COVID-19 myth-busting: an experimental study

Abstract

BackgroundCOVID-19 misinformation is a danger to public health. A range of formats are used by health campaigns to correct beliefs but data on their effectiveness is limited. We aimed to identify A) whether three commonly used myth-busting formats are effective for COVID-19 myths, immediately and after a delay, and B) which is the most effective.MethodsWe tested whether three common correction formats could reduce beliefs in COVID-19 myths: (i) question-answer, ii) fact-only, (ii) fact-myth. n = 2215 participants (n=1291 after attrition), UK representative of age and gender, were randomly assigned to one of the three formats. n = 11 myths were acquired from fact-checker websites and piloted to ensure believability. Participants rated myth belief at baseline, were shown correction images (the intervention), and then rated myth beliefs immediately post-intervention and after a delay of at least 6 days. A partial replication, n = 2084 UK representative, was also completed with immediate myth rating only. Analysis used mixed models with participants and myths as random effects.ResultsMyth agreement ratings were significantly lower than baseline for all correction formats, both immediately and after the delay; all β’s > 0.30, p’s < .001. Thus all formats were effective at lowering beliefs in COVID-19 misinformation.Correction formats only differed where baseline myth agreement was high, with question-answer and fact-myth more effective than fact-only immediately; β=0.040, p=.022 (replication set: β = 0.053, p = .0075) and β = -0.051, p = .0059 (replication set: β=-0.061, p < .001), respectively. After the delay however, question-answer was more effective than fact-myth, β = 0.040, p =. 031, and fact-only marginally so, β = .025, p = 0.10.ConclusionOur results imply that COVID-19 myths can be effectively corrected using materials and formats typical of health campaigns. Campaign designers can use our results to choose between correction formats. When myth belief was high, question-answer format, in which the reader is invited to consider whether a myth is true, had a more lasting effect than a traditional fact-myth format.

Using dialogues to increase positive attitudes towards Covid-19 vaccines in a vaccine-hesitant UK population

“…Furthermore, not only are our percentage changes very similar to Altay's chatbot condition effects, who were recruited from the general population and not specifically against vaccination, but also much greater than those in previous studies, for example when influenced by norms, participants only showed a 5% decline in rating themselves as 'undecided' or 'against' vaccination (Moehring et al, 2021), whereas we found a 16% decline. Previous research also suggests that using Q&A style information is more effective than presenting pure fact-based information, again reporting similar effects to ours (Challenger et al, 2021).…”

“…Brand, Department of Psychology, University of Sheffield, Sheffield, S1 1HD. E-mail: c.brand@sheffield.ac.uk al., 2021), presenting information on the timeline of vaccine development (Thorpe et al, 2021), different styles of mythbusting (Challenger, Sumner, & Bott, 2021), the use of social norms (Moehring et al, 2021), framing messaging in terms of individual risk preferences (Trueblood, Sussman, & O'Leary, 2020) and even chatbots (Altay, Hacquin, Chevallier, & Mercier, 2021), all with varying levels of success.…”

Using dialogues to increase positive attitudes towards COVID-19 vaccines in a vaccine-hesitant UK population

“…Furthermore, not only are our percentage changes very similar to Altay et al's chatbot condition effects, who were recruited from the general population and not specifically against vaccination, but also much greater than those in previous studies, for example when influenced by norms, participants only showed a 5% decline in rating themselves as 'undecided' or 'against' vaccination [4], whereas we found a 16% decline. Previous research also suggests that using question and answer (Q&A) style information is more effective than presenting pure fact-based information, again reporting similar effects to ours [3].…”

“…Appropriately, huge amounts of attention and research effort have been directed towards how to increase COVID-19 vaccination uptake. Owing to the urgency and impact of the problem, a multi-pronged attack is warranted, and thus research rightly spans many different strategies, from pre-empting misinformation on social media [ 1 ], presenting information on the comparison of COVID-19 symptoms to vaccination side-effects [ 2 ], presenting information on the timeline of vaccine development [ 2 ], different styles of myth-busting [ 3 ], the use of social norms [ 4 ], framing messaging in terms of individual risk preferences [ 5 ], and even chatbots [ 6 ], all with varying levels of success.…”