Date Published: January 30, 2019
Publisher: Public Library of Science
Author(s): Jessica Paynter, Sarah Luskin-Saxby, Deb Keen, Kathryn Fordyce, Grace Frost, Christine Imms, Scott Miller, David Trembath, Madonna Tucker, Ullrich Ecker, Amanda A. Webster.
Misinformation poses significant challenges to evidence-based practice. In the public health domain specifically, treatment misinformation can lead to opportunity costs or direct harm. Alas, attempts to debunk misinformation have proven sub-optimal, and have even been shown to “backfire”, including increasing misperceptions. Thus, optimized debunking strategies have been developed to more effectively combat misinformation. The aim of this study was to test these strategies in a real-world setting, targeting misinformation about autism interventions. In the context of professional development training, we randomly assigned participants to an “optimized-debunking” or a “treatment-as-usual” training condition and compared support for non-empirically-supported treatments before, after, and six weeks following completion of online training. Results demonstrated greater benefits of optimized debunking immediately after training; thus, the implemented strategies can serve as a general and flexible debunking template. However, the effect was not sustained at follow-up, highlighting the need for further research into strategies for sustained change.
Misinformation can have adverse consequences because misinformation-based decisions carry inherent risk of direct harm or opportunity costs. To illustrate with two public health examples: Some cancer patients choose homeopathic remedies based on misconceptions regarding proposed (but untrue) healing powers, but pay the price with higher rates of disease recurrence and death . Similarly, misinformation-based rejection of vaccinations—especially in the wake of the “vaccine-autism scare” surrounding the mumps-measles-rubella vaccination—has demonstrably contributed to the resurgence of vaccine-preventable diseases . Given the potentially serious implications of misinformation, we need to better understand the processes underlying the perpetuation of misinformation, and how to counter its influence [3–6].
In this study, we designed an optimized-debunking intervention based on recommendations from the cognitive science literature [7, 9], systematically implementing a set of generalizable principles. We trialed this approach in an area that has been highly susceptible to misinformation, namely autism treatment. We demonstrated that an optimized-debunking intervention was more effective than a treatment-as-usual intervention at reducing support for non-empirically-supported treatments. Our approach has potential to serve as a flexible template for both real-world application and future research. Our findings expand significantly previous work in this area, which has used debunking materials created less systematically and/or with fewer elements incorporated. Our research confirmed the positive effects of weight-of-evidence information and graphical representations, while avoiding backfire effects potentially arising from emotive or confrontational debunkings [30, 32].