Abstract
Negative posttraumatic cognitions, or negative trauma-related thoughts and appraisals, contribute to the onset and chronicity of posttraumatic stress disorder (PTSD) and other comorbid conditions, like eating disorders (EDs). PTSD and EDs are highly comorbid, and negative posttraumatic cognitions are one hypothesized pathway contributing to the onset and maintenance of PTSD-ED comorbidity. Yet, there is a lack of information about the ways in which specific types of negative posttraumatic cognitions relate to ED symptoms. To address this gap in the literature, the present study used network analysis to understand the connections between negative posttraumatic cognitions and ED symptoms in two separate studies of United States (U.S.) veteran men and women (post-9/11 and any service era) with a history of trauma exposure. Veterans in both studies completed self-report measures of trauma exposure, negative posttraumatic cognitions, and ED symptoms. Network analytic models stratified by sample and biological sex revealed (1) a clustering of like nodes together and (2) sex differences in network strength (but not structure) in the post-9/11 sample and network equivalence across sex in the any service era sample. Among the ED symptoms, the shape/weight concerns node was most strongly connected to negative posttraumatic cognitions. The negative posttraumatic cognitions about self node was most strongly connected to ED symptoms. Overall, network model findings suggest that cognitive factors are important for understanding PTSD-ED comorbidity among male and female U.S. military veterans. Shape/weight concerns and negative cognitions about self might be useful clinical targets in PTSD-ED integrated treatment approaches.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 37-44 |
| Number of pages | 8 |
| Journal | Journal of Psychiatric Research |
| Volume | 201 |
| DOIs | |
| State | Published - Oct 2026 |
Bibliographical note
Publisher Copyright:© 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
PubMed: MeSH publication types
- Journal Article
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