Attitudes Toward Human Papillomavirus Self-Sampling in Regularly Screened Women in Edmonton, Canada: A Cross-Sectional Study
Bibliographic record
Abstract
OBJECTIVE/PURPOSE: The aim of the study was to determine the level of interest in human papillomavirus (HPV) self-sampling as a method of cervical cancer screening in a population of women affiliated with a primary care clinic. MATERIALS AND METHODS: A survey was given to women (N = 182) between the ages of 25 and 69 years attending a family medicine clinic in Edmonton, Canada. Primary outcome measures include (1) the percentage of women who feel that HPV self-sampling should be available and (2) the percentage of women who would prefer HPV self-sampling to the Pap test. Secondary outcomes include the percentage of women aware of HPV self-sampling and factors associated with a preference for HPV self-sampling using logistic regression. RESULTS: Most women (84%) were up-to-date on Pap testing, and most (85%) had had postsecondary education (either completed or in progress). The percentage of the women who moderately or strongly felt that HPV self-sampling should be available was 60%; the percentage of the women who would prefer HPV self-sampling was 24%. Only 7% of the women reported being previously aware of HPV self-sampling. The factor associated with a preference for HPV self-sampling was the Pap comfort score, with an odds ratio of 1.51 (95% CI = 1.05-2.16, p = .026). CONCLUSIONS: In this population of well-educated women who were mostly up-to-date on cervical screening, there was a clear interest to have the option of HPV self-sampling. It is important for cancer screening programs to take this into account, given that women are the ultimate beneficiaries of these 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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".