Volume 28, Issue 3 pp. 664-672
ORIGINAL ARTICLE
Free Access

Exploring genetic counselors’ perceptions of usefulness and intentions to use refined risk models in clinical care based on the Technology Acceptance Model (TAM)

Christopher Heinlen

Corresponding Author

Christopher Heinlen

Division of Human Genetics, Department of Internal Medicine, The Ohio State University, Columbus, Ohio

Genetic Counseling Program, Department of Genetics, OhioHealth, Columbus, Ohio

Correspondence

Christopher Heinlen, OhioHealth, Columbus, OH.

Email: [email protected]

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Shelly R. Hovick

Shelly R. Hovick

School of Communication, The Ohio State University, Columbus, Ohio

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Guy N. Brock

Guy N. Brock

Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio

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Brett G. Klamer

Brett G. Klamer

Center for Biostatistics, The Ohio State University, Columbus, Ohio

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Amanda Ewart Toland

Amanda Ewart Toland

Division of Human Genetics, Department of Internal Medicine, The Ohio State University, Columbus, Ohio

Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio

Department of Cancer Biology and Genetics, The Ohio State University Wexner Medical Center, Columbus, Ohio

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Leigha Senter

Leigha Senter

Division of Human Genetics, Department of Internal Medicine, The Ohio State University, Columbus, Ohio

Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio

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First published: 07 March 2019
Citations: 5

Abstract

Pathogenic germline mutations in the BRCA1 or BRCA2 genes are associated with an elevated lifetime risk for breast (50%–85% risk) and ovarian cancer (20%–40% risk). Genome-wide association studies have identified over 100 genetic variants associated with modified breast and/or ovarian cancer risk in BRCA1 and BRCA2 carriers. Risk models generated based on these variants have shown that these genetic modifiers strongly influence absolute risk of developing breast or ovarian cancer in BRCA mutation carriers. There is a lack of understanding, however, about the clinical applicability and utility of these risk models. To investigate this gap, we collected survey data from 274 cancer genetic counselors (GCs) through the National Society of Genetic Counselors Cancer Special Interest Group. Questions assessed perceptions of usefulness and intentions of genetic counselors to use these refined risk models in clinical care based on the Technology Acceptance Model (TAM). We found that GCs’ reactions to the estimates were largely positive, though they thought the possibility of changing management based on results was unlikely. Additionally, we found that more experienced GCs were more likely to consider refined risk estimates in clinic. Support also was provided for core predictions within the TAM, whereby the perceived usefulness (indirect effect est. = 0.08, 95% CI: [0.04, 0.13]) and perceived ease of use (indirect effect est. = 0.078, 95% CI: [0.04, 0.13]) of refined risk estimates were indirectly associated with intentions to use via attitudes.

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