Giving Voice to the Unheard: Perceptions, Practices & Beliefs About Breast Cancer and Screening Among Ethnic Minority Women From the MENA (Middle East & North Africa) Region in Edmonton, Alberta.
Bibliographic record
Abstract
Breast cancer is one of the major causes of death among women in Canada and globally. In Canada, screening has been found to be successful in decreasing morbidity and mortality (Canadian Cancer Society, 2015). Use of breast cancer screening services by immigrant women however is limited (Bowser, Mrqusee, Kousa, & Auton, 2017). Cultural values and religion often shape health decisions, and failure to recognize this diversity results in breast cancer and screening disparities among ethnic minorities (Aziza, 2014). Studies on accessing breast cancer screening for particular cultural groups have been rare in Canada (Bowser et al., 2017). Using focused ethnography, this study examined how women from the MENA (Middle East and North Africa) region perceive and practise breast health, breast cancer risk and screening, and explored barriers to breast cancer screening. Six focus groups were conducted with six participants in each group, and the results were analyzed thematically. Three broad themes were identified: knowledge about breast health, cancer risk and screening services; barriers to maintaining breast health and screening; and potential solutions for overcoming barriers. The findings showed the participants have quite limited knowledge about breast cancer screening practices in Alberta and there remain multiple barriers to screening. The study contributes to the development of culturally appropriate interventions to overcome barriers and motivate MENA women to use breast cancer screening services.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".