Relational and Growth Outcomes Following Couples Therapy With MDMA for PTSD
Bibliographic record
Abstract
Healing from trauma occurs in a relational context, and the impacts of traumatic experiences that result in post-traumatic stress disorder (PTSD) go beyond the diagnosis itself. To fully understand a treatment for PTSD, understanding its impact on interpersonal, relational, and growth outcomes yields a more fulsome picture of the effects of the treatment. The current paper examines these secondary outcomes of a pilot trial of Cognitive Behavioral Conjoint Therapy (CBCT) for PTSD with MDMA. Six romantic dyads, where one partner had PTSD, undertook a course of treatment combining CBCT for PTSD with two MDMA psychotherapy sessions. Outcomes were assessed at mid-treatment, post-treatment, and 3- and 6-month follow-up. Both partners reported improvements in post-traumatic growth, relational support, and social intimacy. Partners reported reduced behavioral accommodation and conflict in the relationship, and patients with PTSD reported improved psychosocial functioning and empathic concern. These improvements were maintained throughout the follow-up period. These findings suggest that CBCT for PTSD with MDMA has significant effect on relational and growth outcomes in this pilot sample. Improvements in these domains is central to a holistic recovery from traumatic experiences, and lends support to the utility of treating PTSD dyadically.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".