Delivery of preventive care
Bibliographic record
Abstract
Objective To determine family physicians’ practice of, knowledge about, and attitudes toward delivering preventive care during periodic health examinations (PHEs). Design A stratified sample of 5013 members of the College of Family Physicians of Canada were randomly selected to receive a questionnaire by mail. Descriptive analysis was performed on a national data set of 1010 respondents. Setting Canada. Participants A sample of family physicians from each Canadian province. Main outcome measures Physicians were asked questions about whether they addressed aspects of preventive care, such as tobacco smoking, nutrition, physical activity, alcohol intake, and sun exposure with patients during PHEs. The questions were designed to gauge attitudes and identify barriers to the provision of preventive care. Results Most respondents (87% to 89%) indicated that they were comfortable counseling their patients about issues such as nutrition, physical activity, and alcohol consumption; however, many of these respondents did not refer their patients to specialists or provide them with additional resources to educate patients about the health risks of their conditions. While tobacco smoking risks and cessation were addressed by most family physicians (79%) during PHEs, other topics, such as sun exposure, were often overlooked. Conclusion The results of this survey indicate that while many family physicians follow the evidence-based guidelines for preventive care, current levels of preventive care in the primary care setting are below national standards. It is critical that Canadians receive optimal preventive care to improve the outlook of the chronic disease burden on the health care system.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".