Math Matters: A Novel, Brief Educational Intervention Decreases Whole Number Bias When Reasoning About COVID-19

• Published in: Journal of experimental psychology. Applied 2021-12, Vol.27 (4), p.632-656
• Main Authors: Thompson, Clarissa A., Taber, Jennifer M., Sidney, Pooja G., Fitzsimmons, Charles J., Mielicki, Marta K., Matthews, Percival G., Schemmel, Erika A., Simonovic, Nicolle, Foust, Jeremy L., Aurora, Pallavi, Disabato, David J., Seah, T. H. Stanley, Schiller, Lauren K., Coifman, Karin G.
• Format: Article
• Language: English
• Subjects: Adult; Bias; Brief Interventions; COVID-19; Female; Health; Human; Humans; Intervention; Learning; Male; Mathematics; Number Comprehension; Pandemics; Reasoning; SARS-CoV-2; School Based Intervention
• ISSN: 1076-898X; 1939-2192
• DOI: 10.1037/xap0000403

At the onset of the coronavirus disease (COVID-19) global pandemic, our interdisciplinary team hypothesized that a mathematical misconception-whole number bias (WNB)-contributed to beliefs that COVID-19 was less fatal than the flu. We created a brief online educational intervention for adults, leveraging evidence-based cognitive science research, to promote accurate understanding of rational numbers related to COVID-19. Participants from a Qualtrics panel (N = 1,297; 75% White) were randomly assigned to an intervention or control condition, solved health-related math problems, and subsequently completed 10 days of daily diaries in which health cognitions and affect were assessed. Participants who engaged with the intervention, relative to those in the control condition, were more accurate and less likely to explicitly mention WNB errors in their strategy reports as they solved COVID-19-related math problems. Math anxiety was positively associated with risk perceptions, worry, and negative affect immediately after the intervention and across the daily diaries. These results extend the benefits of worked examples in a practically relevant domain. Ameliorating WNB errors could not only help people think more accurately about COVID-19 statistics expressed as rational numbers, but also about novel future health crises, or any other context that involves information expressed as rational numbers. Public Significance Statement In late March 2020 at the beginning of the coronavirus disease (COVID-19) pandemic, we conducted a randomized controlled trial in which a large panel of U.S. adults (N = 1,297) was randomly assigned to either an educational intervention or a control condition. Those in the educational intervention learned how to accurately compare case-fatality rates for the flu versus COVID-19 by engaging with a brief, online tutorial, which taught them step-by-step how to divide the number of deaths by the number of cases and then compare to find the most fatal virus. The training decreased the likelihood that people mistakenly focused just on the number of deaths, which would have led them to the mistaken conclusion that the flu was more fatal than COVID-19.