Screening mammography participation and invitational strategy: the Quebec Breast Cancer Screening Program, 1998-2000.
Bibliographic record
Abstract
In the Quebec Breast Cancer Screening Program, a personalized letter signed by a regional program physician is sent to every woman in the province 50 to 69 years of age, inviting her to have a screening mammogram. A reminder letter is also frequently sent. The aim of this study was to evaluate the influence of this screening invitational strategy on rates of participation. The population studied was comprised of 684,028 women in Quebec aged 50-69. The baseline (expected) monthly mammography screening rate was estimated from the rate of screening mammograms recorded between the date a woman became eligible for screening and the mailing date of her personalized invitational letter; the observed monthly mammography screening rate was calculated after the mailing of the letter. Compared to baseline (expected) screening rates, observed rates were substantially increased (p<.05). The ratios of observed to expected rates were respectively 3.05 and 2.23 in the second and fourth months, respectively, after the letter mailing, coinciding with the mailing of the initial and reminder letters. In the twelve months after the mailing, the ratio of observed to expected rates was 1.68 (95% CI: 1.67-1.69). Twelve months following the mailing, 30 percent of the women who were letter recipients had undergone a screening mammography, compared to an expected cumulative probability of 20 percent for women not receiving a letter. The strength of this effect was similar to one seen in randomised controlled trials.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".