Women's perceptions of personalized risk‐based breast cancer screening and prevention: An international focus group study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Increased knowledge of breast cancer risk factors enables a shift from one-size-fits-all breast cancer screening to a risk-based approach, tailoring screening policy to a woman's individual risk. New opportunities for prevention will arise. However, before this novel screening and prevention program is introduced, its acceptability from a woman's perspective needs to be explored. METHODS: Women eligible for breast cancer screening in the Netherlands, United Kingdom, and Sweden were invited to take part in focus groups. A total of 143 women participated. Data were transcribed verbatim and analyzed using thematic analysis. RESULTS: Analysis identified five themes across the three countries. The first theme "impact of knowledge" describes women's concern of not being able to unlearn their risk, perceiving it as either a motivator for change or a burden which may lead to stigma. The second theme "belief in science" explains women's need to trust the science behind the risk assessment and subsequent care pathways. Theme three "emotional impact" explores, eg, women's perceived anxiety and (false) reassurance, which may result from knowing their risk. Theme four "decision making" highlights cultural differences in shared versus individual decision making. Theme five "attitude to medication" explores the controversial topic of offering preventative medication for breast cancer risk reduction. CONCLUSIONS: Acceptability of risk-based screening and prevention is mixed. Women's perceptions are informed by a lack of knowledge, cultural norms, and common emotional concerns, which highlights the importance of tailored educational materials and risk counselling to aid either shared or individual informed decision making.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 it