Self-Reported Study Analyzing Physicians’ Personal Compliance with Health Prevention Guidelines in a Medium-Sized Canadian Community
Bibliographic record
Abstract
There have only been limited studies that have assessed the attitude of Canadian physicians toward their own physical health. The aim of our study was to explore the self-reported health maintenance behavior and the predictors of health practices among physicians in a small-medium sized Canadian community. We used a descriptive mailed in self-report survey to contact all 649 physicians registered with the Essex County Medical Society, with a 36% response rate. Our results showed that 81% of physicians in Windsor-Essex County were satisfied with how well they care for themselves, despite reporting low levels of physical activity and a lower percentage of respondents having family physicians than the general population. Five independent factors were identified with physician self-perceived health satisfaction: Physician age of 45 to 54 (95% CI 0.17-0.92; OR 0.39), graduating from Canadian medical schools (95% CI 0.15 to 0.80; OR 0.35), having more than one co-morbidity (95% CI 0.13-0.72; OR 0.31), physicians who had a regular family doctor (95% CI 1.12-5.52; OR 2.43), and engagement in regular moderate weekly exercise (95% CI 1.05-4.94; OR 2.28). We also contrasted the preventive health screening markers of our study to compliance rates of the general population as well as the national physician study. Our results showed that screening rates among our study physician group differed markedly from the general population. For colorectal and breast cancers, physicians in our study reported screening rates of 77.8% and 37.3% respectively, compared with the general population, who's screening rates are 32.3% and 72.5%. Future studies exploring specific targeted health promotion interventions that could address these factors may be warranted in order to further improve Canadian physician health, and ultimately improve their ability to take care of their patients.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".