Women’s attitudes towards a human papillomavirus-based cervical cancer screening strategy: a systematic review
Bibliographic record
Abstract
OBJECTIVE: To provide insights into women's attitudes towards a human papillomavirus (HPV)-based cervical cancer screening strategy. DATA SOURCES: Medline, Web of Science Core Collection, Cochrane Library, PsycINFO, CINAHL and ClinicalTrials.gov were systematically searched for published and ongoing studies (last search conducted in August 2021). METHODS OF STUDY SELECTION: The search identified 3162 references. Qualitative and quantitative studies dealing with women's attitudes towards, and acceptance of, an HPV-based cervical cancer screening strategy in Western healthcare systems were included. For data analysis, thematic analysis was used and synthesised findings were presented descriptively. TABULATION, INTEGRATION, AND RESULTS: Twelve studies (including 9928 women) from USA, Canada, UK and Australia met the inclusion criteria. Women's attitudes towards HPV-based screening strategies were mainly affected by the understanding of (i) the personal risk of an HPV infection, (ii) the implication of a positive finding and (iii) the overall screening purpose. Women who considered their personal risk of HPV to be low and women who feared negative implications of a positive finding were more likely to express negative attitudes, whereas positive attitudes were particularly expressed by women understanding the screening purpose. Overall acceptance of an HPV-based screening strategy ranged between 13% and 84%. CONCLUSION: This systematic review provides insights into the attitudes towards HPV-based cervical cancer screening and its acceptability based on studies conducted with women from USA, Canada, UK and Australia. This knowledge is essential for the development of education and information strategies to support the implementation of HPV-based cervical cancer screening. SYSTEMATIC REVIEW REGISTRATION: PROSPERO (CRD42020178957).
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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 | 0.012 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".