Knowledge, Attitudes, and Practices Surrounding Breast Cancer Screening in Educated Appalachian Women
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To determine how and what women learn about breast cancer and screening practices and which factors influence women's breast cancer screening practices. DESIGN: Descriptive analysis of questionnaire data collected at the time of enrollment in a clinical trial. SETTING: Breast care center of a mid-Atlantic academic health sciences center. SAMPLE: 185 women in a predominantly Appalachian, entirely rural state. METHODS: Participants completed the Modified Toronto Breast Self-Examination Inventory and questions related to personal mammography practices at the time of enrollment before randomization in a longitudinal clinical intervention study. MAIN RESEARCH VARIABLES: Women's demographics, knowledge of breast cancer screening practices, adherence to breast cancer screening guidelines, and motivation, knowledge, and practice proficiency surrounding breast cancer screening. FINDINGS: These educated women had knowledge deficits about breast cancer, breast cancer risk factors, and screening guidelines, particularly the timing and practice behaviors of breast self-examination. Women who had received healthcare and cancer-screening instruction by healthcare providers, including advanced practice nurses, had greater knowledge of breast cancer and detection practices. CONCLUSIONS: Women still have knowledge deficits about breast cancer, breast cancer detection, and personal risk factors. In addition, some educated women in this study failed to practice breast cancer screening according to current guidelines. IMPLICATIONS FOR NURSING: Practitioners must continue to remind and update women about breast disease, and women's cancer-screening practices must be reinforced. All levels of providers should improve their rates of performing clinical breast examinations with physical examinations. Nurses, who greatly influence women's health care, must remain current in their knowledge of breast disease, screening, and treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".