Efficacy of a Web-Based Intelligent Tutoring System for Communicating Genetic Risk of Breast Cancer

Christopher R. Wolfe, Valerie F. Reyna, Colin L. Widmer, Elizabeth M. Cedillos, Christopher R. Fisher, Priscila G. Brust-Renck and Audrey M. Weil

Medical Decision Making, 2015, vol. 35, issue 1, 46-59

Abstract: Background . Many healthy women consider genetic testing for breast cancer risk, yet BRCA testing issues are complex. Objective . To determine whether an intelligent tutor, BRCA Gist, grounded in fuzzy-trace theory (FTT), increases gist comprehension and knowledge about genetic testing for breast cancer risk, improving decision making. Design . In 2 experiments, 410 healthy undergraduate women were randomly assigned to 1 of 3 groups: an online module using a Web-based tutoring system (BRCA Gist) that uses artificial intelligence technology, a second group read highly similar content from the National Cancer Institute (NCI) Web site, and a third that completed an unrelated tutorial. Intervention . BRCA Gist applied FTT and was designed to help participants develop gist comprehension of topics relevant to decisions about BRCA genetic testing, including how breast cancer spreads, inherited genetic mutations, and base rates. Measures . We measured content knowledge, gist comprehension of decision-relevant information, interest in testing, and genetic risk and testing judgments. Results . Control knowledge scores ranged from 54% to 56%, NCI improved significantly to 65% and 70%, and BRCA Gist improved significantly more to 75% and 77%, P

Keywords: genetic testing; breast cancer risk; Intelligent Tutoring System; Fuzzy-Trace Theory (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:35:y:2015:i:1:p:46-59

DOI: 10.1177/0272989X14535983

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