Knowledge and utilization of screening for cervical cancer among female in Ethiopia: a systemic review and meta-analysis
Bibliographic record
Abstract
Objective: The aim of this systemic review and meta-analysis was to verify that whether knowledge about screening for cervical cancer related with usage of screening for cervical cancer among female in Ethiopia. Previous studies on knowledge about screening for cervical cancer and usage of screening for cervical cancer indicated different findings. We include 12 studies in different regions of Ethiopia. We have done this study focusing on female’s usage of screening for cervical cancer Materials and Methods: Electronic databases were searched from 2014 to 2019.on reference manager software reporting knowledge and usage of screening for cervical cancer. Data extraction and assessment were guided by PRISMA checklist. Observational studies and studies with Newcastle-Ottawa Scale score > 50% were included in the review. The combined adjusted Odds ratios (OR)) and 95% confidence intervals were calculated using random effect model Results: Twelve observational studies involving 4704 participants, 1235 of which had usage of screening for cervical cancer, were included. The combined effect size (OR) for usage of screening for cervical cancer comparing female who know about screening for cervical cancer versus female who did not know about screening for cervical cancer was 1.16 (95%CI 0.28 to 4.77), p = 0.813, I2 = 96.23%). There was significant = heterogeneity (Q = 291.78; p = 0.000; I2 =9 6.23%%. No publication bias was observed (Egger’s test: p = 0.693, Begg’s test: p = 0.131). 47.16% (2218) women who know cervical cancer screening service 11.41% (537) engaged to use screening for cervical cancer. The proportion of utilization of screening for cervical cancer among female aged >20 years was 18.22% in 6 of the 12 studies. The overall proportion of screening usage for cervical cancer was 24.21% and 28.08% for those having knowledge of screening for cervical cancer and not having knowledge screening for cervical cancer, respectively. Conclusions: Knowledge of screening for cervical cancer is not associated with usage of screening for cervical cancer. The association between age and usage of screening for cervical cancer should be explored further.
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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 | 0.020 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.041 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".