Factors Associated with an Individual's Decision to Withdraw from Genetic Testing for Breast And Ovarian Cancer Susceptibility: Implications for Counseling
Bibliographic record
Abstract
Our study aimed to examine why individuals withdraw from genetic testing for breast and ovarian cancer susceptibility. We explored the characteristics of 334 individuals from high-risk breast and ovarian cancer families who declined genetic testing for BRCA1/2 mutations, when, and why they did so. Individuals who declined genetic testing were older, and a greater proportion had never developed breast or ovarian cancer. Fifty one per cent (51.1%) of individuals withdrew after the first genetic counseling session. Most of those who declined were afraid of the psychological effects of genetic testing (36.3%). The next most-cited explanations concerned logistic problems such as a limited ability to travel, lack of time, personal issues, advanced age, or health problems (21.7%). The third category included individuals who did not see any advantage in being tested (14.5%). Insurability was a concern (5.9%), mainly for men. Surprisingly, confidentiality was not a frequently reported issue (1.3%). Sixty eight per cent (68%) of individuals belonging to a family in which at least one individual has been tested withdrew after the presence of a deleterious BRCA1/2 mutation in a relative was disclosed, compared to 42% after the disclosure of a nonconclusive test result in at least one relative. Concern about the psychological effects of the result was still one of the major reasons. Several factors may influence an individual's decision to decline genetic testing; a greater understanding of these issues may help health professionals to better meet the needs and concerns of individuals from high-risk families, thus possibly improving their health outcomes.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".