From foundations to frontiers: the status and perception of formulation teaching in Canadian English-speaking psychiatry residency programs
Bibliographic record
Abstract
Aim of the study Formulation is considered a key competence that should be taught during psychiatry training in residency. The scientific literature indicates shortcomings in teaching this clinical skill such as a lack of standardization and clear guidelines. The main objective of this research was to examine psychiatry residents’ perception regarding teaching of formulation in Canadian psychiatry residency programs. Subject or material and methods All Canadian psychiatry program directors in English programs were emailed a link for the study survey. The survey had a mix of closed and open-ended questions. With the exception of one Program Director, the survey link was distributed by all of the Program Directors. 116/661 (17.5%) of residents completed the survey. Results Overall, results of this survey indicated that residents did not feel very competent in their formulation skills, although they felt this was an important ability. Residents mostly learn it through individual supervision or through mentoring with a senior resident. Discussion Residents suggested a more structured approach in teaching formulation, as well as adding a small group format or workshops. Conclusions This research could provide guidance to educators in developing new curricula in the context of the upcoming transition to the competence-based framework by the Royal College of Physicians and Surgeons of Canada.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".