Barriers and/or facilitating factors affecting breast screening mammograms in women 50 to 69 years of age in a northern Manitoba town
Bibliographic record
Abstract
Breast cancer is the most common cause of cancer in women over 30 years of age in Canada.lncreasing age is the greatest risk factor for developing cancer.The early detection of breast cancer through the secondary preventive method of mammography can reduce breast cancer mortality by 30% in women aged 50 to 69 years of age if there is a70%o rate of participation of these women.The Manitoba Breast Screening Program provides a mobile screening mammogram service for women living in rural areas of Manitoba.For 200012001, the town of Churchill's participation was approximately 48% of eligible women.The overall goal of this practícum project was to discover factors that act as barriers and/or facilitators of women's participation in the mobile breast screening program in the town of Churchill.The methodology included achartaudit and interviews of health care professionals and community women.From the information obtained, recoÍtmendations and interventions were suggested to enhance women's access to participating in the breast screening program.Findings of the project suggested the type of primary care visit had apositive or negative effect on preventive breast screening referrals.In addition, barriers and/or facilitators to accessing breast screening exist within the health care system as well as the social/cultural environment of women.Addressing social, ethnic and cultural needs and beließ are imporüant if women's participation in the brcast screening program is to be enhanced.primary care iv practitioners' referrals for preventive screening may influence \¡/omen's health practices, Collaboration amongst health care professionals and systems is necessary to improve access to screening mammograms.Debbie Askin and Dr. Alec Macaulay for their support, guidance and patience throughout this project.Especially thank you for being willing to accommodate the long distance commwrication of information through email which made possible my clinical placement in Churchill.It is very much appreciated.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".