Your browser doesn't support javascript.
loading
Heterogeneous attitudinal profiles towards gene editing: Evidence from latent class analysis.
Halstead, Isaac N; Boehnke, Jan R; Lewis, Gary J.
Afiliação
  • Halstead IN; Royal Holloway, University of London, UK.
  • Boehnke JR; University of Dundee, UK.
  • Lewis GJ; Royal Holloway, University of London, UK.
Public Underst Sci ; 32(2): 159-174, 2023 02.
Article em En | MEDLINE | ID: mdl-36003037
ABSTRACT
Advances in gene-editing technology have important implications for the treatment and prevention of disease. Accordingly, it is important to understand public perceptions towards gene editing, as the public's willingness to endorse gene editing may be as important as technological breakthroughs themselves. Previous research has almost exclusively examined attitudes towards gene editing on specific issues, but has not addressed how attitudes towards gene editing across a range of issues coalesce in individuals that is, the degree to which discrete, heterogeneous attitudinal profiles exist versus a simple support/oppose continuum. Here, we addressed this issue using latent class analysis on data from The Pew Research Center (N = 4726; US residents) across a wide range of gene-editing topics. We found that attitudes towards gene editing cohere into 10 distinct latent classes that showed some evidence of a support/oppose continuum, but also for clear qualitative differences between each class, even with support or oppose classes, on a number of issues. The most opposed classes significantly differed from the supporter classes in age, sex, political ideology and self-rated knowledge. These findings provide evidence that attitudes towards gene editing are heterogeneous and public discourse, as well as policy making need to consider a range of arguments when evaluating this technology.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Opinião Pública / Edição de Genes Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Opinião Pública / Edição de Genes Idioma: En Ano de publicação: 2023 Tipo de documento: Article