Factors that facilitate or impede colorectal cancer screening in women from Ontario: A representative regional study
Bibliographic record
Abstract
Purpose. To investigate the prevalence and factors associated with women's use of colorectal cancer (CRC) screening. Analyses were guided by Andersen's Behavioral Model of predisposing, enabling and need factors. Methods. Using the Ontario sub-sample of the 2005 Canadian Community Health Survey, women aged 50-74 who had never screened for CRC (n=3,676) were compared to women who had screened (n=2,105). Chi-square tests and logistic regression analyses were used. Results. Approximately one-third (38.1%) of women had used CRC screening. Predisposing factors (older age, higher education, not working, history of cancer, use of other screening tests), enabling factors (urban location, having a doctor, 5+ doctor visits annually), and, need factors (non-smoking, normal weight, higher activity level) were associated with higher odds of screening. Conclusions. Healthier respondents with lower risk of CRC were more likely to screen, indicating inequitable access to screening. Findings will improve targeting of CRC screening campaigns.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".