DDRIG in DRMS: Lay Understanding of Vaccine Efficacy

Efficacy rates for COVID-19 vaccines have received major attention in scientific journal articles and news media outlets. Further, many sources emphasize the high efficacy rates for the three vaccines with FDA or FDA EUA status in the United States. For example, the mRNA-based Pfizer-BioNTech vaccine boasts an efficacy rate of 95% against the original strain of the COVID-19 virus, meaning that over the duration of a 3-month period in which 1% of the population without the vaccine contracted COVID-19, we could expect about 0.05% of vaccinated people to contract COVID-19 (95% lower). However, many lay people may not understand how vaccine efficacy rates are computed, and the 95% efficacy rate could be misunderstood to mean that 95% of vaccinated people will be protected from disease, implying that 5% of vaccinated people will become diseased with COVID-19. This project examines how lay people (such as patients) use health-related numerical information, sheds light on the basic cognitive processes underlying misuse of vaccine efficacy numbers and speaks to the broader question of how to present numerical health information in a way that lay people can understand and effectively use. The research identifies the degree to which different facets of cognitive processing (e.g., knowing how to use the mathematical formula, understanding the concept of relative risk reduction, and engaging in deliberation or comparison processes) act as facilitators to providing the normative response. Findings from the proposed research have the potential to foster informed medical decision making and patient agency. Understanding how lay people understand vaccine efficacy is highly relevant during the COVID-19 pandemic when conversations about vaccine efficacy receive increased attention and interest from patients. Given the strong association between perceived vaccine efficacy and vaccination intention, it is critical to identify and correct misconceptions in patients' understanding of vaccine efficacy statistics.

The COVID-19 pandemic prompted widespread discussion of efficacy rates for COVID-19 vaccines in scientific journal articles and news media outlets, but little is known about how well lay people understand vaccine efficacy, which entails a fairly sophisticated mathematical calculation. This research tests the prediction that lay people are lured by a plausible and computationally simple but incorrect calculation: post-vaccination risk of infection = 1 - efficacy. For example, the lure response would be that after receiving a 95% effective vaccine a person has a 5% risk of getting infected. Previous medical decision-making research demonstrates that patients, especially those low in numeracy, often have difficulty understanding numerical information, which has a consequential impact on their health decisions and health outcomes. Moreover, prior cognition research provides evidence of quick, intuitive responses that may be analogous to the lure response in the vaccine efficacy context. This series of studies investigates the extent to which laypeople improperly interpret efficacy and whether this misunderstanding is associated with individual characteristics such as numeracy, cognitive reflection, and scientific literacy. First, hypothetical scenario experiments are employed to better understand how lay people utilize information about vaccine efficacy. Scenarios that vary information about fictitious vaccines illuminate the extent to which lay people improperly understand efficacy (for example, by answering that a vaccine that is 95% effective means that 5% of vaccinated people will get infected). Additional studies test a tutorial designed to improve viewers' conceptual understanding of vaccine efficacy. Two versions of the tutorial differ in their emphasis on the mathematical formula vs. the concept of relative risk reduction, enabling a test of which of these facets is the major barrier to normative responses. Final studies examine a debiasing method that prompts participants to make an implicit comparison of disease risk between untreated and treated groups, testing the hypothesis that misunderstandings about vaccine efficacy stem from a failure to consider a comparison between a placebo group and a vaccinated group.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.