A randomized clinical trial to dismantle components of cognitive processing therapy for posttraumatic stress disorder in female victims of interpersonal violence.
Bibliographic record
Abstract
The purpose of this experiment was to conduct a dismantling study of cognitive processing therapy in which the full protocol was compared with its constituent components--cognitive therapy only (CPT-C) and written accounts (WA)--for the treatment of posttraumatic stress disorder (PTSD) and comorbid symptoms. The intent-to-treat (ITT) sample included 150 adult women with PTSD who were randomized into 1 of the 3 conditions. Each condition consisted of 2 hr of therapy per week for 6 weeks; blind assessments were conducted before treatment, 2 weeks following the last session, and 6 months following treatment. Measures of PTSD and depression were collected weekly to examine the course of recovery during treatment as well as before and after treatment. Secondary measures assessed anxiety, anger, shame, guilt, and dysfunctional cognitions. Independent ratings of adherence and competence were also conducted. Analyses with the ITT sample and with study completers indicate that patients in all 3 treatments improved substantially on PTSD and depression, the primary measures, and improved on other indices of adjustment. However, there were significant group differences in symptom reduction during the course of treatment whereby the CPT-C condition reported greater improvement in PTSD than the WA condition.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".