Sociodemographic Inequalities in Sexual Activity and Cervical Cancer Screening: Implications for the Success of Human Papillomavirus Vaccination
Bibliographic record
Abstract
BACKGROUND: Papanicolaou smear screening has significantly reduced cervical cancer morbidity and mortality. However, inequalities still persist across different socioeconomic status (SES) groups. These inequalities have been associated with differential participation in screening. However, even with equal participation to screening, some women may still have greater risk of cervical cancer because of sexual behavior. We aim to identify the sociodemographic characteristics of women who reported greater sexual activity and/or screening underuse. METHODS: We used data from (i) the Canadian Community Health Survey-2005, a population-based survey of 130,000 Canadians, and (ii) a multicenter study including 952 women screened for cervical cancer. RESULTS: Aboriginals and women with lower SES reported greater sexual activity and lower screening participation, which may produce synergetic effects toward higher cervical cancer risk. Women who did not complete high school and aboriginals were, respectively, 3.6 and 2.5 times more likely to report sexual debut before 15 years old compared with women with university degree and Caucasians. Women who did not complete high school were 2.2 times more likely to have never been screened compared with women with university degree. East and South Asian women were, respectively, 4.3 and 3.1 times more likely to have never been screened than Canadian-born women but reported lower levels of sexual activity and were adherent to screening guidelines when screened at least once. CONCLUSIONS: The success of human papillomavirus vaccination at reducing cervical cancer and inequalities will depend on achieving high coverage among high-risk subpopulations. IMPACT: These groups must be monitored closely, and if need be, targeted for additional interventions.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".