Patterns and predictors of adherence to colorectal cancer screening recommendations in Alberta’s Tomorrow Project participants stratified by risk
Bibliographic record
Abstract
BACKGROUND: Colorectal cancer (CRC) screening is an important modifiable behaviour for cancer control. Regular screening, following recommendations for the type, timing and frequency based on personal CRC risk, contributes to earlier detection and increases likelihood of successful treatment. METHODS: To determine adherence to screening recommendations in a large provincial cohort of adults, participants in Alberta's Tomorrow Project (n = 9641) were stratified based on increasing level of CRC risk: age (Age-only), family history of CRC (FamilyHx), personal history of bowel conditions (PersonalHx), or both (Family/PersonalHx) using self-reported information from questionnaires. Provincial and national guidelines for timing and frequency of screening tests were used to determine if participants were up-to-date based on their CRC risk. Screening status was compared between enrollment (2000-2006) and follow-up (2008) to determine screening pattern over time. RESULTS: The majority of participants (77%) fell into the average risk Age-only strata. Only a third of this strata were up-to-date for screening at baseline, but the proportion increased across the higher risk strata, with > 90% of the highest risk Family/PersonalHx strata up-to-date at baseline. There was also a lower proportion (< 25%) of the Age-only group who were regular screeners over time compared to the higher risk strata, though age, higher income and uptake of other screening tests (e.g. mammography) were associated with a greater likelihood of regular screening in multinomial logistic regression. CONCLUSIONS: The low (< 50%) adherence to regular CRC screening in average and moderate risk strata highlights the need to further explore barriers to uptake of screening across different risk profiles.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".