Susceptibility to Misinformation about COVID-19 Vaccines: A Signal Detection Analysis

TL;DR

This study uses Signal Detection Theory to analyze why individuals accept COVID-19 vaccine misinformation, highlighting the roles of truth insensitivity, belief bias, and cognitive factors in susceptibility.

Contribution

It introduces a novel application of Signal Detection Theory to understand cognitive biases influencing misinformation acceptance about COVID-19 vaccines.

Findings

Truth insensitivity varies with prior vaccine attitudes.

Participants show a strong belief bias towards attitude-congruent info.

Belief bias is a stronger predictor of misinformation acceptance than truth insensitivity.

Abstract

An analysis drawing on Signal Detection Theory suggests that people may fall for misinformation because they are unable to discern true from false information (truth insensitivity) or because they tend to accept information with a particular slant regardless of whether it is true or false (belief bias). Three preregistered experiments with participants from the United States and the United Kingdom (N = 961) revealed that (i) truth insensitivity in responses to (mis)information about COVID-19 vaccines differed as a function of prior attitudes toward COVID-19 vaccines; (ii) participants exhibited a strong belief bias favoring attitude-congruent information; (iii) truth insensitivity and belief bias jointly predicted acceptance of false information about COVID-19 vaccines, but belief bias was a much stronger predictor; (iv) cognitive elaboration increased truth sensitivity without reducing belief bias; and (v) higher levels of confidence in one's beliefs were associated with greater belief bias. The findings provide insights into why people fall for misinformation, which is essential for individual-level interventions to reduce susceptibility to misinformation.