Evidence map›Paper›PMID 35663290›Full record

ArticleRisk management and insurance review2021

Genetic testing and insurance implications: Surveying the US general population about discrimination concerns and knowledge of the Genetic Information Nondiscrimination Act (GINA).

Anya E R Prince, Wendy R Uhlmann, Sonia M Suter, Aaron M Scherer

Abstract read
In one paragraph

Article in Risk management and insurance review, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
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  3. Review
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  5. Article
  6. Article
  7. Enhancing patient representation learning with inferred family pedigrees improves disease risk prediction.Journal of the American Medical Informatics Association : JAMIA · 2025
    Article
  8. Principles and Policy Recommendations for Comprehensive Genetic Data Governance.Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society · 2025
    Article
  9. Article
  10. Review
  11. Article
  12. Review
  13. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Anya E R PrinceUniversity of Iowa College of Law.
Wendy R UhlmannDepartment of Internal Medicine, Division of Genetic Medicine; Department of Human Genetics; Center for Bioethics and Social Sciences in Medicine, University of Michigan School of Medicine.
Sonia M SuterThe George Washington University Law School.
Aaron M SchererDepartment of Internal Medicine, University of Iowa.

Funding

Use of Genetic Information by Life, Long-term Care, and Disability InsurersR00HG008819 · NHGRI · UNIVERSITY OF IOWA · PI PRINCE, ANYA E.R. · 2017 to 2019
$728k
NHGRI NIH HHS R00 HG008819
6 · The paper itself

Abstract

Globally, due to public concerns of genetic discrimination, some countries and insurance industries have adopted policies restricting insurer use of genetic information, such as the US Genetic Information Nondiscrimination Act (GINA). This study reports on combined analysis of two surveys assessing public knowledge of GINA and concerns of genetic discrimination in a diverse U.S. sample (N=1616). We focus on whether occupation, genetic testing history, and insurance status are correlated with knowledge of GINA or concerns of discrimination. While bivariate analysis identified some populations with higher subjective/objective knowledge and concern relative to counterparts, multivariable regression identified very few significant associations with outcomes of interest. Overall, this study highlights lack of awareness and understanding of GINA, even among subpopulations hypothesized to have greater knowledge of the law. These findings have implications for the broader debate around insurer use of genetic information.

Identifiers

PMID35663290
PMCPMC9165621

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.