Document Type

Dissertation

Degree

Doctor of Philosophy

Major

Psychology, Clinical-Community

Date of Defense

5-4-2020

Graduate Advisor

Steven E. Bruce, Ph.D.

Committee

Ann Steffen, Ph.D.

Mike Griffin, Ph.D.

Carissa Philippi, Ph.D.

Abstract

Along with numerous combinations of symptoms, posttraumatic stress disorder (PTSD) is linked to high dropout and non-response rates in treatment. Poor treatment response may be due to an inaccurate conceptualization of PTSD. One newer approach to the conceptualization of psychopathology is network theory. Network theory posits that symptoms both directly and indirectly reinforce each other, with connections between symptoms varying in strength. Previous studies of network theory and PTSD have found intrusive symptoms to be highly central, but have not included samples of individuals traumatized by interpersonal violence. Because trauma type has been shown to predict symptom presentations, this represents an important gap in the literature. The current study attempts to address this by analyzing the PTSD and depression network of 83 adult female participants meeting criteria for PTSD from interpersonal violence. PTSD symptoms were measured using the Posttraumatic Diagnostic Scale. Using the Extended Bayesian Information Criterion Graphical Least Absolute Shrinkage and Selector Operator (EBICglasso) method, and after bootstrapping the data with 95% confidence intervals based on 1000 bootstrap iterations, a partial correlation network was created to depict the network. PTSD network results showed feeling distant and intrusive symptoms to have the highest centrality. Further, anhedonia was shown to be a bridge symptom between PTSD and depressive symptoms. These results may better connect theory to impending therapeutic action by assisting in identifying specific targets for interventions when working with PTSD in victims of interpersonal violence.

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