ABSTRACT
A growing body of research indicates that transparent communication of statistical uncertainty around facts and figures does not undermine credibility. However, the extent to which these findings apply in the context of the COVID-19 pandemic--rife with uncertainties--is unclear. In a large international survey experiment, (Study 1; N = 10,519) we report that communicating uncertainty around COVID-19 statistics in the form of a numeric range (vs. no uncertainty) may lead to slightly lower trust in the number presented but has no impact on trust in the source of the information. We also report the minimal impact of numeric uncertainty on trust is consistent across estimates of current or future COVID-19 statistics (Study 2) and figures relating to environmental or economic research, rather than the pandemic (Study 3). Conversely, we find imprecise statements about the mere existence of uncertainty without quantification can undermine both trust in the numbers and their source - though effects vary across countries and contexts. Communicators can be transparent about statistical uncertainty without concerns about undermining perceptions of their trustworthiness, but ideally should aim to use numerical ranges rather than verbal statements.
ABSTRACT
Understanding the drivers of vaccine acceptance is crucial to the success of COVID-19 mass vaccination campaigns. Across 25 national samples from 12 different countries we examined the psychological correlates of willingness to receive a COVID-19 vaccine (total N = 25,334), with a focus on risk perception and trust in a number of relevant actors, both in general and specifically regarding the COVID-19 pandemic. Male sex, trust in medical and scientific experts and worry about the virus emerge as the most consistent predictors of reported vaccine acceptance across countries. In a subset of samples we show that these effects are robust after controlling for attitudes towards vaccination in general. Our results indicate that the burden of trust largely rests on the shoulders of the scientific and medical community, with implications for how future COVID-19 vaccination information should be communicated to maximize uptake.
ABSTRACT
As increasing amounts of data accumulate on the effects of the novel coronavirus Sars-CoV-2 and the risk factors that lead to poor outcomes, it is possible to produce personalised estimates of the risks faced by groups of people with different characteristics. The challenge of how to communicate these then becomes apparent. Based on empirical work (total n=5,520, UK) supported by in-person interviews with the public and physicians, we make recommendations on the presentation of such information. These include: using predominantly percentages when communicating the absolute risk, but also providing, for balance, a format which conveys a contrasting (higher) perception of risk (expected frequency out of 10,000); using a visual linear scale cut at an appropriate point to illustrate the maximum risk, explained through an illustrative persona who might face that highest level of risk; and providing context to the absolute risk through presenting a range of other personas illustrating people who would face risks of a wide range of different levels. These personas should have their major risk factors (age, existing health conditions) described. By contrast, giving people absolute likelihoods of other risks they face in an attempt to add context was considered less helpful.
