Commentary on the Special Issue on Network Analysis: Assessment, Intervention, Theory, and the Nature of Reality: Actualizing the Potential of Network Perspectives on Posttraumatic Stress Disorder.

This commentary on the Journal of Traumatic Stress special issue on network analysis explores the network perspective on posttraumatic stress disorder (PTSD), emphasizing the advances in research made in this collection of articles. The commentary is organized around the following themes related to actualizing the perspective's methodological, assessment, and intervention potential and the potential shift in the theoretical underpinnings of mental disorders that networks models imply. First, extant data using network analysis suggest that reactions to traumatic stress are more complicated than once thought but that this complexity does not mean efficient, relatively simple heuristics to aid assessment and intervention do not exist. Attention to methodological issues in symptom assessment may help move this aspect of the research forward. Second, the extant research is largely correlational and has not yet established causal linkages, although temporal associations underlying network models are being identified. Prospective and intervention studies employing network analysis are critical. Third, the network perspective of PTSD symptoms may advance research on the mechanisms of risk and resilience (e.g., neurodevelopmental, cognitive behavioral, emotional, and social models) by helping link symptoms to theoretical causal processes. A developmental framework that views the effect of traumatic stress in terms of temporal cascades of reactions with both negative and potentially positive cognitive, behavioral, social, and emotional outcomes fits the network analysis model. Fourth, network models call into question some of the fundamental assumptions underlying the conceptualization of mental disorders, leaving several ontological questions and implications currently unanswered; research examining the implications of the new assumptions is needed.