Frequency of colorectal cancer screening and the impact of family physicians on screening behaviour
Bibliographic record
Abstract
BACKGROUND: Mortality associated with colorectal cancer can be reduced by early detection. However, the participation of eligible people in colorectal cancer screening is thought to be inadequate. We examined the frequency of colorectal cancer screening in 4 Canadian provinces and the influence of patient contact with a family physician on the uptake of cancer screening. METHODS: We performed analyses using data from the 2003 Canadian Community Health Survey. The study population included 12,776 people at average risk for colon cancer living in British Columbia, Saskatchewan, Ontario, and Newfoundland and Labrador who were aged 50 years or older and who were eligible for colorectal cancer screening. We assessed the proportion of respondents who reported having previous colorectal cancer screening tests and the degree of contact with a family physician. RESULTS: The provincial response rates for the survey were 78.5%-87.0%. The proportion of respondents who reported any history of colorectal cancer screening was 23.5%. This value dropped to 17.6% when only up-to-date screening was considered (screening within the time frame recommended in guidelines). The proportion of people with up-to-date colorectal cancer screening varied significantly among provinces, but it was low in all provinces sampled. Contact with a family physician was associated with increased colorectal cancer screening. Compared with no physician contact, the odds of screening associated with 1-2 physician contacts in the 12 months before the survey was 1.97 (95% confidence interval [CI] 1.56-2.48], and the odds of screening associated with more than 4 contacts was 2.75 (95% CI 2.14-3.53). INTERPRETATION: Self-reported colorectal cancer screening falls well below acceptable levels. People with increased contact with a family physician are more likely than those without contact to report a history of up-to-date colorectal cancer screening.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".