Strategies to Reach Marginalized Women for Cervical Cancer Screening: A Qualitative Study of Stakeholder Perspectives
Bibliographic record
Abstract
Background: Self-sampling for human papillomavirus (hpv) has the potential to reach marginalized populations that are underserved for cervical cancer screening. However, before implementing an alternative screening strategy such as self-sampling for under- and never-screened women, the key processes, facilitators, and barriers to reform need to be understood. Methods: A descriptive qualitative study was conducted that involved semi-structured interviews with Canadian and international cancer screening health care providers and policy-makers. Respondents were purposively selected from a list of thirty stakeholders generated through an environmental scan. The interviews were transcribed verbatim and analyzed using directed content analysis. Results: Nineteen stakeholders participated in the interviews. Most respondents thought that self-sampling was an appropriate cervical screening alternative for hard-to-reach populations, as it addressed barriers to cervical screening related to various social determinants of health. All respondents emphasized that transitioning to hpv primary screening would catalyze a policy shift towards self-sampling. Clinician respondents were less enthusiastic about self-sampling strategies since that discouraged women's appointments with primary care providers, because cervical screening offered an opportunity to discuss other preventive health topics. There also was little consensus between respondents on whether the state of evidence was satisfactory to integrate a self-sampling option into policy, or whether more Canadian research was needed. Conclusion: Canadian cervical cancer screening stakeholders should collaborate to identify the knowledge gaps that researchers should address and leverage the existing literature to implement tailored, patient-centred alternative cervical screening strategies. The transition to hpv primary screening would be a key first step in the broad implementation of hpv self-sampling in Canada.
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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 | 0.017 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".