The relationship between rural residence and cervical cancer screening in three sub-Saharan countries with different national screening policies
Bibliographic record
Abstract
PURPOSE: To compare cervical cancer screening prevalence between urban and rural women aged 30-49 years in three sub-Saharan African countries chosen by their country-specific screening strategy (Burkina Faso, which has a systematic population-based cervical cancer screening programme in place; Tanzania, where opportunistic screening options only are implemented; and Ghana, which has implemented neither one). METHODS: We used the most recent Demographic and Health Surveys data from Burkina Faso, Ghana and Tanzania. We restricted our analysis to women aged 30-49 eligible for cervical cancer screening and categorised them by their place of residence as urban or rural. We calculated screening proportions using country-specific survey weights to estimate the absolute prevalence difference in cervical cancer screening between urban/rural residents. RESULTS: Rural participants represented 69.5% in Burkina Faso, 64.6% in Tanzania and 42.8% in Ghana. Burkina Faso women reported higher cervical cancer screening prevalence at 19.9%, and Ghana participants reported the lowest at 7.4%. Compared with urban participants, rural women screened less across countries, with an absolute prevalence difference in screening wider in Tanzania at 13.1% (95% CI 10.6% to 15.7%), followed by Burkina Faso at 11.1% (95% CI 7.7% to 14.6%) and narrower in Ghana at 5.9% (95% CI 4.1% to 7.7%). CONCLUSION: We found a consistently low screening uptake and a screening prevalence gap disfavouring rural women from these three sub-Saharan African countries, with the narrowest urban/rural gap in Ghana and the widest in Tanzania, which has a large opportunistic cervical cancer screening programme. Our findings offer no indication of a potential benefit of having a systematic screening programme as a tool that can mitigate the screening gap between urban and rural populations. Further screening uptake studies, including more countries, are needed on this topic, which should account for the existing country-specific non-screening related factors in the healthcare system that may influence cervical cancer screening uptake.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".