Exploring the acceptability of human papillomavirus self-sampling among Muslim immigrant women
Bibliographic record
Abstract
BACKGROUND: With appropriate screening (ie, the Papanicolaou [Pap] test), cervical cancer is highly preventable, and high-income countries, including Canada, have observed significant decreases in cervical cancer mortality. However, certain subgroups, including immigrants from countries with large Muslim populations, experience disparities in cervical cancer screening. Little is known about the acceptability of human papillomavirus (HPV) self-sampling as a screening strategy among Muslim immigrant women in Canada. This study assessed cervical cancer screening practices, knowledge and attitudes, and acceptability of HPV self-sampling among Muslim immigrant women. METHODS: A convenience sample of 30 women was recruited over a 3-month period (June-August 2015) in the Greater Toronto Area. All women were between 21 and 69 years old, foreign-born, and self-identified as Muslim, and had good knowledge of English. Data were collected through a self-completed questionnaire. RESULTS: More than half of the participants falsely indicated that Pap tests may cause cervical infection, and 46.7% indicated that the test is an intrusion on privacy. The majority of women reported that they would be willing to try HPV self-sampling, and more than half would prefer this method to provider-administered sampling methods. Barriers to self-sampling included confidence in the ability to perform the test and perceived cost, and facilitators included convenience and privacy being preserved. CONCLUSION: The results demonstrate that HPV self-sampling may provide a favorable alternative model of care to the traditional provider-administered Pap testing. These findings add important information to the literature related to promoting cancer screening among women who are under or never screened for cervical cancer.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".