Factors associated with open practices: results from the Canadian National Family Physician Survey.
Bibliographic record
Abstract
OBJECTIVE: Closed and conditionally closed practices appear to be increasing in many parts of Canada as reflected in the fact that more and more patients report difficulties finding family physicians who accept new patients. But the extent of, nature of, and factors related to open, closed, and conditionally closed practices are still largely unknown. DESIGN: This study used data from the 2001 National Family Physician Workforce Survey for secondary analysis. Chi-square tests and logistic regression were used to examine factors related to FPs' decisions to keep their practices open or to close them. SETTING: Private offices, clinics, community health centres, and academic family medicine practice units in Canada. PARTICIPANTS: Of 10,325 FPs surveyed, 2360 respondents who practised in emergency departments, hospitals, nursing homes, homes for the aged, walk-in clinics, and more than one setting were excluded. Overall response rate was 51.2%. MAIN OUTCOME MEASURES: Practice status (open, conditionally closed, and closed), restrictions placed on conditionally closed practices, and factors associated with open practices. RESULTS: The odds of having an open practice increased if respondents were male, younger than 35, working fewer hours at the time, or working in a group practice that included other types of physicians. Family physicians in rural and remote areas were much less likely than those in urban centres to close their practices. Conversely, FPs were more likely to close their practices when they perceived their communities to have good emergency department services and when other FPs in the community also had closed their practices. CONCLUSION: Demographic and practice characteristics of physicians have an effect on whether practices are open, conditionally closed, or completely closed. But the broader practice environment, determined by such factors as geographic location and medical services available in the community, is equally important.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| 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".