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Posttraumatic Stress Disorder Symptom Network Analysis in U.S. Military Veterans: Examining the Impact of Combat Exposure.
Abstract
Recent work inspired by graph theory has begun to conceptualize mental disorders as
networks of interacting symptoms. Posttraumatic stress disorder (PTSD) symptom networks
have been investigated in clinical samples meeting full diagnostic criteria, including
military veterans, natural disaster survivors, civilian survivors of war, and child
sexual abuse survivors. Despite reliable associations across reported networks, more
work is needed to compare central symptoms across trauma types. Additionally, individuals
without a diagnosis who still experience symptoms, also referred to as subthreshold
cases, have not been explored with network analysis in veterans. A sample of 1,050
Iraq/Afghanistan-era U.S. military veterans (851 males, mean age = 36.3, SD = 9.53)
meeting current full-criteria PTSD (n = 912) and subthreshold PTSD (n = 138) were
assessed with the Structured Clinical Interview for DSM-IV Disorders (SCID). Combat
Exposure Scale (CES) scores were used to group the sample meeting full-criteria into
high (n = 639) and low (n = 273) combat exposure subgroups. Networks were estimated
using regularized partial correlation models in the R-package qgraph, and robustness
tests were performed with bootnet. Frequently co-occurring symptom pairs (strong network
connections) emerged between two avoidance symptoms, hypervigilance and startle response,
loss of interest and detachment, as well as, detachment and restricted affect. These
associations replicate findings reported across PTSD trauma types. A symptom network
analysis of PTSD in a veteran population found significantly greater overall connectivity
in the full-criteria PTSD group as compared to the subthreshold PTSD group. Additionally,
novel findings indicate that the association between intrusive thoughts and irritability
is a feature of the symptom network of veterans with high levels of combat exposure.
Mean node predictability is high for PTSD symptom networks, averaging 51.5% shared
variance. With the tools described here and by others, researchers can help refine
diagnostic criteria for PTSD, develop more accurate measures for assessing PTSD, and
eventually inform therapies that target symptoms with strong network connections to
interrupt interconnected symptom complexes and promote functional recovery.
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Journal articlePermalink
https://hdl.handle.net/10161/18138Published Version (Please cite this version)
10.3389/fpsyt.2018.00608Publication Info
Phillips, Rachel D; Wilson, Sarah M; Sun, Delin; VA Mid-Atlantic MIRECC Workgroup;
& Morey, Rajendra (2018). Posttraumatic Stress Disorder Symptom Network Analysis in U.S. Military Veterans:
Examining the Impact of Combat Exposure. Frontiers in psychiatry, 9. pp. 608. 10.3389/fpsyt.2018.00608. Retrieved from https://hdl.handle.net/10161/18138.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Rajendra A. Morey
Professor of Psychiatry and Behavioral Sciences
Research in my lab is focused on brain changes associated with posttraumatic stress
disorder (PTSD), traumatic brain injury (TBI), and other neuropsychiatric disorders.
We apply several advanced methods for understanding brain function including functional
MRI, structural MRI, diffusion tensor imaging, and genetic effects.
Sarah M Wilson
Assistant Professor in Psychiatry and Behavioral Sciences
Sarah M. Wilson is an Assistant Professor in the Department of Psychiatry & Behavioral
Sciences at the Duke University School of Medicine, with a secondary appointment in
the Department of Population Health Sciences and a faculty affiliation in the Duke
Center for Health Policy and Inequalities Research. She is a Research Investigator
and Co-Lead of the Diversity, Equity, and Inclusion Core at the Veterans Affairs Center
of Innovation to Accelerate Discovery and Practice Transformation (ADAP
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