameters.…”

Using clinical expertise and empirical data in constructing networks of trauma symptoms in refugee youth

“…how many connections a symptom has with other symptoms, are investigated (Borsboom & Cramer, 2013 ). A systematic review of 35 network analyses (Birkeland, Greene, & Spiller, 2020 ) and a network meta-analysis (Isvoranu, Epskamp, & Cheung, 2020 ) of post-traumatic stress symptoms found that, despite some similarities, relations between symptoms and their centrality differed across studies. Such heterogeneous results can be explained by the fact that samples and trauma types varied between studies.…”