Sociodemographic factors associated with cervical cancer screening and follow-up of abnormal results.
Bibliographic record
Abstract
OBJECTIVE: To determine the sociodemographic factors associated with cervical cancer screening and follow-up of abnormal results. DESIGN: Population cohort study. SETTING: Ontario. PARTICIPANTS: Women between the ages of 18 and 70 years who were eligible for Papanicolaou testing. MAIN OUTCOME MEASURES: Rates of cervical cancer screening and follow-up of abnormal and inadequate Pap test results, and associated sociodemographic factors such as age, neighbourhood income level, and health region. Multivariate logistic regression was used to identify independent factors associated with screening and follow-up. RESULTS: Of the 3.7 million women eligible for screening, 69% had had Pap tests in the past 3 years. These rates varied by age, income, and region (P < .001). Women residing in the lowest-income neighbourhoods were half as likely to be screened (odds ratio 0.56, 95% CI 0.55 to 0.56). Only 44% of those whose Pap test results revealed atypical squamous cells of uncertain significance or low-grade squamous intraepithelial lesions had repeat Pap tests or colposcopy within 6 months, and this varied by age, income, and region (P < .001). Among women with unsatisfactory Pap test results, only 35% were retested within 4 months, and this varied by age (P < .001). CONCLUSION: Despite universal health coverage, cervical cancer screening rates are suboptimal among low-income women at greatest risk. Follow-up among women with inadequate or abnormal test results is often poor. Novel models of cervical cancer screening are needed to address these inadequacies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".