Literature DB >> 19450036

Impact of genetic risk information and type of disease on perceived risk, anticipated affect, and expected consequences of genetic tests.

Linda D Cameron1, Kerry A Sherman, Theresa M Marteau, Paul M Brown.   

Abstract

OBJECTIVE: Genetic tests vary in their prediction of disease occurrence, with some mutations conferring relatively low risk and others indicating near certainty. The authors assessed how increments in absolute risk of disease influence risk perceptions, interest, and expected consequences of genetic tests for diseases of varying severity.
DESIGN: Adults (N = 752), recruited from New Zealand, Australia, and the United Kingdom for an online analogue study, were randomly assigned to receive information about a test of genetic risk for diabetes, heart disease, colon cancer, or lung cancer. The lifetime risk varied across conditions by 10% increments, from 20% to 100%. MAIN OUTCOME MEASURES: Participants completed measures of perceived likelihood of disease for individuals with mutations, risk-related affect, interest, and testing consequences.
RESULTS: Analyses revealed two increment clusters yielding differences in likelihood perceptions: A "moderate-risk" cluster (20%-70%), and a "high-risk" cluster (80%-100%). Risk increment influenced anticipated worry, feelings of risk, testing-induced distress, and family obligations, with nonlinear patterns including disproportionately high responses for the 50% increment. Risk increment did not alter testing interest or perceived benefits. These patterns of effects held across the four diseases.
CONCLUSION: Magnitude of risk from genetic testing has a nonlinear influence on risk-related appraisals and affect but is unrelated to test interest.

Entities:  

Mesh:

Year:  2009        PMID: 19450036     DOI: 10.1037/a0013947

Source DB:  PubMed          Journal:  Health Psychol        ISSN: 0278-6133            Impact factor:   4.267


  51 in total

1.  Preferences for genetic and behavioral health information: the impact of risk factors and disease attributions.

Authors:  Suzanne C O'Neill; Colleen M McBride; Sharon Hensley Alford; Kimberly A Kaphingst
Journal:  Ann Behav Med       Date:  2010-10

2.  False-positive newborn screening result and future health care use in a state Medicaid cohort.

Authors:  Beth A Tarini; Sarah J Clark; Subra Pilli; Kevin J Dombkowski; Steven J Korzeniewski; Acham Gebremariam; Jon Eisenhandler; Violanda Grigorescu
Journal:  Pediatrics       Date:  2011-09-19       Impact factor: 7.124

3.  Direct-to-consumer personal genomic testing: a case study and practical recommendations for “genomic counseling”.

Authors:  Amy C Sturm; Kandamurugu Manickam
Journal:  J Genet Couns       Date:  2012-06       Impact factor: 2.537

4.  Taking Stock of Unrealistic Optimism.

Authors:  James A Shepperd; William M P Klein; Erika A Waters; Neil D Weinstein
Journal:  Perspect Psychol Sci       Date:  2013-07

5.  Communication strategies for enhancing understanding of the behavioral implications of genetic and biomarker tests for disease risk: the role of coherence.

Authors:  Linda D Cameron; Theresa M Marteau; Paul M Brown; William M P Klein; Kerry A Sherman
Journal:  J Behav Med       Date:  2011-06-23

6.  "Awakening to" a new meaning of being at-risk for arrhythmogenic right ventricular cardiomyopathy: a grounded theory study.

Authors:  April Manuel; Fern Brunger
Journal:  J Community Genet       Date:  2015-01-27

7.  Letter to the Editor: Response to Cox (2018).

Authors:  Teresa Gavaruzzi; Alessandra Tasso; Marzena Franiuk; Liliana Varesco; Lorella Lotto
Journal:  J Genet Couns       Date:  2018-09       Impact factor: 2.537

8.  Communication of uncertainty regarding individualized cancer risk estimates: effects and influential factors.

Authors:  Paul K J Han; William M P Klein; Tom Lehman; Bill Killam; Holly Massett; Andrew N Freedman
Journal:  Med Decis Making       Date:  2010-07-29       Impact factor: 2.583

9.  Introducing genetic testing for cardiovascular disease in primary care: a qualitative study.

Authors:  Jo B Middlemass; Momina F Yazdani; Joe Kai; Penelope J Standen; Nadeem Qureshi
Journal:  Br J Gen Pract       Date:  2014-05       Impact factor: 5.386

Review 10.  Being more realistic about the public health impact of genomic medicine.

Authors:  Wayne D Hall; Rebecca Mathews; Katherine I Morley
Journal:  PLoS Med       Date:  2010-10-12       Impact factor: 11.069

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