Implementing evidence-based obesity management guidelines requires development of medical competencies: A commentary outlining future directions in obesity education in Canada
Bibliographic record
Abstract
Background: This commentary provides an overview of forthcoming activities by Obesity Canada (OC) to inform obesity competencies in medical education. Competencies in medical education refer to abilities of medical professionals to appropriately provide patients the care they need. A recognized Canadian framework for informing medical competencies is CanMEDs. Additionally, the Obesity Medicine Education Collaborative (OMEC) provides 32 obesity specific medical competencies to be integrated across medical education curriculum. OC released the first globally recognized Adult Obesity Clinical Practice Guideline (CPGs) in 2020 inclusive of 80 recommendations. Referring to the CanMEDs and OMEC competencies, OC is developing medical education competencies for caring for patients who have obesity in line with the recent CPGs that can be applied to health professions education programs around the world. Methods: Activities being completed by OC's Education Action Team include a scoping review to summarize Canadian obesity medical education interventions or programs. Next, with expert consensus a competency set is being developed by utilizing the CanMEDs Framework, OMEC and the CPGs. Following this, OC will initially survey undergraduate medical programs across the country and determine to what degree they are meeting the competencies in content delivery. These findings will lead to a national report card outlining the current state of obesity medical education in Canada within undergraduate medical education. Results: To date, OC has completed the scoping review and the competency set. The Education Action Team is in the process of developing the survey tools to assess the current delivery of obesity medical education in Canada. Conclusion: The evidenced-based report card will support advocacy to refine and enhance future educational initiatives with the overall goal of improving patient care for individuals living with obesity. The process being applied in Canada may also be applicable and modified for other regions to assess and better obesity medical education.
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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 | 0.037 | 0.182 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.016 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.015 | 0.022 |
| Insufficient payload (model declined to judge) | 0.005 | 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".