Breast cancer screening among Arabic women living in the State of Qatar: Awareness, knowledge, and participation in screening activities
Bibliographic record
Abstract
Abstract Background: Breast cancer is the most common cancer among women in the State of Qatar, and the incidence rate is rising. Previous findings indicate women in Qatar are often diagnosed with breast cancer at advanced stages and their participation rates in screening activities are low. Purpose: To investigate within the State of Qatar Arabic women’s knowledge regarding breast cancer and breast cancer screening (BCS) methods and their participation rates in BCS. This paper reports on the results of a cross-sectional survey. Methods: A quantitative, cross-sectional interview survey was conducted with 1,063 Arabic women (Qatari citizens and non-Qatari Arabic-speaking residents), 35 years of age or older, from March 2011 to July 2011. Results: Of the 1,063 women interviewed (87.5% response rate), 90.7% were aware of breast cancer; 7.6% were assessed with having basic knowledge of BCS, 28.9% were aware of breast self-examination (BSE), 41.8% were aware of clinical breast exams (CBE), and 26.9% were aware of mammograms. Of the women interviewed, 13.8% performed BSE monthly, 31.3% had a CBE once a year or once every two years, and 26.9% of women 40 years of age or older had a mammogram once a year or once every two years. Participation rates in BCS activities were significantly related to awareness and knowledge of BCS, education levels, and receiving information about breast cancer, self-examination or mammography from any of a variety of sources, particularly physicians. Conclusions: Study results demonstrate that despite the existent breast cancer screening recommendations, less than one-third of Arabic women living in Qatar participate in BCS activities. Public health campaigns encouraging more proactive roles for health care professionals regarding awareness and knowledge of breast cancer, BCS, and the benefits of early detection of breast cancer will help increase screening rates and reduce mortality rates among Arabic women living in the State of Qatar.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".