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The University of Southampton
Centre for Risk Research

Cancer Research UK interested in utilising Centre's research findings

Published: 25 April 2014

Cancer Research UK have recently expressed an interest in utilising the findings from one of the Centre for Risk Research's latest studies which identifies how to help people better understand certain cancer risks.

The study, which was conducted by Dr Ian Dawson, Professor Johnnie Johnson and Dr Michelle Luke, identified a method that significantly improves the extent to which people understand that the risk of developing certain cancers (e.g., oesophageal cancer) is multiplied when specific risk factors (e.g., smoking and drinking) are combined. Lizzie Shoda, from the Cancer Research UK Policy Team, recently became aware of these findings and explained that the charity are always interested in identifying ways to improve how they communicate cancer risk. Lizzie Shoda said that she the Policy Team have shared the findings with their Health Information Team to help inform their future work.

The UK's largest cancer charity

Dr Ian Dawson, the Centre's Coordinator, said "At the Centre for Risk Research we are always keen to ensure that our research has a positive impact on people's understanding of risk. We are delighted that Cancer Research UK has shown an interest in utilising our research findings and hope that they can be used to help people to better understand certain cancer risks and, therefore, to make more informed choices."

The communication method identified by the Centre's staff involves the combined use of two types of visual diagrams: one that shows what happens inside the body when two harmful substances are consumed, and one that illustrates how the statistical probability of developing cancer increases for people who regularly consume the two substances. The research findings have recently been published in Risk Analysis: An International Journal in a paper entitled "Helping individuals to understand synergistic risks: an assessment of message contents depicting mechanistic and probabilistic concepts".

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