MDMA-assisted therapy significantly reduces eating disorder symptoms in a randomized placebo-controlled trial of adults with severe PTSD
Bibliographic record
Abstract
INTRODUCTION: Eating disorders (EDs) and posttraumatic stress disorder (PTSD) are highly comorbid, yet there are no proven integrative treatment modalities for ED-PTSD. In clinical trials, MDMA-assisted therapy (MDMA-AT) has shown marked success in the treatment of PTSD and may be promising for ED-PTSD. METHODS: Ninety individuals with severe PTSD received treatment in a double-blind, placebo-controlled pivotal trial of MDMA-AT. In addition to the primary (Clinician-Administered PTSD Scale) and secondary (Sheehan Disability Scale) outcome measures, the Eating Attitudes Test 26 (EAT-26) was administered for pre-specified exploratory purposes at baseline and at study termination. RESULTS: The study sample consisted of 58 females (placebo = 31, MDMA = 27) and 31 males (placebo = 12, MDMA = 19) (n = 89). Seven participants discontinued prior to study termination. At baseline, 13 (15%) of the 89 individuals with PTSD had total EAT-26 scores in the clinical range (≥20), and 28 (31.5%) had total EAT-26 scores in the high-risk range (≥11) despite the absence of active purging or low weight. In completers (n = 82), there was a significant reduction in total EAT-26 scores in the total group of PTSD participants following MDMA-AT versus placebo (p = .03). There were also significant reductions in total EAT-26 scores in women with high EAT-26 scores ≥11 and ≥ 20 following MDMA-AT versus placebo (p = .0012 and p = .0478, respectively). CONCLUSIONS: ED psychopathology is common in individuals with PTSD even in the absence of EDs with active purging and low weight. MDMA-AT significantly reduced ED symptoms compared to therapy with placebo among participants with severe PTSD. MDMA-AT for ED-PTSD appears promising and requires further study.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".