A randomized controlled dismantling trial of post-workshop consultation strategies to increase effectiveness and fidelity to an evidence-based psychotherapy for Posttraumatic stress disorder
Bibliographic record
Abstract
BACKGROUND: Posttraumatic Stress Disorder (PTSD) is a serious mental health condition with substantial costs to individuals and society. Among military veterans, the lifetime prevalence of PTSD has been estimated to be as high as 20%. Numerous research studies have demonstrated that short-term cognitive-behavioral psychotherapies, such as Cognitive Processing Therapy (CPT), lead to substantial and sustained improvements in PTSD symptoms. Despite known benefits, only a minority of clinicians provide these therapies. Transferring this research knowledge into clinical settings remains one of the largest hurdles to improving the health of veterans with PTSD. Attending a workshop alone is insufficient to promote adequate knowledge transfer and sustained skill; however, relatively little research has been conducted to identify effective post-training support strategies. METHODS: The current study investigates whether clinicians receiving post-workshop support (six-month duration) will deliver CPT with greater fidelity (i.e., psychotherapy adherence and competence) and have improved patient outcomes compared with clinicians receiving no formal post-workshop support. The study conditions are: technology-enhanced group tele-consultation; standard group tele-consultation; and fidelity assessment with no consultation. The primary outcome is independent assessment (via audio-recordings) of the clinicians' adherence and competence in delivering CPT. The secondary outcome is observed changes in patient symptoms during and following treatment as a function of clinician fidelity. Post-consultation interviews with clinicians will help identify facilitators and barriers to psychotherapy skill acquisition. The study results will inform how best to implement and transfer evidence-based psychotherapy (e.g., CPT) to clinical settings to attain comparable outcomes to those observed in research settings. DISCUSSION: Findings will deepen our understanding of how much and what type of support is needed following a workshop to help clinicians become proficient in delivering a new protocol. Several influences on clinician learning and patient outcomes will be discussed. An evidence-based model of clinical consultation will be developed, with the ultimate goal of informing policy and influencing best practice in clinical consultation. TRIAL REGISTRATION: ClinicalTrials.gov: NCT01861769.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 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".