Patient Decision Aid for Contralateral Prophylactic Mastectomy for Use in the Consultation: A Feasibility Study
Bibliographic record
Abstract
Background: Rates of contralateral prophylactic mastectomy (cpm) continue to rise internationally despite evidence-based guidance strongly discouraging its use in most women with unilateral breast cancer. The purpose of the present study was to develop and assess the feasibility of a knowledge translation tool [a patient decision aid (da)] designed to enhance evidence-informed shared decision-making about cpm. Methods: A consultation da was developed using the Ottawa Patient Decision Aid Development eTraining in consultation with clinicians and knowledge translation experts. The final da was then assessed for feasibility with health care professionals and patients across Canada. The assessment involved a survey completed online (health care professionals) or by telephone (patients). Survey data were analyzed using descriptive statistics for closed-ended questions and qualitative content analysis for open-ended questions. Results: The 51 participants who completed the survey included 39 health care professionals and 12 patients. The da was acceptable; 88% of participants viewed it as having the right amount of information or slightly more or less information than they would like. Almost all participants (98%) felt that the da would prepare patients to make better decisions. The aid was perceived to be usable, with 73% of participants stating that they would be willing to use or share the da. Conclusions: The cpm patient da developed for the present study was viewed by health care professionals and patients across Canada to be acceptable and usable during the clinical consultation. It holds promise as a knowledge translation tool to be used by clinicians in consultation with women who have unilateral breast cancer to enhance evidence-informed and shared decision-making with respect to undergoing cpm.
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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 | 0.029 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".