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Interpretation of Melanoma Risk Feedback in First-degree Relatives of Melanoma Patients

Overview
Publisher Wiley
Specialty Oncology
Date 2012 Aug 14
PMID 22888347
Citations 2
Authors
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Abstract

Little is known about how individuals might interpret brief genetic risk feedback. We examined interpretation and behavioral intentions (sun protection, skin screening) in melanoma first-degree relatives (FDRs) after exposure to brief prototypic melanoma risk feedback. Using a 3 by 2 experimental pre-post design where feedback type (high-risk mutation, gene environment, and nongenetic) and risk level (positive versus negative findings) were systematically varied, 139 melanoma FDRs were randomized to receive one of the six scenarios. All scenarios included an explicit reminder that melanoma family history increased their risk regardless of their feedback. The findings indicate main effects by risk level but not feedback type; positive findings led to heightened anticipated melanoma risk perceptions and anticipated behavioral intentions. Yet those who received negative findings often discounted their family melanoma history. As such, 25%, 30%, and 32% of those who received negative mutation, gene-environment, and nongenetic feedback, respectively, reported that their risk was similar to the general population. Given the frequency with which those who pursue genetic testing may receive negative feedback, attention is needed to identify ideal strategies to present negative genetic findings in contexts such as direct to consumer channels where extensive genetic counseling is not required.

Citing Articles

Genetic Testing Awareness and Attitudes among Latinos: Exploring Shared Perceptions and Gender-Based Differences.

Hamilton J, Shuk E, Arniella G, Javier Gonzalez C, Gold G, Gany F Public Health Genomics. 2015; 19(1):34-46.

PMID: 26555145 PMC: 4706768. DOI: 10.1159/000441552.


Family risk discussions after feedback on genetic risk of melanoma.

Hay J, Gordon M, Li Y JAMA Dermatol. 2014; 151(3):342-3.

PMID: 25337828 PMC: 5499670. DOI: 10.1001/jamadermatol.2014.3421.

References
1.
Zeger S, Liang K . Longitudinal data analysis for discrete and continuous outcomes. Biometrics. 1986; 42(1):121-30. View

2.
Cameron L, Sherman K, Marteau T, Brown P . Impact of genetic risk information and type of disease on perceived risk, anticipated affect, and expected consequences of genetic tests. Health Psychol. 2009; 28(3):307-16. DOI: 10.1037/a0013947. View

3.
Raimondi S, Sera F, Gandini S, Iodice S, Caini S, Maisonneuve P . MC1R variants, melanoma and red hair color phenotype: a meta-analysis. Int J Cancer. 2008; 122(12):2753-60. DOI: 10.1002/ijc.23396. View

4.
Geransar R, Einsiedel E . Evaluating online direct-to-consumer marketing of genetic tests: informed choices or buyers beware?. Genet Test. 2008; 12(1):13-23. DOI: 10.1089/gte.2007.0024. View

5.
McBride C, Emmons K, Lipkus I . Understanding the potential of teachable moments: the case of smoking cessation. Health Educ Res. 2003; 18(2):156-70. DOI: 10.1093/her/18.2.156. View