Nightmare Frequency, Nightmare Distress and the Efficiency of Trauma-Focused Cognitive Behavioral Therapy for Post-Traumatic Stress Disorder
Bibliographic record
Abstract
BACKGROUND: Up to 71% of trauma victims diagnosed with PTSD have frequent nightmares (NM), compared to only 2% to 5% of the general population. OBJECTIVES: The present study examined whether nightmares before the beginning of cognitive behavior therapy (CBT) for post-traumatic stress disorder (PTSD) could influence overall PTSD symptom reduction for 71 individuals with PTSD and different types of traumatic events. PATIENTS AND METHODS: Participants received a validated CBT of 20 weekly individual sessions. They were evaluated at five measurement times: at pre-treatment, after the third and ninth session, at post-treatment, and at 6 months follow-up. RESULTS: The presence of nightmares did not impact overall CBT efficiency. Specific CBT components were efficient in reducing the frequency and distress of nightmares. CONCLUSIONS: Most participants no longer had PTSD but some still had nightmares.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".