Perceived risk and adherence to breast cancer screening guidelines among women with a familial history of breast cancer: A review of the literature
Bibliographic record
Abstract
OBJECTIVES: A small positive association has been consistently demonstrated between perceived breast cancer risk and mammography use. Evidence specific to women with familial breast cancer risk has not been previously reviewed. METHODS: A literature search was conducted. 186 studies were identified for abstract/full-text review, of which 10 articles were included. Manual searching identified 10 additional articles. Twenty articles examining the association between perceived breast cancer risk and adherence to mammography, clinical breast examination (CBE) or breast self-examination (BSE) guidelines among women with familial breast cancer risk were reviewed. Studies were classified according to screening modality, categorized by finding and ordered by year of publication. Studies assessing mammography were further classified according to the applied method of measuring perceived risk. RESULTS: Our review found a weak positive association between higher perceived risk and adherence to mammography guidelines among women with familial breast cancer risk. Consistent associations between perceived risk and adherence to CBE and BSE guidelines were not observed. CONCLUSIONS: Our ability to understand the relationship between perceived breast cancer risk and adherence to breast screening guidelines is limited, because most previous research is cross-sectional. Future studies with prospective methodologies that use consistent measurement methods and are adequately powered are warranted.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".