Developing a model of post-workshop consultation for clinicians learning to deliver Cognitive Processing Therapy for posttraumatic stress disorder
Bibliographic record
Abstract
Best practice in training clinicians to deliver evidence-based psychotherapies includes workshop attendance followed by post-workshop consultation. Although previous research highlights the importance of consultation, little is known about what makes for effective consultation, and no model of clinical consultation currently exists. The primary aims of this study were to identify the primary elements of consultation, and develop a model of consultation in a sample of clinicians learning to deliver Cognitive Processing Therapy (CPT; Resick, Monson, & Chard, 2014), an evidence-based psychotherapy for posttraumatic stress disorder. The study was conducted from a realist perspective, a paradigm that is particularly useful for theory building. The study involved the participation of mental health clinicians (N = 41) who attended one of five CPT workshops, and CPT consultants (N = 6) who provided the clinicians with post-workshop consultation for six months following the workshop. Thirty audio recorded consultation calls were randomly selected and transcribed. The data was coded and analyzed using thematic analysis. The kappa statistic measuring inter-rater reliability was .80. The following contextual factors were identified: access to group support, clinicians joining late, clinicians not having content to discuss, study participation, and technological disruptions. Knowledge consolidation and case conceptualization were identified as the overarching functions of consultation. The remaining elements of consultation were classified into the following themes: Organization, Asking for Help, Directive Instruction, Non-Directive Instruction, and Provision of Feedback. Two hypothesized mechanisms of consultation, reflection and connectedness, wereidentified. A comprehensive model positing how consultation works was presented. Additionally, three sets of context-mechanism-outcome configurations were presented. The model of consultation was compared to the model of clinical supervision proposed by Milne and colleagues (2008). Finally, the usefulness of Kolb’s (1984) model of experiential learning was explored as a framework for understanding the learning that occurs during clinical consultation. Based on the study’s findings, several recommendations for clinical practice were made. An important next step is to test the proposed theory, and to assess the relationship between the use of various elements of consultation and the development of proficiency in delivering CPT.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".