Concurrent cancer screening participation and associated factors among Canadian women: Insights from a cross-sectional study
Bibliographic record
Abstract
Objectives Colorectal, breast, and cervical cancers are leading causes of morbidity and mortality among Canadian women. While organized screening programs aim to reduce this burden, participation rates remain suboptimal, particularly for colorectal cancer screening. This study examined factors associated with colorectal cancer screening uptake among women participating in breast and cervical cancer screening ('screen-aware” women), investigated patterns of concurrent participation across all three programs, and identified associated factors. Methods Cross-sectional data from the 2017 Canadian Community Health Survey were analyzed for women aged 50–69 eligible for breast cancer (mammography), cervical cancer (Pap smear), and colorectal cancer (fecal and/or endoscopy tests) screening ( n = 10,426). Multivariable logistic regression evaluated factors associated with colorectal cancer screening among “screen-aware” women. Multinomial logistic regression assessed factors related to full (all three), partial (any two), single, or non-participation across screening programs, using “no screening” as the reference. Results Although the majority of women (87%) participated in at least one screening program, only 27% reported full participation. Colorectal cancer screening (53.7%) lagged behind breast and cervical cancer screening (∼64%). Among “screen-aware” women, older age (adjusted odds ratio 1.50, 95% confidence interval 1.31–1.71), higher income, self-rated health as “great” (adjusted odds ratio 1.31, 95% confidence interval 1.05–1.63), and having a regular healthcare provider (adjusted odds ratio 3.29, 95% confidence interval 2.45–4.40) were associated with higher colorectal cancer screening participation. Having multiple chronic conditions reduced colorectal cancer screening likelihood (adjusted odds ratio 0.72, 95% confidence interval 0.55–0.94). Higher income, self-rated health, having a regular healthcare provider, and physical activity increased the odds of full screening participation, while smoking and Asian identity reduced the odds. Conclusions Colorectal cancer screening uptake remains low among Canadian women, even those participating in other cancer screenings. Socioeconomic, health-related, and systemic factors influence concurrent screening participation. Tailored interventions addressing identified barriers and promoting equitable access to screening are crucial for improving cancer prevention efforts.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".