Evaluation of the reconsolidation of traumatic memories protocol for the treatment of PTSD: a randomized, wait-list-controlled trial
Bibliographic record
Abstract
Introduction: The reconsolidation of traumatic memories (RTM) is a cognitive intervention for post-traumatic stress disorder (PTSD) believed to employ reconsolidation blockade with significant potential as a cost-effective and empirically supported treatment. This is the second empirical evaluation of the intervention. Methods: This study used a randomized wait-list-controlled design ( n=30) to examine the efficacy of three sessions of RTM among male Veterans having high symptom scores on the PTSD Symptom Scale Interview (PSS-I) and the PTSD Checklist – military version (PCL-M) with current-month flashbacks and nightmares. Of the 55 volunteers, 30 met inclusion criteria and participated in the study, 15 each were randomly assigned to treatment and control conditions. After completing a six-week wait period, control subjects also received the intervention. Results: Data analyses suggest that RTM was superior to control. There were significant pre-post treatment improvements across measures of PTSD. Gains were maintained at 6 and 12-month follow-ups. At six months post, within group RTM effect sizes (Hedges' g) ranged from 2.79 to 5.33. Further, at six months post, 88% of those treated had lost the DSM diagnosis for PTSD: 15% had lost DSM diagnosis (CPL-M<50 and DSM criteria not met) and 73% were in complete remission from all symptoms (PCL-M<30). Therapist competence and adherence to treatment protocols were both strong. Patient satisfaction with the intervention was high. Discussion: Study limitations and implications for the assessment and treatment of Veterans with PTSD are discussed.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".