Exercise Medicine In Residency Training
Bibliographic record
Abstract
Physical activity (PA) is a key intervention for chronic disease, yet few physicians prescribe exercise. Determining factors associated with physicians who have the greatest conviction to prescribe exercise in their practice may help inform future training. PURPOSE: To determine residents’: (1) perceived importance of exercise prescription, (2) personal PA levels, (3) attitudes/beliefs about PA (4) exercise counselling and prescription practices, (5) knowledge of the PA Guidelines, (6) competence in exercise prescription and (7) perspectives of training in exercise medicine. METHODS: 396 University of British Columbia family medicine residents were eligible to complete the 49-item cross-sectional survey. All variables were evaluated on a 7-point Likert scale, and assessed in relation to the importance of exercise prescription, with significance set conservatively to p=0.01. RESULTS: The response rate was 80.6% (319/396). Exercise prescription was important to residents (95.6%), with 37.5% strongly agreeing (termed “prescribers”). Both groups reported strong beliefs of the importance of PA in health (97.3% vs. 90.0%, p<0.001), physician responsibility advising patients in PA (96.3% vs. 90.7%, p<0.001), with prescribers higher across each (of 5) variable assessed. The level of exercise counseling (57.8% vs. 38.3%, p=0.001), prescription (36.7% vs. 18.0%, p=0.001) and self-reported competence prescribing exercise (48.5% vs. 56.6%, p<0.001) was greater for prescribers. Both groups had low knowledge of the PA guidelines (42.5%, p =1.0). Neither group is sufficiently PA, with few meeting the guidelines (51.9% aerobic, 24.5% strength). Both groups valued their exercise (94.2% vs. 87.5%, p<0.001), perceived lower control over it (68.5% vs. 67.3%, p=0.72) and desired program support in being active (96.3% vs. 90.7%, p<0.001). Few Residents’ perceived their training in exercise medicine as adequate (24.6% vs. 15.3% p=0.25) and both groups desired additional training in exercise prescription (94.2% vs. 89.1% p=0.004). CONCLUSIONS: Current training is not preparing physicians to prescribe exercise, nor to be suitable PA role models for their patients. Program reform should include curriculum in exercise medicine, support residents’ personal exercise and foster a culture of physical activity.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.095 | 0.017 |
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".