Literature DB >> 16162383

Self-regulation and the behavioural response to DNA risk information: a theoretical analysis and framework for future research.

Theresa M Marteau1, John Weinman.   

Abstract

The few studies conducted to date suggest that DNA risk information may be less likely to achieve behaviour change than other types of health risk information. We draw upon self-regulation theory to explain and predict the characteristics of risk information that are more and less likely to motivate behaviour change. Self-regulation theory describes how information about a health threat is processed within individuals' pre-existing cognitive schema, and how the cognitive representations within these schemas activate coping procedures for dealing with the perceived threat. We explore the proposition that the initial impact of information about a health threat depends upon how well it "fits" with existing cognitive representations of that threat. For example, in one study DNA risk information regarding an inherited form of bowel cancer was perceived as more accurate and had a greater impact on risk perceptions in those whose representation of the threat included genes as the single cause, as opposed to one of several. Since the cognitive representation of a threat activates coping procedures that fit with that representation, we also explore the proposition that cognitive representations of a threat that has a genetic identity are less likely to activate coping procedures that include risk-reducing behaviours. For example, using DNA risk information to assess an inherited predisposition to heart disease increased the extent to which the condition was seen as caused by genes, which in turn reduced the expectation that a behavioural means of coping would be effective (eating a low fat diet), but increased the expectation that a biological means was effective (taking lipid lowering medication). Describing the heuristics that operate between risk information, the cognitive representations of threat and coping procedures could be used to identify the cognitions to target so as to optimize the motivational impact of DNA and other risk information.

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Year:  2005        PMID: 16162383     DOI: 10.1016/j.socscimed.2005.08.005

Source DB:  PubMed          Journal:  Soc Sci Med        ISSN: 0277-9536            Impact factor:   4.634


  114 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.  Does Type 2 Diabetes Genetic Testing and Counseling Reduce Modifiable Risk Factors? A Randomized Controlled Trial of Veterans.

Authors:  Corrine I Voils; Cynthia J Coffman; Janet M Grubber; David Edelman; Azita Sadeghpour; Matthew L Maciejewski; Jamiyla Bolton; Alex Cho; Geoffrey S Ginsburg; William S Yancy
Journal:  J Gen Intern Med       Date:  2015-04-16       Impact factor: 5.128

3.  Predictive genetic testing for type 2 diabetes.

Authors:  A Cecile J W Janssens; Marta Gwinn; Rodolfo Valdez; K M Venkat Narayan; Muin J Khoury
Journal:  BMJ       Date:  2006-09-09

4.  A research agenda for assessing the potential contribution of genomic medicine to tobacco control.

Authors:  Wayne D Hall
Journal:  Tob Control       Date:  2007-02       Impact factor: 7.552

5.  Interest and informational preferences regarding genomic testing for modest increases in colorectal cancer risk.

Authors:  A E Anderson; K G Flores; W Boonyasiriwat; A Gammon; W Kohlmann; W C Birmingham; M D Schwartz; J Samadder; K Boucher; A Y Kinney
Journal:  Public Health Genomics       Date:  2014-01-14       Impact factor: 2.000

6.  A randomized trial of the clinical utility of genetic testing for obesity: design and implementation considerations.

Authors:  Catharine Wang; Erynn S Gordon; Catharine B Stack; Ching-Ti Liu; Tricia Norkunas; Lisa Wawak; Michael F Christman; Robert C Green; Deborah J Bowen
Journal:  Clin Trials       Date:  2013-11-11       Impact factor: 2.486

7.  How can psychological science inform research about genetic counseling for clinical genomic sequencing?

Authors:  Cynthia M Khan; Christine Rini; Barbara A Bernhardt; J Scott Roberts; Kurt D Christensen; James P Evans; Kyle B Brothers; Myra I Roche; Jonathan S Berg; Gail E Henderson
Journal:  J Genet Couns       Date:  2014-12-09       Impact factor: 2.537

8.  How Are Information Seeking, Scanning, and Processing Related to Beliefs About the Roles of Genetics and Behavior in Cancer Causation?

Authors:  Erika A Waters; Courtney Wheeler; Jada G Hamilton
Journal:  J Health Commun       Date:  2016-09-23

Review 9.  Public health genomics and genetic test evaluation: the challenge of conducting behavioural research on the utility of lifestyle-genetic tests.

Authors:  Saskia C Sanderson; Jane Wardle; Steve E Humphries
Journal:  J Nutrigenet Nutrigenomics       Date:  2008-08-06

10.  Cancer genetic predisposition: information needs of patients irrespective of risk level.

Authors:  Alison Metcalfe; Julie Werrett; Lucy Burgess; Cyril Chapman; Collette Clifford
Journal:  Fam Cancer       Date:  2009-06-11       Impact factor: 2.375

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