The association of traumatic events and posttraumatic stress disorder with greater eating disorder and comorbid symptom severity in residential eating disorder treatment centers
Bibliographic record
Abstract
OBJECTIVE: Traumatic events, posttraumatic stress disorder (PTSD) and related symptoms are commonly associated with eating disorders (ED). Several clinical features indicative of a more severe and complex course have been associated with traumatized ED patients, especially those with PTSD, who may be more likely admitted to residential treatment (RT). Research in this population is sparse but of increasing interest. METHOD: Adult participants (96.7% female) with EDs entering RT (n = 642) at seven sites in the U.S. completed validated self-report assessments of ED, PTSD, major depression, state-trait anxiety, and quality of life. Presumptive diagnoses of DSM-5 PTSD (PTSD+) were made via the Life Events Checklist-5 and the PTSD Symptom Checklist for DSM-5. RESULTS: PTSD+ occurred in 49.3% of patients. PTSD+ patients had significantly higher scores on all assessment measures (p ≤ .001), including measures of ED psychopathology, depression, state-trait anxiety, and quality of life. Those with PTSD+ had significantly higher numbers of lifetime traumatic event types, higher rates of almost all lifetime traumatic events, and a greater propensity toward binge-type EDs. DISCUSSION: Results confirm that ED-PTSD+ patients in RT are more symptomatic and have worse quality of life than ED patients without PTSD+. Integrated treatment approaches that effectively address ED-PTSD+ are greatly needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".