8. Decision Regret in Breast Reconstruction Patients Following Preconsultation Education Group Intervention: A Randomized Controlled Trial
Bibliographic record
Abstract
Purpose: Decision regret is an important long-term outcome in evaluating decision-making following surgery. The decision to undergo postmastectomy breast reconstruction (PMBR) is complex. We developed the Preconsultation Education Group Intervention (PEGI) as a decision support tool to educate patients about PMBR. PEGI was previously shown to significantly increase patient knowledge of PMBR. In this study, we investigate the effect of PEGI on decision regret at 6 months postconsultation. Methods: Patients referred to University Health Network (UHN) for PMBR were randomized to receive PEGI or routine education (control) groups preconsultation. Patients filled questionnaires at baseline (T0), one week postconsultation (T1) and 6 months postconsultation (T2). Outcome measures were assessed using the BREAST-Q Satisfaction with Information at T1, Decision Regret Scale at T2, Satisfaction with Decision Scale at T2, and State-Trait Anxiety Inventory (STAI) at T2. Results: Of the 156 patients randomized, 137 patients completed the T1 questionnaires. Satisfaction with Information was significantly higher at T1 in PEGI with a median (IQR) of 75 (60, 85) compared to controls with 64 (51, 74) (p=0.02). Of the 137 patients, 97 completed their outcome measures at T2. Forty patients had undergone surgery by T2, of which 27 (67.5%) underwent autologous reconstruction, 7 (17.5%) had implant-based reconstruction, and 6 (15%) had mixed implants with latissimus dorsi flap reconstruction. There was no significant difference in decision regret or satisfaction with decision between the two groups. Decision regret was low overall, with 19.6% expressing no regret, 40.2% expressing mild regret, 40.2% expressing moderate regret, and none expressing high regret. Additionally, the two groups had similar levels of anxiety at T2. Furthermore, we found that undergoing PMBR was associated with lower decision regret (r= -0.344, p=0.001). Lower decision regret was also associated with lower anxiety levels at T2 (rs= 0.374, p<0.001). Lastly, lower decision regret was significantly correlated with higher BREAST-Q Satisfaction with Information at T1 (rs= -0.22, p=0.032). Conclusion: The decision support tool PEGI had no effect on long-term decision regret or satisfaction with decision, but significantly increased patient reported satisfaction with information. Overall, lower long-term decision regret was associated with undergoing PMBR, reduced anxiety, and increased satisfaction with information regardless of the preconsultation education method.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".