Development and Evaluation of a Decision Aid for <i>BRCA</i> Carriers with Breast Cancer
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
BRCA+ breast cancer patients face high risk for a second breast cancer and ovarian cancer. Helping these women decide among risk-reducing options requires effectively conveying complex, emotionally-laden, information. To support their decision-making needs, we developed a web-based decision aid (DA) as an adjunct to genetic counseling. Phase 1 used focus groups to determine decision-making needs. These findings and the Ottawa Decision Support Framework guided the DA development. Phase 2 involved nine focus groups of four stakeholder types (BRCA+ breast cancer patients, breast cancer advocates, and genetics and oncology professionals) to evaluate the DA's decision-making utility, information content, visual display, and implementation. Overall, feedback was very favorable about the DA, especially a values and preferences ranking-exercise and an output page displaying personalized responses. Stakeholders were divided as to whether the DA should be offered at-home versus only in a clinical setting. This well-received DA will be further tested to determine accessibility and effectiveness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.000 | 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