Understanding the Acceptability and Uptake of HPV Self-Sampling Amongst Women Under- or Never-Screened for Cervical Cancer in Toronto (Ontario, Canada): An Intervention Study Protocol
Bibliographic record
Abstract
Cervical cancer remains a global public health concern, even though scientific advancements have made the disease almost entirely preventable. With the link between human papillomavirus (HPV) and cervical cancer, and the subsequent improvement in screening technology, there is potential to improve access and coverage of cervical screening with the introduction of HPV self-sampling. In Ontario, Canada, a province with a cytology-based screening program (i.e., Pap test), women who identify as South Asian, West Asian, Middle Eastern and North African have some of the lowest rates of screening, and research suggests they have a higher burden of cervical cancer. In this study, we will use both quantitative and qualitative methods to understand the acceptability and uptake of a take-home HPV self-sampling kit. Working with community champions-people with pre-existing connections with local groups-we will recruit women from these groups who are under- or never-screened for cervical cancer. Women will self-select whether they are in the group that tries HPV self-sampling or in the group that does not. We will aim for 100 women in each group. All participants will provide feedback on the feasibility, acceptability and preferences for cervical screening through a survey and phone follow-up. Women who self-select the HPV self-sampling group, will be followed up to find out if they followed through with self-sampling and to understand their experience using the device. Women who do not want to try self-sampling will be followed up to see if they went on to get a Pap test. The qualitative phase of this study consists of five focus groups with participants and semi-structured interviews with key informants in the community.
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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 | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".