Lessons Learned from Leading a Canadian Psychotherapy Medical Education Program
Bibliographic record
Abstract
Introduction Under Canadian training requirements, psychiatry residents must demonstrate proficiency in various psychotherapy modalities such as cognitive behavior therapy and psychoanalytic psychotherapy. Objective Building from an earlier case study of the development of a comprehensive psychotherapy education program, the current presentation explores lessons learned from the ongoing delivery of this program to psychiatrists in training. Innovative strategies, opportunities, challenges and current outcomes on the delivery of this program are explored through a case study framework. The design, implementation and ongoing operation of the psychotherapy education program are based on the Royal College of Physicians of Canada specialty training requirements in psychiatry. Methods In the context of the case study framework, a Canadian psychotherapy training program for psychiatrists in training is analysed. The psychotherapy education model is designed and operated to offer a gradual and integrated educational and clinical experience in psychotherapy over four years of training. Results The psychotherapy education program was investigated to explore new frameworks and innovative strategies of delivery and operation. Among the lessons learned were the need to maintain formally structured, modality specific teaching and supervision, video recording of sessions in supervision, provision of additional protected psychotherapy time, access to online training resources and utilization of non-physician mental health experts. Conclusions This presentation will investigate the ongoing insights emerging from managing delivery of different psychotherapy competencies to psychiatrists in training in a Royal College of Physicians of Canada accredited program. Implications for training, practice and future research will be discussed. Disclosure of interest The authors have not supplied their declaration of competing interest.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".