Providers’ perspectives on the reproductive decision-making of BRCA-positive women
Bibliographic record
Abstract
Abstract Background Reproductive decision-making is difficult for BRCA-positive women. Our objective was to assess the complexities of decision-making and identify decisional supports for patients and providers when discussing reproductive options prior to risk-reducing salpingo-oophorectomy (RRSO). Methods This study was of qualitive design, using data collection via semi-structured interviews conducted from November 2018 to October 2020. Individuals were included if they were identified to provide care to BRCA-positive women. In total, 19 providers were approached and 15 consented to participate. Providers were recruited from three clinics in Toronto, Ontario located at academic centers: [1] A familial ovarian cancer clinic, [2] A familial breast cancer clinic and [3] A fertility clinic, all of which treat carriers of the BRCA1/BRCA2 genetic mutation. The interview guide was developed according to the Ottawa Decision Support Framework and included questions regarding reproductive options available to patients, factors that impact the decision-making process and the role of decisional support. Interviews were transcribed and transcripts were analyzed thematically using NVIVO 12. Results Providers identified three major decisions that reproductive-aged women face when a BRCA mutation is discovered: [1] “Do I want children?”; [2] “Do I want to take the chance of passing on this the mutation?”; and [3] “Do I want to carry a child?” Inherent decision challenges that are faced by both providers and patients included difficult decision type, competing options, scientifically uncertain outcomes, and challenging decision timing. Modifiable decisional needs included: inadequate knowledge, unrealistic expectations, unclear values and inadequate support or resources. Identified clinical gaps included counselling time constraints, lack of reliable sources of background information for patients or providers and need for time-sensitive, geographically accessible, and centralized care. Conclusion Our study identified a need for a patient information resource that can be immediately provided to patients who carry a BRCA genetic mutation. Other suggestions for clinical practice include more time during consultation appointments, adequate follow-up, value-centric counseling, access to psychosocial support, and a specialized decisional coach.
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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 | 0.015 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".