Résumé
This review provides an overview of concepts relating to the communication of statistical and empirical evidence in times of crisis, with a special focus on COVID-19. In it, we consider topics relating both to the communication of numbers -- such as the role of format, context, comparisons, and visualization -- and the communication of evidence more broadly -- such as evidence quality, the influence of changes in available evidence, transparency, and repeated decision making. A central focus is on the communication of the inherent uncertainties in statistical analysis, especially in rapidly changing informational environments during crises. We present relevant literature on these topics and draw connections to the communication of statistics and empirical evidence during the COVID-19 pandemic and beyond. We finish by suggesting some considerations for those faced with communicating statistics and evidence in times of crisis.
Sujets)
COVID-19Résumé
Background: The quality of evidence about the effectiveness of non-pharmaceutical health interventions is often low, but little is known about the effects of communicating indications of evidence quality to the public. Methods: In two blinded, randomised, controlled, online experiments, US participants (total n=2140) were shown one of several versions of an infographic illustrating the effectiveness of eye protection in reducing COVID-19 transmission. Their trust in the information, understanding, feelings of effectiveness of eye protection, and the likelihood of them adopting it were measured. Findings: Compared to those given no quality cues, participants who were told the quality of the evidence on eye protection was "low", rated the evidence less trustworthy (p=.001), and rated it as subjectively less effective (p=.020). The same effects emerged compared to those who were told the quality of the evidence was "high", and in one of the two studies, those shown "low" quality of evidence said they were less likely to use eye protection (p=.005). Participants who were told the quality of the evidence was "high" showed no significant differences on these measures compared to those given no information about evidence quality. Interpretation: Without quality of evidence cues, participants responded to the evidence about the public health intervention as if it was high quality and this affected their subjective perceptions of its efficacy and trust in the provided information. This raises the ethical dilemma of weighing the importance of transparently stating when the evidence base is actually low quality against evidence that providing such information can decrease trust, perception of intervention efficacy, and likelihood of adopting it.
Sujets)
COVID-19Résumé
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.
Sujets)
COVID-19Résumé
ObjectivesTo assess the effects of different official information on public interpretation of a personal COVID-19 PCR ( swab) test result. DesignA 5xx2 factorial, randomised, between-subjects experiment, comparing four wordings of information about the test result and a control arm of no additional information; for both positive and negative test results. SettingOnline experiment using recruitment platform Respondi. ParticipantsUK participants (n=1,744, after a pilot of n=1,657) collected by quota sampling to be proportional to the UK national population on age and sex. InterventionsParticipants were given a hypothetical COVID-19 swab test result for John who was presented as having a 50% chance of having COVID-19 based on symptoms alone. Participants were randomised to receive either a positive or negative result for John, then randomised again to receive either no more information, or text information on the interpretation of COVID-19 test results copied from the public websites of the UKs National Health Service, the USs Centers for Disease Control, New Zealands Ministry of Health, or a modified version of the UKs wording incorporating uncertainty. Information identifying the source of the wording was removed. Main outcome measuresParticipants were asked "What is your best guess as to the percent chance that John actually had COVID-19 at the time of his test, given his result?"; questions about their feelings of trustworthiness in the result, their perceptions of the quality of the underlying evidence, and what action they felt John should take in the light of his result. ResultsOf those presented with a positive COVID-19 test result for John, the mean estimate of the probability that he had the virus was 73%; for those presented with a negative result, 38%. There was no main effect of information (wording) on these means. However, those participants given the official information on the UK website, which did not mention any uncertainty around the test result, were significantly more likely to give a categorical (100% or 0%) answer (for positive result, p