A Peer Health Educator Program for Breast Cancer Screening Promotion: Arabic, Chinese, South Asian, and Vietnamese Immigrant Women’s Perspectives
Bibliographic record
Abstract
This study explored Arabic, Chinese, South Asian, and Vietnamese immigrant women's experiences with a peer health educator program, a public health program that facilitated access to breast health information and mammography screening. Framed within critical social theory, this participatory action research project took place from July 2009 to January 2011. Ten focus groups and 14 individual interviews were conducted with 82 immigrant women 40 years of age and older. Qualitative methods were utilized. Thematic content analysis derived from grounded theory and other qualitative literature was employed to analyze data. Four dominant themes emerged: Breast Cancer Prevention focused on learning within the program, Social Support provided by the peer health educator and other women, Screening Services Access for Women centered on service provision, and Program Enhancements related to specific modifications required to meet the needs of immigrant women accessing the program. The findings provide insights into strategies used to promote breast health, mammography screening, and the improvement of public health programming. Perceived barriers that continue to persist are structural barriers, such as the provision of information on breast cancer and screening by family physicians. A future goal is to improve collaborations between public health and primary care to minimize this barrier.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".