MDMA-assisted brief cognitive behavioral conjoint therapy for PTSD: Study protocol for a pilot study
Bibliographic record
Abstract
Background: Posttraumatic Stress Disorder (PTSD) impacts both individual and relational functioning. Veteran couples are at increased risk of relationship distress due to military stressors such as deployment, family reintegration, and traumatic stress. Although both Cognitive-Behavioral Conjoint Therapy (CBCT) and its brief version (bCBCT) consistently have large effects on reducing PTSD symptoms, these treatments have more variable effects on relational outcomes. Given the impact of relationship functioning on the overall health of veterans, improving the effect of PTSD treatments on relationship functioning is an essential area of research. One promising path is the role of MDMA (3,4-methylenedioxymethamphetamine)-assisted therapy in augmenting the relational impact of established therapeutic interventions such as bCBCT. Method/Design: = 16). Therapy teams trained in bCBCT and MDMA-assisted therapy will deliver bCBCT combined with two MDMA sessions and two couple emotion focused integration sessions. PTSD symptom severity and relationship functioning outcomes will be evaluated. Conclusion: This is the first study to examine the efficacy of MDMA-assisted bCBCT for improving PTSD and relationship functioning among a sample of U.S. military veterans and their partners. This project could provide an opportunity to pilot a scalable model of treating PTSD within the Veterans Affairs healthcare system and leverage the benefits of MDMA for veterans with PTSD, as well as the downstream benefits to their partner on both individual and relationship functioning. ClinicalTrials.gov Identifier: NCT05979844.
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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 | 0.013 | 0.009 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.065 | 0.012 |
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".