The Effect of Biased Health Information and Consumer Attitudes on Anticipated Whole Genome Screening Uptake. — ASN Events

The Effect of Biased Health Information and Consumer Attitudes on Anticipated Whole Genome Screening Uptake. (#77)

Alana Fisher 1 , Carissa Bonner 1 , Ilona Juraskova 1 , Andrew Biankin 2
  1. School of Psychology, Centre for Medical Psychology & Evidence-based Decision-making (CeMPED), University of Sydney, Sydney, NSW, Australia
  2. Pancreatic Cancer Research, Cancer Program, Garvan Institute of Medical Research, Sydney, NSW, Australia

Aim. Genetic, environmental, and behavioural factors may all contribute to an individual’s risk of developing cancer. Given its mix of hereditable and modifiable risk factors, cancer represents a prime disease candidate for whole genome sequencing screening (WGS). This new generation of DNA testing may not only enable healthy individuals to learn their genetic susceptibility to a range of chronic illnesses, but also prompt risk-reducing behaviour changes. Proponents claim WGS will usher in a new era of personalised and preventative medicine, however, in the interest of informed choice, consumer education is of paramount importance. This study investigated the effect of biased health information on beliefs about, and intention to undergo, WGS; and predictors of intention.
Methods. A single-blind parallel-group randomised trial was conducted in Australia, in 2011. Undergraduate participants (N=216) were randomly allocated a neutral information pamphlet or a biased version omitting screening limitations. Measures included: screening intention; Protection Motivation Theory (PMT) constructs; consideration of future consequences (CFC); uncertainty avoidance (UA); anticipated regret (AR).
Results. Intention decreased from pre to post-manipulation (p<.001, η²=.07, 95% CIs [4.41, 4.86], [3.99, 4.44], respectively). Biased participants (n=106) had higher response efficacy beliefs than neutral participants (n=102) (p<.001, η²=.04, 95% CIs [4.80, 5.10], [4.49, 4.79] respectively), but equal intention. The model explained 36.2% of the variance in intention; response efficacy (p<.001), response costs (p<.001), self-efficacy (p=.024), and UA (p=.019) were predictors.
Conclusion. This is the first study to use a psychosocial model to examine the belief-based predictors of, and the effects of biased information on anticipated WGS screening uptake. Omitting screening limitations may bias beliefs about screening efficacy and benefits. Uptake may be driven by perceived benefits and costs, self-efficacy beliefs, and uncertainty avoidance. PMT appears to be an appropriate psychosocial model for this setting; its components may be used to tailor future educational interventions in specific cancer settings.