Voices from the Margins: Barriers and Facilitators to HPV Self-Sampling Among Structurally Marginalized People with a Cervix in the Greater Toronto Area and Ontario
Bibliographic record
Abstract
Sex workers and formerly incarcerated people with a cervix face significant structural, interpersonal, and emotional barriers to cervical cancer screening, despite being at elevated risk for HPV infection. HPV self-sampling (HPV-SS) is a validated, user-directed method that has the potential to address these barriers, yet it remains excluded from Ontario's organized screening program. This qualitative study explored the lived experiences of structurally marginalized individuals with a cervix who were offered HPV-SS as part of a mixed-methods pilot in the Greater Toronto Area. Five virtual focus groups were conducted with 34 participants, including both those who used the HPV-SS kit and those who declined it. Using inductive thematic analysis, we identified barriers to traditional screening including fear, stigma, mistrust of healthcare providers, logistical constraints, and a lack of accessible information. HPV-SS was widely described as more acceptable, empowering, and emotionally manageable, offering participants autonomy, privacy, and control over their care. Concerns included swab design, uncertainty about correct use, and unclear follow-up after positive results. Participants offered concrete, community-informed recommendations to improve HPV-SS implementation, including opt-in distribution models, gender-affirming language, and trauma-informed educational materials. The findings highlight the urgent need to integrate HPV-SS into organized screening programs to advance equitable access to cervical cancer prevention for marginalized populations.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".