The phases of disclosing BRCA1/2 genetic information to offspring
Bibliographic record
Abstract
OBJECTIVE: Women who carry a genetic mutation for hereditary breast/ovarian cancer (BRCA1 or BRCA2) are at high risk to develop cancer. A positive genetic test result also has implications for a BRCA1/2 carrier's offspring who each have a 50% chance of inheriting the mutation. The dissemination of BRCA1/2-related information by carriers to offspring is not well understood. Our study examines the experiences of BRCA1/2 carriers in communicating genetic information to their offspring using a grounded theory approach. METHODS: Qualitative data were obtained from a multi-site group therapy trial for BRCA1/2 carriers with primary themes identified and coded using the constant comparison technique and verified by team members. RESULTS: Female participants had a mean age of 45.4 years, 83% were married, 71% had children (ranging from ages 2 to 30 years) and 45.9% had a prior diagnosis of cancer. Dissemination of genetic information by BRCA1/2 carriers to their offspring was described as a process involving several distinct phases with specific challenges within each phase. Several themes were identified including dilemmas on 'if' and 'when' to disclose to offspring, concerns should offspring receive a positive test result for BRCA1/2, dilemmas around feeling a need to protect versus the need to inform, and women as being the primary communicators. CONCLUSION: These findings have implications for genetic counselling as well as follow-up.
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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 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".