Decision-Making Process of Women Carrying a <i>BRCA1</i> or <i>BRCA2</i> Mutation Who Have Chosen Prophylactic Mastectomy
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To explore the decision-making process of women with a BRCA1 or BRCA2 gene mutation who have chosen to undergo prophylactic mastectomy. DESIGN: Cross-sectional, qualitative, descriptive design. SETTING: Participants were recruited from an outpatient cancer prevention center in the oncology and medical genetics departments of a large university-affiliated hospital in Montreal, Quebec, Canada. SAMPLE: 10 women carrying a BRCA1 or BRCA2 mutation; 8 previously had had a prophylactic mastectomy and 2 were scheduled for surgery at the time of study. METHODS: Semistructured, in-depth interviews were conducted. Field notes were written and audiotapes were transcribed verbatim. The textual data were coded and analyzed. MAIN RESEARCH VARIABLES: Decision-making process for prophylactic mastectomy. FINDINGS: Two broad findings emerged. First, several intrapersonal and contextual factors interacted throughout the process to move women either closer to choosing a prophylactic mastectomy or further from the decision. Second, all women reported experiencing a "pivotal point," an emotionally charged event when the decision to have a prophylactic mastectomy became definitive. Pivotal points for patients included either receiving a positive result for a genetic mutation or a breast cancer diagnosis for herself or a family member in the context of positive mutation status. CONCLUSIONS: Decision making about prophylactic mastectomy was an affective and intuitive process incorporating contexts and their relations rather than a rational, straight-forward process of weighing pros and cons. IMPLICATIONS FOR NURSING: Supportive interventions for women in this population should explicitly address the individual and the inter-relationships of contextual factors that shape decision making about prophylactic mastectomy while recognizing important affective components involved.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 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".