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Studies: Genetic Predisposition to Disease
 Description of Study | Research Team | Progress and Publications | Resources
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Non-Fatalism-Enhancing Messages and Lay Models of Gene-Environment Interaction

One of the projected health dividends of the Human Genome Project is the use of personalized predictive assessment for susceptibilities to common diseases. It is anticipated that personalized multi-gene testing will identify individual susceptibilities, consequently allowing persons to undertake preventative courses of action.

But if the benefits of these technologies are to be accessible to all Americans, several barriers will need to be overcome. One key factor will be effective methods for representing lay understandings of the interaction of genetics and other influences such as diet, exercise, stress, and medicine (often collapsed into the omnibus category of “environment”). For instance, existing research indicates that public health messages that link genes to disease causation increase fatalistic attitudes among lay recipients, especially low income individuals who already are likely to be high in fatalism. If patients believe that genetic diagnoses are fatalistic forecasts of future ill health, then they may not benefit from personalized genetic medicine.

This study will describe lay Americans’ understandings about the gene-environment interaction in common diseases. Specifically, researchers will use qualitative interview methods to develop mental maps of low income urban and rural African American and White Georgians’ models of the relationship between genes and environment in heart disease, lung cancer, and diabetes. Fifty in-depth, in-person interviews will be conducted and analyzed using qualitative readings. The transcripts will also be content analyzed using a coding scheme based on the qualitative analysis.

Preventative health messages based on these models will then be designed. In particular, audio messages will be used in an experiment delivered by a targeted telephone survey to test hypotheses which include, for example, 1) messages expressing interaction-based models produce less fatalism, and 2) messages consonant with pre-existing lay models produce higher intention to adopt recommended behaviors. The survey will also provide a quantitative description of the major lay mental models of gene-environment interaction among low income African Americans and White Americans.

Overall, the findings from this study will help develop improved public health message strategies for informing and motivating individuals with health risks to engage in disease prevention behaviors. These results particularly may be useful to make personalized genetic testing for prevention purposes more effective.

 

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