Pretreatment Posttraumatic Stress Disorder Symptom Network Metrics Predict the Strength of the Association Between Node Change and Network Change During Treatment

Abstract

Network analysis has been increasingly applied in an effort to understand complex interactions among symptoms in posttraumatic stress disorder (PTSD). Although methods that initially focused on identifying central symptoms in cross-sectional networks have been extended to longitudinal data that can reveal the relative roles of acute symptoms in the emergence of the PTSD syndrome, the association between network metrics and symptom change during treatment have yet to be explored in PTSD. To address this gap, we estimated pretreatment PTSD symptom networks in a sample of patients from a multisite clinical trial for women with full or subthreshold PTSD and substance use. We tested the hypothesis that node metrics calculated in the pretreatment network would be predictive of the strength of the association between a symptom's change and the change in the severity of all other symptoms through the course of treatment. A symptom node's strength and predictability in the pretreatment network were each strongly correlated with the association between that symptom's change and overall change across the symptom network, r(15) = .79, p < .001 and r(15) = .75, p < .001, respectively, whereas a symptom's mean severity at pretreatment was not, r(15) = .27, p = .292. These findings suggest that a node's centrality prior to treatment engagement is a predictor of its association with overall symptom change throughout the treatment process.

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