Elsevier

Preventive Medicine

Volume 30, Issue 2, February 2000, Pages 155-166
Preventive Medicine

Regular Article
Likelihood of Undergoing Genetic Testing for Cancer Risk: A Population-Based Study,☆☆

https://doi.org/10.1006/pmed.1999.0610Get rights and content

Abstract

Background. Studies on public perceptions of genetic susceptibility testing for cancer risks are few and tend to focus on specific cancer risks of higher-risk populations, ignoring the general population and their perceived risk of getting any cancers. This study develops and tests a psychosocial model of the proximal and distal influences on likelihood of undergoing genetic susceptibility testing for cancer risk among a population-based sample.

Methods. The sample consisted of 622 adults aged 18–75 interviewed by telephone. The survey instrument included measures derived from the Health Belief Model and adaptations of existing measures from the literature. Data were analyzed using structural equation modeling techniques.

Results. The model suggested independent main effects for perceived benefits, perceived barriers, perceived susceptibility, and pessimism while simultaneously accounting for the effects of age, socioeconomic status, family history of cancer, and awareness of the existence of genetic susceptibility testing for cancer risk. The model explained 34% of the variance in likelihood.

Conclusions. While perceived benefits, perceived barriers, perceived susceptibility, and pessimism may directly impact likelihood, they may also mediate the effects of age, socioeconomic status, family history of cancer, and awareness of cancer genetic susceptibility testing, on likelihood.

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  • Cited by (0)

    Leadership for data collection provided by Joan Skelly and Barbara Branch is appreciated. The contibutions to this research of Patricia Gavin and Tammy Snell of the Glens Falls Hospital and Roger Secker-Walker of the University of Vermont are acknowledged.

    ☆☆

    This study was supported by a grant from the Lake Champlain Cancer Research Organization to the Glens Falls Hospital, Glens Falls, New York. It was also supported by Vermont Cancer Center Grant CA22435.

    2

    To whom correspondence and reprint requests should be addressed at the Department of Medical Biostatistics, University of Vermont, 25C Hills Building, Burlington, Vermont 05405. Fax: (802) 656-0632. E-mail: [email protected].

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