Posttraumatic stress disorder treatment preference: Prolonged exposure therapy, cognitive processing therapy, or medication therapy?
Bibliographic record
Abstract
= 126) read descriptions of front-line recommended treatments for PTSD, including prolonged exposure therapy (PE), cognitive-processing therapy (CPT), and medication therapy (MT). Participants selected their treatment of choice and provided ratings of the credibility and their personal reactions to each treatment. Participants generally preferred psychotherapeutic treatments (CPT and PE) over MT, and this finding persisted when considering likely PTSD. Trauma support group participants and students with no likely PTSD showed preference towards CPT over PE, and students with likely PTSD preferred both CPT and PE over MT. In both groups, credibility and personal reaction ratings were also generally higher for the psychotherapeutic treatments than MT, with the highest ratings of credibility and personal reactions for CPT. There was a significant interaction between treatment type and likely PTSD for credibility and personal reaction ratings among students, such that students with likely PTSD had lower credibility and personal reaction ratings to MT. Determining preference for PTSD treatment has important implications for maximizing treatment efficacy, adherence, and engagement. Our results indicate that individuals generally prefer psychotherapeutic treatments, highlighting the need to increase the availability and utilization of evidence-based psychotherapeutic treatments for PTSD. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.003 |
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".