Reach and effectiveness of an HPV self-sampling intervention for cervical screening amongst under- or never-screened women in Toronto, Ontario Canada
Bibliographic record
Abstract
BACKGROUND: Cervical cancer is almost entirely preventable with appropriate and timely screening. In Ontario, Canada, South Asian, Middle Eastern and North African women have some of the lowest rates of screening and a suggested higher burden of cervical cancer. With increasing international evidence and adoption of HPV testing, many screening programs are making the move away from Pap tests and towards HPV testing with the option of HPV self-sampling seeming promising for under- or never-screened (UNS) women. Our study aimed to understand the uptake and acceptability of an HPV self-sampling intervention amongst these disproportionately UNS women in Peel region and surrounding areas in Ontario. METHODS: A community -based mixed methods approach guided by the RE-AIM framework was used to recruit approximately 100 UNS racialized immigrant women aged 30-69, during the period of June 2018 to December 2019. The main recruitment strategy included community champions (i.e. trusted female members of communities) to engage people in our selected areas in Peel Region. Participants completed a study questionnaire about their knowledge, attitudes and practices around cervical cancer screening, self-selected whether to use the HPV self-sampling device and completed follow-up questions either about their experience with self-sampling or going to get a Pap test. RESULTS: In total, 108 women participated in the study, with 69 opting to do self-sampling and 39 not. The majority of women followed through and used the device (n = 61) and found it 'user friendly.' The experience of some participants suggests that clearer instructions and/or more support once at home is needed. Survey and follow-up data suggest that privacy and comfort are common barriers for UNS women, and that self-sampling begins to address these concerns. Across both groups addressing misinformation and misconceptions is needed to convince some UNS women to be screened. Family, friends and peers also seemed to play a role in the decision-making process. CONCLUSIONS: HPV self-sampling is viewed as an acceptable alternative to a Pap test for cervical screening, by some but not all UNS women. This method begins to address some of the barriers that often prevent women from being screened and is already being offered in some jurisdictions as an alternative to clinical cervical cancer screening.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".