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Posttraumatic Stress Disorder Symptom Network Analysis in U.S. Military Veterans: Examining the Impact of Combat Exposure

Overview of attention for article published in Frontiers in Psychiatry, November 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

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1 Redditor

Citations

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Title
Posttraumatic Stress Disorder Symptom Network Analysis in U.S. Military Veterans: Examining the Impact of Combat Exposure
Published in
Frontiers in Psychiatry, November 2018
DOI 10.3389/fpsyt.2018.00608
Pubmed ID
Authors

Rachel D. Phillips, Sarah M. Wilson, Delin Sun, VA Mid-Atlantic MIRECC Workgroup, Rajendra Morey, Elizabeth Van Voorhees, Christine E. Marx, Patrick S. Calhoun, John A. Fairbank, Larry A. Tupler, Jean C. Beckham, Mira Brancu, Cindy M. Swinkels, Scott D. McDonald, Ruth Yoash-Gantz, Katherine H. Taber, Robin Hurley, Eric A. Dedert, Eric B. Elbogen, Jason Kilts, Angela C. Kirby, Scott Moore, Jared A. Rowland, Steven T. Szabo, Nathan A. Kimbrel, Jennifer C. Naylor, Henry R. Wagner

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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The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 74 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 11%
Student > Master 8 11%
Researcher 6 8%
Student > Doctoral Student 4 5%
Student > Bachelor 4 5%
Other 10 14%
Unknown 34 46%
Readers by discipline Count As %
Psychology 18 24%
Nursing and Health Professions 6 8%
Neuroscience 4 5%
Social Sciences 4 5%
Medicine and Dentistry 3 4%
Other 4 5%
Unknown 35 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 January 2019.
All research outputs
#5,560,782
of 23,114,117 outputs
Outputs from Frontiers in Psychiatry
#2,398
of 10,230 outputs
Outputs of similar age
#111,244
of 437,538 outputs
Outputs of similar age from Frontiers in Psychiatry
#88
of 252 outputs
Altmetric has tracked 23,114,117 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,230 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has done well, scoring higher than 76% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 437,538 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 252 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.