Breast Reconstruction Decision Aids Decrease Decisional Conflict and Improve Decisional Satisfaction: A Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Decision aids are useful adjuncts to clinical consultations for women considering breast reconstruction. This study compared the impact of two online decision aids, the Breast RECONstruction Decision Aid (BRECONDA) and the Alberta Health Services (AHS) decision aid, on decisional conflict, decisional satisfaction, and decisional regret. METHODS: This randomized controlled trial included 60 women considering whether or not to undergo breast reconstruction. Two online decision aids, the AHS and the BRECONDA, were compared using randomized two-arm equal allocation. Participants responded to questionnaires at baseline, after the first and second consultations, and at 6 weeks and 6 months after deciding to, or not to, undergo reconstruction. Change in decisional conflict scores was compared between the BRECONDA and the AHS decision aid. Secondary outcomes included decisional regret and decisional satisfaction. RESULTS: Both groups were similar in demographic, clinical, and behavioral characteristics. Women spent more time consulting the BRECONDA in comparison to women using the AHS decision aid (56.7 ± 53.8 minutes versus 28.4 ± 27.2 minutes; P < 0.05). Decisional conflict decreased (P < 0.05), and decisional satisfaction improved over time in both groups (P < 0.05). However, there were no differences based on the type of decision aid used (P > 0.05). Both decision aids had a similar reduction in decisional regret (P > 0.05). CONCLUSIONS: Decision aids decrease decisional conflict and improve decisional satisfaction among women considering breast reconstruction. Physicians should therefore offer patients access to decision aids as an adjunct to breast reconstruction consultations to help patients make an informed decision. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, I.
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How this classification was reachedexpand
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 | 0.005 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".