Disclosure of Genetics Research Results after the Death of the Patient Participant: A Qualitative Study of the Impact on Relatives
Bibliographic record
Abstract
When a gene mutation is identified in a research study following the death of the study participant, it is not clear whether such information should be made available to relatives. We report here an evaluation of the impact on relatives of being informed of study results that detected pathogenic BRCA2 mutations in a male relative, now deceased, who had early onset (under the age of 55) prostate cancer. The breast and ovarian cancer risk was unknown to the living relatives. Qualitative analysis of interviews with thirteen relatives indicated that those who had a higher risk perception, resulting from an awareness of cancer family history or experiential knowledge of cancer in their family, tended to adjust more easily to the results. All participants believed that genetics research results of clinical significance should be fed back to relatives. Those who were fully aware of the BRCA2 results and implications for themselves felt they had benefited from the information, irrespective of whether or not they had elected for genetic testing, because of the consequent availability of surveillance programs. Initial anxiety upon learning about the BRCA2 result was alleviated by genetic counselling. Factors influencing those who have not engaged with the information included scepticism related to the relative who attempted to inform them, young age and fear of cancer. Those who had not sought genetic counselling did not attempt further dissemination, and some were not undergoing regular screening. Implications for informed consent in genetics research programs, and the requirement for genetic counselling when research results are disclosed, are discussed.
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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 | 0.039 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.016 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".