The effects of MDMA-assisted therapy on alcohol and substance use in a phase 3 trial for treatment of severe PTSD
Bibliographic record
Abstract
BACKGROUND: Post-traumatic stress disorder (PTSD) is commonly associated with alcohol and substance use disorders (ASUD). A randomized, placebo-controlled, phase 3 trial demonstrated the safety and efficacy of MDMA-assisted therapy (MDMA-AT) for the treatment of severe PTSD. This analysis explores patterns of alcohol and substance use in patients receiving MDMA-AT compared to placebo plus therapy (Placebo+Therapy). METHODS: Adult participants with severe PTSD (n = 90) were randomized to three blinded trauma-focused therapy sessions with either MDMA-AT or Placebo+Therapy. Eligible participants met DSM-5 criteria for severe PTSD and could meet criteria for mild (current) or moderate (early remission) alcohol or cannabis use disorder; other SUDs were excluded. The current analyses examined outcomes on standardized measures of hazardous alcohol (i.e., Alcohol Use Disorder Identification Test; AUDIT) and drug (i.e., Drug Use Disorder Identification Test; DUDIT) use at baseline prior to randomization and at study termination. RESULTS: There were no treatment group differences in AUDIT or DUDIT scores at baseline. Compared to Placebo+therapy, MDMA-AT was associated with a significantly greater reduction in mean (SD) AUDIT change scores (Δ = -1.02 (3.52) as compared to placebo (Δ = 0.40 (2.70), F (80, 1) = 4.20, p = 0.0436; Hedge's g= .45). Changes in DUDIT scores were not significantly different between treatment groups. CONCLUSIONS: MDMA-AT for severe PTSD may also lead to subclinical improvements in alcohol use. MDMA-AT does not appear to increase risk of illicit drug use. These data provide preliminary evidence to support the development of MDMA-AT as an integrated treatment for co-occurring PTSD and ASUD.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".