Low Uptake of Colorectal Cancer Screening 3 Yr After Release of National Recommendations for Screening
Bibliographic record
Abstract
BACKGROUND: National guidelines recommending colorectal cancer (CRC) screening for average risk Canadians were released in 2001. The current study determined rates of CRC screening and predictors of screening 3 yr after the guidelines were released. METHOD: A population-based random digit dial telephone survey of 1,808 Alberta men and women aged 50-74 yr assessed awareness about, and self-reported rates of, screening. RESULTS: More average risk women than men reported a recent screening with a home fecal occult blood test (FOBT) (14.0%vs 9.8%, P= 0.013) but men had slightly higher rates of screening endoscopy in the past 5 yr (4.3%vs 1.6%, P= 0.003). Overall, only 14.3% of average risk adults (N = 1,476) were up-to-date on CRC screening. Multivariable predictors of being up-to-date on CRC screening differed for men and women although a doctor's recommendation for screening was a strong predictor for both genders (men OR 5.0, 2.9-8.3, women OR 3.8, 2.3-6.5). Screening for other cancers was also an important predictor in both men and women. CONCLUSION: Three years after the release of national guidelines, rates of screening among average risk adults aged 50-74 yr were very low. Public education programs and primary care interventions to specifically invite average risk adults for screening may be required to increase CRC screening rates.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".