Sudden gains in PTSD symptoms and social functioning in cognitive processing therapy for posttraumatic stress disorder
Bibliographic record
Abstract
OBJECTIVE: Sudden gains (SGs) are rapid symptom improvements between two consecutive therapy sessions that predict treatment outcomes. This study investigated SGs in posttraumatic stress disorder (PTSD) symptoms, interpersonal relationship functioning, and social role functioning in Cognitive Processing Therapy (CPT). METHOD: Participants were 121 patients and 81 therapists involved in a parent randomized controlled hybrid implementation-effectiveness trial of CPT. Descriptive analyses examined the frequency and timing of different forms of SGs. Multilevel modeling examined the impact of the three SGs on outcomes. RESULTS: PTSD SGs occurred more often and at different sessions than SGs in facets of social functioning. Most individuals experienced only one form of SG and there were no significant clinical or demographic differences in those who had PTSD only SGs, social functioning only SGs, or both SGs. PTSD SGs and interpersonal relationship functioning SGs both predicted changes in PTSD symptoms and interpersonal difficulties over time, but not changes in social role functioning. SGs in social role functioning predicted all three forms of outcomes. CONCLUSIONS: The findings suggest that there are multiple forms of SGs in CPT beyond primary symptom changes that are predictive of patient outcomes. Clinicians should highlight various SGs that patients experience to further enhance outcomes.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".