Development and evaluation of a breast cancer prevention decision aid for higher‐risk women
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: To develop and evaluate the effectiveness of a breast cancer prevention decision aid for women aged 50 and older at higher risk of breast cancer. DESIGN: Pre-test-post-test study using decision aid alone and in combination with counselling. SETTING: Breast Cancer Risk Assessment Clinic. PARTICIPANTS: Twenty-seven women aged 50-69 with 1.66% or higher 5-year risk of breast cancer. INTERVENTION: Self-administered breast cancer prevention decision aid. MAIN OUTCOME MEASURES: Acceptability; decisional conflict; knowledge; realistic expectations; choice predisposition; intention to improve life-style practices; psychological distress; and satisfaction with preparation for consultation. RESULTS: The decision aid alone, or in combination with counselling, decreased some dimensions of decisional conflict, increased knowledge (P < 0.01), and created more realistic expectations (P < 0.01). The aid in combination with counselling, significantly reduced decisional conflict (P < 0.01) and psychological distress (P < 0.02), helped the uncertain become certain (P < 0.02), and increased intentions to adopt healthier life-style practices (P < 0.03). Women rated the aid as acceptable, and both women and practitioners were satisfied with the effect it had on the counselling session. CONCLUSION: The decision aid shows promise as a useful decision support tool. Further research should compare the effect of the decision aid in combination with counselling to counselling alone.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.000 | 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