Breast and Cervical Cancer Screening Among Women in Jordan: Findings from the Behavioural Risk Factor Surveillance System - 2007
Bibliographic record
Abstract
Introduction: Breast cancer is the most common cancer among women in Jordan.Age standardized incidence rate for cervical cancer has been estimated at 3.6 per 100,000 women.This report presents the results of breast and cervical cancer screening practicesamong a nationally representative sample of Jordanian women aged 35 years or above.Method: We used data from the third Jordan Behavioural Risk Factor Surveillance System (2007) among a nationally representative sample of Jordanian women aged 35 years (n=1,157).Logistic regression was used to examine the associations between each of breast and cervical cancer screening practices and selected socio-demographic characteristics.Results: Only 12.4% of women aged 35 years or older reported ever having a mammography.One fifth reported ever having a clinical breast examination at least once in their life time.Over one quarter (27.1%) of the women reported that they perform self-breast examination on monthly basis, and 41.7% reported ever having performed a self-breast examination.Among ever-married women aged 35 years or more, Pap smear test was performed by 27.8% during their life.The reported low practices have shown substantial differences across regions, age groups, level of education, family income, marital status, and source of medical services. Conclusion:The low reported cancer screening activities among women in Jordan calls for action.Data on current screening practices is a primary step to provide health professionals, and policy-makers with the information necessary to identify priorities and to facilitate cancer control, policy development, and planning.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".