Open label pilot study on posttrauma health impacts of the Processing of Positive Memories Technique (PPMT).
Bibliographic record
Abstract
=29.25 years; 58.30% women). We used the reliable change indices and clinically significant change score approach. The following number of participants showed statistically reliable changes: 9 participants for PTSD severity (8 recovered/improved); 6 participants for depression severity (5 improved); 5 participants for positive affect levels (2 recovered/improved); 9 participants for negative affect levels (8 recovered); 9 participants for posttrauma cognitions (7 recovered/improved); 5 participants for positive emotion dysregulation (4 recovered); 11 participants for number of retrieved positive memories (3 recovered); and 5 participants for therapeutic alliance (4 recovered). PPMT may impact certain posttrauma targets more effectively (PTSD, depression, negative affect, posttrauma cognitions). PPMT may be more helpful in improving regulation rather than levels of positive affect. PPMT, if supported in further investigations, may add to the clinician tool-box of PTSD interventions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".