Cardiovascular genetic counselor decision making about discussing life insurance with patients
Bibliographic record
Abstract
Genetic counselors (GCs) educate patients about the benefits, risks, and limitations of genetic testing. The regulatory environment governing the use of genetic data in life insurance is not uniform internationally or within the United States (US). This multinational survey assessed how cardiovascular GCs incorporate the topic of life insurance (LI) into patient discussions. An online survey was distributed to GCs currently providing care to patients with non-syndromic cardiovascular disease. Brief clinical scenarios were included to avoid participants considering ambiguous or marginal phenotypes. Respondents were 121 cardiovascular GCs from five countries. Patient phenotype was the strongest indicator of whether GCs engaged in LI discussion. For phenotype-negative pediatric and adult patient scenarios, 62% and 74% of participants would discuss LI. For phenotype-positive pediatric and adult patient scenarios, 29% and 39% of participants would discuss LI. Non-U.S. participants were more likely to discuss LI with phenotype-positive patients than U.S. participants (61% vs. 33%, p = 0.005). Participants seeing primarily adult patients were more likely to discuss LI than those seeing primarily pediatric patients, for both pediatric (44% vs. 12%, p = 0.003) and adult phenotype-positive scenarios (46% vs. 17%, p = 0.008). Most participants would discuss LI with family variant testing (91%). Many participants reported patients declining genetic testing due to fear of genetic discrimination (77%) and 21% reported patients who were denied LI due to a genetic test result. Insufficient time was an important reported reason to not discuss LI (31%). Most participants reported learning about LI considerations in graduate education and reported confidence in their knowledge and ability to learn about related laws. Patient phenotype was the primary driver of whether cardiovascular GCs discussed life insurance implications of genetic testing with their patients, regardless of the age of the patient or the nationality of the genetic counselor. This study is the first to assess this nuanced aspect of cardiovascular genetic counseling and may support GC practice decisions and education.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".