Math matters during a pandemic: A novel, brief educational intervention combats whole number bias to improve health decision-making and predicts COVID-19 risk perceptions and worry across 10 days
Math matters during a pandemic: A novel, brief educational intervention combats whole number bias to improve health decision-making and predicts COVID-19 risk perceptions and worry across 10 days
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数学在大流行期间很重要:一种新颖、简短的教育干预措施可以消除整数偏差,以改善健康决策,并预测 10 天内的 COVID-19 风险认知和担忧
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发表时间:
2020
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影响因子:
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通讯作者:
Karin G. Coifman
中科院分区:
文献类型:
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作者:
Clarissa A. Thompson;Jennifer M. Taber;P. Sidney;Charles J. Fitzsimmons;Marta K. Mielicki;Percival G. Matthews;Erika Schemmel;N. Simonovic;Jerry L. Foust;P. Aurora;T. H. S. Seah;D. Disabato;Karin G. Coifman
At the onset of the COVID-19 global pandemic, our interdisciplinary team hypothesized that a mathematical misconception--whole number bias (WNB)--contributed to incorrect beliefs that COVID-19 was less fatal than the flu. We created a novel, five-minute online educational intervention, leveraging evidence-based cognitive science research, to encourage accurate COVID-19 and flu fatality rate calculations and comparisons. As predicted, adults (N = 1,297) randomly assigned to the intervention were more likely to correctly answer health decision-making problems and were less likely to report WNB errors in their problem-solving strategies relative to control participants. There were no immediate effects of condition on COVID-19 risk perceptions and worry; however, those in the intervention group did exhibit increased perceived risk and worry across 10 days of daily diaries. The intervention did not cause distress; instead, it increased positive affect. Ameliorating WNB errors could impact people’s risk perceptions about future health crises.