What statistics are most likely to promote positive actions during a pandemic?
A new study from PIK Professor Dolores Albarracín and research associate Haesung Annie Jung finds that some COVID statistics are more effective than others at encouraging people to change their behavior.
Throughout the COVID-19 pandemic, health officials updated the public on the outbreak through statistics—case counts, vaccination rates, test distribution. Whether displayed through graphs, charts, or interactive visualizations, these numbers are meant to help the public make decisions in response to health risks.
But do these statistics actually change individuals’ perceptions of risk and behavioral decisions? A new study from researchers at the Annenberg School for Communication finds that they do, but some more than others.
The researchers—Dolores Albarracín, the Alexandra Heyman Nash University Professor, with joint appointments in the Annenberg School for Communication, the Department of Family and Community Health at the Penn School of Nursing, and the Psychology Department, and Haesung Annie Jung, a research associate at Albarracín’s Social Action Lab—began their study in summer 2020, when COVID-19 was the third leading cause of death in the U.S.
They two aimed to find which statistics are the most effective at encouraging individuals to change their behavior—avoid large gatherings, wear a mask daily, isolate when sick, and vaccinate—to reduce their risk for disease. They conducted experiments to analyze the impact of two of the most frequently shared epidemiological metrics of worldwide disease: first, the number of new infections and second, the total number of infections.
Their findings show information about new infections consistently has a larger influence on people’s decisions to change their behavior than information about the total number of infections (disease prevalence). The impact of prevalence, however, becomes larger when there is no noticeable change in the number of new infections, such that this number is consistently growing or decreasing.
“These two metrics are related, but distinctly important.” Jung says. The number of new infections signal immediate changes in disease threat. It tells you whether your likelihood of contracting a disease has increased or decreased compared to yesterday, for example. In contrast, the number of total infections signals how common a disease is in a region. This second piece of information is critical in determining how much risk you have if you walk outside without a mask today.”
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