Breast cancer screening practices for women aged 35 to 49 and 70 and older.
Bibliographic record
Abstract
OBJECTIVE: To describe physician practices with regard to opportunistic screening for breast cancer in women aged 35 to 49 years and 70 years of age and older, and to identify the determinants associated with the practice of prescribing screening mammography. DESIGN: Postal survey. SETTING: Quebec. PARTICIPANTS: Simple random sample of 1400 general practitioners practising in Quebec in 2009. MAIN OUTCOME MEASURES: Five cancer screening practices among 4 types of female clientele and the factors influencing physicians in their practice of prescribing screening mammography. RESULTS: The response rate was 36%. For women aged 35 to 49 years, more than 80% of physicians reported using practices judged adequate, except for the teaching of breast self-examination and referrals to genetic counseling (60% and 54%). For women 70 years of age and older with good life expectancy, only 50% of general practitioners prescribed screening mammography. For the 70 years of age and older age group without good life expectancy, for whom screening is not indicated, nearly half of physicians continued to do the clinical breast examination and more than one-third reviewed family history. The main determinants for the practice of prescribing mammography are a favourable attitude to screening, screening skills, peer support, belief in the efficacy of mammography, and sufficient knowledge of the issue and of recommendations. CONCLUSION: Improvements are needed in the practice of teaching breast self-examination to women aged 35 to 49 years and referring them to genetic counseling, as well as in prescribing mammography for women 70 years of age and older who are in good health. Public health actions to improve these practices should focus on physician attitudes and skills and on communicating clearer recommendations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".