The role of the consultant in consultation for an evidence-based treatment for PTSD.
Bibliographic record
Abstract
= 60) on post-traumatic stress disorder (PTSD) treatment fidelity and client outcomes. In addition, we assessed the accuracy of consultants' evaluations of clinicians using the Perceived Enthusiasm, Skill, and Participation scale (P-ESP). Results indicated that there was a significant effect of consultant on adherence to, but not competence in, delivering Cognitive Processing Therapy (CPT). The effect of the consultant on PTSD symptom change was not significant. Consultants significantly differed in their discussion of CPT strategies and their application to individual cases, but did not differ on reviewing and providing feedback on fidelity. Consultant perceptions as assessed by the P-ESP were not associated with clinicians' current levels of adherence or competence, suggesting that consultants may not accurately assess clinician skill during consultation. Client PTSD symptom change neither predicted, nor was predicted by, consultants' perceptions of their consultees' skill. This article outlines potential reasons for consultant effects and possible biases at play that may reduce the accuracy of consultant perceptions and presents suggestions on alternative strategies to assess clinician skill during consultation. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".