Bibliographic record
Abstract
OBJECTIVE: To study the health and health practices of Canadian physicians, which can often influence patient health. DESIGN: Mailed survey. SETTING: Canada. PARTICIPANTS: A random sample of 8100 Canadian physicians; 7934 were found to be eligible and 3213 responded (40.5% response rate). MAIN OUTCOME MEASURES: Factors that influence health, such as consumption of fruits and vegetables, amount of exercise and alcohol consumption, smoking status, body mass idex, and participation in preventive health screening measures, as well as work-life balance and emotional stability. RESULTS: Canadian physicians are healthy. More than 90% reported being in good to excellent health, and only 5% reported that poor physical or mental health made it difficult to handle their workload more than half the time in the previous month (although a quarter had reduced work activity because of long-term health conditions). Eight percent were obese, 3% currently smoked cigarettes, and 1% typically consumed 5 drinks or more on days when they drank alcohol. Physicians averaged 4.7 hours of exercise per week and ate fruits and vegetables 4.8 times a day. Their personal screening practices were largely compliant with Canadian Task Force on Preventive Health Care recommendations. They averaged 38 hours per week on patient care and 11 hours on other professional activities. Fifty-seven percent agreed that they had a good work-life balance, and 11% disagreed with the statement "If I can, I work when I am ill." CONCLUSION: Compared with self-reports from the general Canadian population, Canadian physicians, like American physicians, seem to be healthy and to have generally healthy behaviour. There is, however, room for improvement in physicians' personal and professional well-being, and improving their personal health practices could be an efficient and beneficent way to improve the health of all Canadians.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".