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Record W4416673326 · doi:10.1002/jgc4.70146

Cardiovascular genetic counselor decision making about discussing life insurance with patients

2025· article· en· W4416673326 on OpenAlexaff
Sara Cherny, Sarah Jurgensmeyer, Miguel Moran, Susan Christian, Gregory Webster

Bibliographic record

VenueJournal of Genetic Counseling · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsUniversity of Alberta
FundersNational Center for Advancing Translational SciencesNational Heart, Lung, and Blood Institute
KeywordsGenetic counselingGenetic testingYoung adultLife insuranceMEDLINEComprehensionTest (biology)

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.665
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.248
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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