The Many Facets of Genetic Literacy: Assessing the Scalability of Multiple Measures for Broad Use in Survey Research |
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Authors: | Leah R. Abrams Colleen M. McBride Gillian W. Hooker Joseph N. Cappella Laura M. Koehly |
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Affiliation: | 1. Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, Maryland, United States of America.; 2. Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.; 3. NextGxDx, Franklin, Tennessee, United States of America.; 4. Annenberg School for Communication, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.; Leibniz Institute for Prevention Research and Epidemiology (BIPS), GERMANY, |
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Abstract: | ObjectivesTo determine how three dimensions of genetic literacy (familiarity, skills, and factual knowledge) fit the hierarchy of knowledge outlined in E.M. Rogers’ Diffusion of Innovations to better conceptualize lay understandings of genomics.MethodsA consumer panel representing the US adult population (N = 1016) completed an electronic survey in November 2013. Adjusting for education, we used correlations, principle components analysis, Mokken Scale tests, and linear regressions to assess how scores on the three genetic literacy sub-dimensions fit an ordered scale.ResultsThe three scores significantly loaded onto one factor, even when adjusting for education. Analyses revealed moderate strength in scaling (0.416, p<0.001) and a difficulty ordering that matched Rogers’ hierarchy (knowledge more difficult than skills, followed by familiarity). Skills scores partially mediated the association between familiarity and knowledge with a significant indirect effect (0.241, p<0.001).ConclusionWe established an ordering in genetic literacy sub-dimensions such that familiarity with terminology precedes skills using information, which in turn precedes factual knowledge. This ordering is important to contextualizing previous findings, guiding measurement in future research, and identifying gaps in the understanding of genomics relevant to the demands of differing applications. |
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