A Canadian survey of medical students and undergraduate deans on the management of patients living with obesity
Bibliographic record
Abstract
Abstract Background With over 26% of Canadian adults living with obesity, undergraduate medical education (UGME) should prepare medical students to manage this chronic disease. It is currently unknown how the management of patients living with obesity is taught within UGME curricula in Canada. This study (1) examined the knowledge and self-reported competence of final-year medical students in managing patients living with obesity, and (2) explored how this topic is taught within UGME curricula in Canada. Methods We distributed two online surveys: one to final-year medical students, and another to UGME deans at 9 English-speaking medical schools in Canada. The medical student survey assessed students’ knowledge and self-reported competence in managing patients living with obesity. The dean’s survey assessed how management of patients living with obesity is taught within the UGME curriculum. Results One hundred thirty-three (6.9%) and 180 (9.3%) out of 1936 eligible students completed the knowledge and self-reported competence parts of the survey, respectively. Mean knowledge score was 10.5 (2.1) out of 18. Students had greatest knowledge about etiology of obesity and goals of treatment, and poorest knowledge about physiology and maintenance of weight loss. Mean self-reported competence score was 2.5 (0.86) out of 4. Students felt most competent assessing diet for unhealthy behaviors and calculating body mass index. Five (56%) out of 9 deans completed the survey. A mean of 14.6 (5.0) curricular hours were spent on teaching management of patients living with obesity. Nutrition and bariatric surgery were most frequently covered topics, with education delivered most often via large-group sessions and clinical activities. Conclusions Canadian medical students lack adequate knowledge and feel inadequately prepared to manage patients living with obesity. Changes to UGME curricula may help address this gap in education.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.157 | 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 teacher head, 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".