Date of Award
Doctor of Philosophy (PhD)
Recent biomedical research has focused on early detection of Alzheimer’s disease (AD) pathology in people who do not yet have symptoms of the disease. This focus represents a shift in current diagnostic practices from detection of cognitive impairment to include detection of disease risk. This study examines attitudes regarding preclinical risk detection for AD in individuals aged 19-65 recruited online using Amazon’s Mechanical Turk. Participants were randomized to view an educational intervention (varying method and depth of education) and viewed a videotaped disclosure of hypothetical risk for AD to themselves (varying level of risk). Participants reported on several individual difference variables (e.g., prior knowledge, experience with AD) as well as their interest in predictive testing and subjective risk of AD. The results of this study show that prior knowledge, experience with AD, depth of education, and level of risk disclosed interact to influence subjective risk estimates. These findings have implications for the development of empirically-supported education interventions and disclosure processes for preclinical AD.
Chair and Committee
Brian D. Carpenter
David Balota, Mitchell Sommers, Matthew S. Gabel, Desiree A. White,
Gooblar, Jonathan, "Risk Communication for Preclinical Alzheimer's Disease" (2017). Arts & Sciences Electronic Theses and Dissertations. 1266.
Available for download on Wednesday, July 19, 2119