Examination of Breast Cancer Screening Knowledge, Attitudes, and Beliefs among Syrian Refugee Women in a Western Canadian Province
Bibliographic record
Abstract
BACKGROUND: Women living in the Arab world present low breast cancer screening rates, delayed diagnosis, and higher mortality rates. PURPOSE: To further explore the Muslim Syrian refugee women's breast self-examination (BSE), utilization of clinical breast examination (CBE) and mammography. METHODS: A cross-sectional descriptive exploratory study design was used. The sample consisted of 75 refugee women. Data were collected using Champion's Health Belief Model Scale, the Cancer Stigma Scale, and the Arab Culture-Specific Barriers to Breast Cancer Questionnaire. Descriptive, Pearson correlation and logistic regression analyses were used to analyze the data. RESULTS: A minority of women had BSE (32%), CBE (12%) and mammograms (6.7%) anytime during their lifetime. Women's breast cancer screening (BCS) knowledge ranked at a medium level (M = 10.57, SD = 0.40). Low knowledge score, BSE information, policy opposition, responsibility, barriers to BSE, and seriousness were found to be statistically significant in women's BSE practice. BSE benefits and religious beliefs significantly predict CBE Age, education, knowledge, responsibility, susceptibility, social barriers, and religious beliefs were statistically significant in women's mammography use (p < .01). CONCLUSIONS: Participants' breast cancer screening practices were low. Health beliefs, Arab culture and stigma about cancer affected women's BCS practices. Faith-based interventions may improve knowledge and practices.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".