The influence of dispositional optimism on decision regret to undergo major breast reconstructive surgery
Bibliographic record
Abstract
BACKGROUND & OBJECTIVES: It is not known if optimism influences regret following major reconstructive breast surgery. We examined the relationship between dispositional optimism, major complications and decision regret in patients undergoing microsurgical breast reconstruction. METHODS: A consecutive series of 290 patients were surveyed. Independent variables were: (1) dispositional optimism and (2) major complications. The primary outcome was Decision Regret. A multivariate regression analysis determined the relationship between the independent variables, confounders and decision regret. RESULTS: Of the 181 respondents, 63% reported no regret after breast reconstruction, 26% had mild regret, and 11% moderate to severe regret. Major complications did not have a significant effect on decision regret, and the impact of dispositional optimism was not significant in Caucasian women. There was a significant effect in non-Caucasian women with less optimism who had significantly higher levels of mild regret 1.36 (CI 1.02-1.97) and moderate to severe regret 1.64 (CI 1.0-93.87). CONCLUSIONS: This is the first paper to identify a subgroup of non-Caucasian patients with low dispositional optimism who may be at risk for developing regret after microsurgical breast reconstruction. Possible strategies to ameliorate regret may involve addressing cultural and language barriers, setting realistic expectations, and providing more support during the pre-operative decision-making phase.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".