Literature DB >> 22149122

What do men understand about lifetime risk following genetic testing? The effect of context and numeracy.

Jonathan J Rolison1, Yaniv Hanoch, Talya Miron-Shatz.   

Abstract

OBJECTIVE: Genetic testing for gene mutations associated with specific cancers provides an opportunity for early detection, surveillance, and intervention (Smith, Cokkinides, & Brawley, 2008). Lifetime risk estimates provided by genetic testing refer to the risk of developing a specific disease within one's lifetime, and evidence suggests that this is important for the medical choices people make, as well as their future family and financial plans. The present studies tested whether adult men understand the lifetime risks of prostate cancer informed by genetic testing.
METHOD: In 2 experiments, adult men were asked to interpret the lifetime risk information provided in statements about risks of prostate cancer. Statement format was manipulated such that the most appropriate interpretation of risk statements referred to an absolute risk of cancer in experiment 1 and a relative risk in experiment 2.
RESULTS: Experiment 1 revealed that few men correctly interpreted the lifetime risks of cancer when these refer to an absolute risk of cancer, and numeracy levels positively predicted correct responding. The proportion of correct responses was greatly improved in experiment 2 when the most appropriate interpretation of risk statements referred instead to a relative rather than an absolute risk, and numeracy levels were less involved.
CONCLUSION: Understanding of lifetime risk information is often poor because individuals incorrectly believe that these refer to relative rather than absolute risks of cancer.

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Mesh:

Year:  2011        PMID: 22149122     DOI: 10.1037/a0026562

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


  7 in total

Review 1.  Big Data in Science and Healthcare: A Review of Recent Literature and Perspectives. Contribution of the IMIA Social Media Working Group.

Authors:  M M Hansen; T Miron-Shatz; A Y S Lau; C Paton
Journal:  Yearb Med Inform       Date:  2014-08-15

2.  Prevalence and correlates of receiving and sharing high-penetrance cancer genetic test results: findings from the Health Information National Trends Survey.

Authors:  Jennifer M Taber; Christine Q Chang; Tram K Lam; Elizabeth M Gillanders; Jada G Hamilton; Sheri D Schully
Journal:  Public Health Genomics       Date:  2015       Impact factor: 2.000

3.  Communicating Numerical Risk: Human Factors That Aid Understanding in Health Care.

Authors:  Priscila G Brust-Renck; Caisa E Royer; Valerie F Reyna
Journal:  Rev Hum Factors Ergon       Date:  2013-10

4.  Understanding Health Risk Comprehension: The Role of Math Anxiety, Subjective Numeracy, and Objective Numeracy.

Authors:  Jonathan J Rolison; Kinga Morsanyi; Ellen Peters
Journal:  Med Decis Making       Date:  2020-02-13       Impact factor: 2.583

Review 5.  Presenting quantitative information about decision outcomes: a risk communication primer for patient decision aid developers.

Authors:  Lyndal J Trevena; Brian J Zikmund-Fisher; Adrian Edwards; Wolfgang Gaissmaier; Mirta Galesic; Paul K J Han; John King; Margaret L Lawson; Suzanne K Linder; Isaac Lipkus; Elissa Ozanne; Ellen Peters; Danielle Timmermans; Steven Woloshin
Journal:  BMC Med Inform Decis Mak       Date:  2013-11-29       Impact factor: 2.796

6.  mHealth 2.0: Experiences, Possibilities, and Perspectives.

Authors:  Stefan Becker; Talya Miron-Shatz; Nikolaus Schumacher; Johann Krocza; Clarissa Diamantidis; Urs-Vito Albrecht
Journal:  JMIR Mhealth Uhealth       Date:  2014-05-16       Impact factor: 4.773

7.  Knowledge and risk perceptions of the Ebola virus in the United States.

Authors:  Jonathan J Rolison; Yaniv Hanoch
Journal:  Prev Med Rep       Date:  2015-04-16
  7 in total

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