Scaling Up: Multisite Open-Label Clinical Trials of MDMA-Assisted Therapy for Severe Posttraumatic Stress Disorder
Bibliographic record
Abstract
Background: Posttraumatic stress disorder (PTSD) is a debilitating mental health condition associated with serious adverse health outcomes and functional impairment. Previous MDMA–assisted therapy (MDMA-AT) studies have shown promising results in single site studies. Two open-label studies tested this modality in multisite clinical trials to assess the feasibility of scaling this manualized therapy across 14 North American sites. Method: Cotherapist dyads were trained in the manualized MDMA-AT protocol and administered three experimental sessions 3 to 5 weeks apart among participants with severe PTSD. Cotherapist dyads were provided clinical supervision and evaluated for protocol adherence by centralized raters. Clinician-Administered PTSD Scale for DSM-5 (CAPS-5) assessed change in symptoms severity. Results: Adherence rating scores were high across cotherapist dyads ( M = 95.08%, SD = 3.70%) and sites ( M = 95.23%, SD = 2.20%). CAPS-5 scores decreased following 3 MDMA-AT sessions at 18 weeks post baseline (Δ M = −29.99, Δ SD = 13.45, p < .0001, n = 37, Cohen’s d = 2.2, confidence interval [1.97, 2.47]). MDMA was well tolerated. Conclusions: These findings corroborate previous results that MDMA-AT can achieve significant improvements in PTSD symptom severity and demonstrate scalability of manualized therapy across clinic sites in the United States and Canada.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".