Assessing Canadian women's preferences for cervical cancer screening: A brief report
Bibliographic record
Abstract
Human papillomavirus (HPV) testing is recommended for primary screening for cervical cancer by several health authorities. Several countries that have implemented HPV testing programs have encountered resistance against extended screening intervals and older age of initiation. As Canada prepares to implement HPV testing programs, it is important to understand women's preferences toward cervical cancer screening to ensure a smooth transition. The objective of this study was to assess Canadian women's current preferences toward cervical cancer screening. Using a web-based survey, we recruited underscreened ( > 3 years since last Pap test) and adequately screened (< 3 years since last Pap test) Canadian women aged 21–70 who were biologically female and had a cervix. We used Best-Worst Scaling (BWS) methodology to collect data on women's preferences for different screening methods, screening intervals, and ages of initiation. We used conditional logistic regression to estimate preferences in both subgroups. In both subgroups, women preferred screening every three years compared to every five or ten years, and initiating screening at age 21 compared to age 25 or 30. Adequately screened women (n = 503) most preferred co-testing, while underscreened women (n = 524) preferred both co-testing and HPV self-sampling over Pap testing. Regardless of screening status, women preferred shorter screening intervals, an earlier age of initiation, and co-testing. Adequate communication from public health authorities is needed to explain the extended screening intervals and age of initiation to prevent resistance against these changes to cervical 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".