Are Canadian Women Prepared for the Transition to Primary HPV Testing in Cervical Screening? A National Survey of Knowledge, Attitudes, and Beliefs
Bibliographic record
Abstract
As Canadian provinces and territories prepare to transition to HPV-based primary screening for cervical cancer, failure to identify and address potential barriers to screening could hinder program implementation. We examined screening-eligible Canadians’ attitudes towards and knowledge of cervical screening. A nationally representative sample of screening-eligible Canadians (N = 3724) completed a web-based survey in the summer of 2022. Oversampling ensured that half of the sample were underscreened for cervical cancer (>3 years since previous screening or never screened). The participants completed validated scales of cervical cancer, HPV, and HPV test knowledge and HPV test and self-sampling attitudes and beliefs. Between-group differences (underscreened vs. adequately screened) were calculated for scales and items using independent sample t-tests or chi-square tests. The underscreened participants (n = 1871) demonstrated significantly lower knowledge of cervical cancer, HPV, and the HPV test. The adequately screened participants (n = 1853) scored higher on the Confidence and Worries subscales of the HPV Test Attitudes and Beliefs Scale. The underscreened participants scored higher on the Personal Barriers and Social Norms subscales. The underscreened participants also endorsed greater Autonomy conferred by self-sampling. Our findings suggest important differential patterns of knowledge, attitudes, and beliefs between the underscreened and adequately screened Canadians. These findings highlight the need to develop targeted communication strategies and promote patient-centered, tailored approaches in cervical screening programs.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 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".