Women’s intentions to self-collect samples for human papillomavirus testing in an organized cervical cancer screening program
Bibliographic record
Abstract
BACKGROUND: Mounting evidence affirms HPV testing as an effective cervical cancer screening tool, and many organized screening programs are considering adopting it as primary testing. HPV self-collection has comparable sensitivity to clinician collected specimens and is considered a feasible option in hard-to-reach women. We explored women's intentions to HPV self-collect for cervical cancer screening from a cohort participating in a Canadian randomized controlled cervical cancer screening trial. METHODS: Women aged 25-65 were invited to complete an online survey assessing intentions to be screened with HPV testing instead of the Pap smear. The survey was based in the Theory of Planned Behaviour and questions were included to assess women's intentions to self-collect for HPV. Demographic characteristics of women who intended to self-collect were compared with those who did not. Demographic and scale variables achieving a p-value <0.1 in the univariate and bivariate analyses were included in the stepwise logistic regression model. The final model was created to predict factors associated with women's intentions to self-collect an HPV specimen for cervical cancer. Odds ratios were calculated with 95% confidence intervals to identify variables associated with a woman's intention to self-collect for cervical cancer screening. RESULTS: The overall survey response rate was 63.8% (981/1538) with 447 (45.6%) reporting they intended to self-collect, versus 534 (54.4%) reporting they did not. In the univariate analysis, women with more than high school education were more likely to self-collect. Women who intended to receive HPV testing versus the Pap smear were 1.94 times as likely to be in favour of self-collection and those who intended to self-collect had significantly higher attitudinal scores towards HPV self-collection. The adjusted odds ratio and 95% confidence interval from the multivariate analysis demonstrated attitude towards self-collection was the only significant variable predicting a woman's intention to self-collect (OR 1.25; 95% CI: 1.22, 1.29). CONCLUSIONS: The primary predictor of a woman's intention to HPV self-collect for cervical cancer screening was her attitude towards the procedure. From a program planning perspective, these results indicate that education and awareness may be significant contributing factors to improving acceptance of self-collection and subsequently, improving screening attendance rates.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".