The Psychosocial Impact of the Decision to Undergo Risk-Reducing Salpingo-Oophorectomy Surgery in BRCA Mutation Carriers and the Role of Physician-Patient Communication
Bibliographic record
Abstract
mutations and presenting an increased risk of developing breast or ovarian cancer. This procedure is related to physiological, sexual, and psychosocial distress, which altogether increase uncertainty and complexity in the clinical decision-making process and post-surgery adaptation. Physician-patient communication (PPC) has been pointed out as a determinant factor in the decision-making to undergo RRSO, and the subsequent adjustment of women. However, studies examining the psychosocial impact of the decision-making process have been scarce and often lack clear theoretical frameworks. While the role of PPC in such processes has been highlighted in a few qualitative studies, there is a paucity of quantitative research addressing this question. Therefore, this narrative review, conducted using a multidisciplinary approach, was planned to: (1) present an updated medical background for RRSO; (2) analyze the psychosocial impact of the decision-making process within a theoretical framework of the Health Belief Model; and (3) discuss the role of PPC in such a decision-making process and in post-surgery. The collected research also enabled the recommendation of some additions to the existing clinical guidelines and the outlining of future research directions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".