Comparing the unified protocol for transdiagnostic treatment of emotional disorders to prolonged exposure for the treatment of PTSD: Design of a non-inferiority randomized controlled trial
Bibliographic record
Abstract
Background: Prolonged Exposure (PE), a trauma-focused therapy, is one of the most efficacious treatments available for PTSD. However, many people with PTSD do not lose their diagnosis following delivery of PE. The Unified Protocol (UP) for Transdiagnostic Treatment of Emotional Disorders is a non-trauma focused treatment that may offer an alternative treatment for PTSD. Methods: This paper describes the study protocol for IMPACT, an assessor-blinded randomized controlled trial that examines the non-inferiority of UP relative to PE for participants who meet DSM-5 criteria for current PTSD. One hundred and twenty adult participants with PTSD will be randomized to receive either 10 × 90-min sessions of UP or PE with a trained provider. The primary outcome is severity of PTSD symptoms assessed by the Clinician Administered PTSD Scale for DSM-5 (CAPS-5) at post-treatment. Discussion: While evidence-based treatments are available for PTSD, high levels of treatment dropout and non-response require new approaches to be tested. The UP is based on emotion regulation theory and is effective in treating anxiety and depressive disorders, however, there has been limited application to PTSD. This is the first rigorous study comparing UP to PE in a non-inferiority randomized controlled trial and may help improve clinical outcomes for those with PTSD. Trial registration: This trial was prospectively registered with the Australian New Zealand Clinical Trials Registry, Trial ID (ACTRN12619000543189).
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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 | 0.061 | 0.069 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.007 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".