Transparent communication of evidence does not undermine public trust in evidence.

Does clear and transparent communication of risks, benefits, and uncertainties increase or undermine public trust in scientific information that people use to guide their decision-making? We examined the impact of reframing messages written in traditional persuasive style to align instead with recent "evidence communication" principles, aiming to inform decision-making: communicating a balance of risks and benefits, disclosing uncertainties and evidence quality, and prebunking misperceptions. In two pre-registered experiments, UK participants read either a persuasive message or a balanced and informative message adhering to evidence communication recommendations about COVID-19 vaccines (Study 1) or nuclear power plants (Study 2). We find that balanced messages are either perceived as trustworthy as persuasive messages (Study 1), or more so (Study 2). However, we note a moderating role of prior beliefs such that balanced messages were consistently perceived as more trustworthy among those with negative or neutral prior beliefs about the message content. We furthermore note that participants who had read the persuasive message on nuclear power plants voiced significantly stronger support for nuclear power than those who had read the balanced message, despite rating the information as less trustworthy. There was no difference in vaccination intentions between groups reading the different vaccine messages.

COVID-19 risk perception and hoax beliefs in the US immediately before and after the announcement of President Trump's diagnosis.

A notable challenge of the SARS-CoV-2 pandemic has been public scepticism over the severity of the disease, or even its existence. Such scepticism is politically skewed in the USA, with conservatives more likely to downplay or deny the risks of the virus. However, the hospitalization of President Trump with COVID-19 in October 2020 served as a high-profile exemplar of the reality and risks of the virus, and as such may have influenced opinions, particularly for US conservatives. We investigate whether President Trump testing positive was associated with changes in public attitudes towards the virus. In two studies, we surveyed independent representative US samples before and after the announcement of Trump's illness. In Study 1, measuring risk perceptions of the virus, we find that participants surveyed before and after the announcement did not differ in their risk perception regardless of political orientation. In Study 2, measuring belief that the virus is a hoax, we find that among those on the far right of the political spectrum, hoax belief was lower for those surveyed after the announcement, suggesting that Trump's hospitalization may have affected the beliefs of those most receptive to the President's earlier suggestions that the virus might be a hoax.

The effects of quality of evidence communication on perception of public health information about COVID-19: Two randomised controlled trials.

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, d = 0.25), and rated it as subjectively less effective (p = .018, d = 0.19). 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, d = 0.18). Participants who were told the quality of the evidence was 'high' showed no statistically significant differences on these measures compared to those given no information about evidence quality. CONCLUSIONS: 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.

Correlates of intended COVID-19 vaccine acceptance across time and countries: results from a series of cross-sectional surveys.

OBJECTIVE: Describe demographical, social and psychological correlates of willingness to receive a COVID-19 vaccine. SETTING: Series of online surveys undertaken between March and October 2020. PARTICIPANTS: A total of 25 separate national samples (matched to country population by age and sex) in 12 different countries were recruited through online panel providers (n=25 334). PRIMARY OUTCOME MEASURES: Reported willingness to receive a COVID-19 vaccination. RESULTS: Reported willingness to receive a vaccine varied widely across samples, ranging from 63% to 88%. Multivariate logistic regression analyses reveal sex (female OR=0.59, 95% CI 0.55 to 0.64), trust in medical and scientific experts (OR=1.28, 95% CI 1.22 to 1.34) and worry about the COVID-19 virus (OR=1.47, 95% CI 1.41 to 1.53) as the strongest correlates of stated vaccine acceptance considering pooled data and the most consistent correlates across countries. In a subset of UK samples, we show that these effects are robust after controlling for attitudes towards vaccination in general. CONCLUSIONS: 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 maximise uptake.

How do the UK public interpret COVID-19 test results? Comparing the impact of official information about results and reliability used in the UK, USA and New Zealand: a randomised controlled trial.

OBJECTIVES: To assess the effects of different official information on public interpretation of a personal COVID-19 PCR test result. DESIGN: A 5×2 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. SETTING: Online experiment using recruitment platform Respondi. PARTICIPANTS: UK participants (n=1744, after a pilot of n=1657) quota-sampled to be proportional to the UK national population on age and sex. INTERVENTIONS: Participants were given a hypothetical COVID-19 PCR 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 in September 2020 from the public websites of the UK's National Health Service, the USA's Centers for Disease Control, New Zealand's Ministry of Health or a modified version of the UK's wording. Information identifying the source of the wording was removed. MAIN OUTCOME MEASURES: Participants 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. RESULTS: Of those presented with a positive COVID-19 test result for 'John', the mean estimate of the probability that he had the virus was 73% (71.5%-74.5%); for those presented with a negative result, 38% (36.7%-40.0%). There was no main effect of information (wording) on these means. However, those participants given the official information from the UK website, which did not mention the possibility of false negatives or false positives, were more likely to give a categorical (100% or 0%) answer (UK: 68/343, 19.8% (15.9%-24.4%); control group: 42/356, 11.8% (8.8%-15.6%)); the reverse was true for those viewing the New Zealand (NZ) wording, which highlighted the uncertainties most explicitly (20/345: 5.8% (3.7%-8.8%)). Aggregated across test result (positive/negative), there was a main effect of wording (p<0.001) on beliefs about how 'John' should behave, with those seeing the NZ wording marginally more likely to agree that 'John' should continue to self-isolate than those viewing the control or the UK wording. The proportion of participants who felt that a symptomatic individual who tests negative definitely should not self-isolate was highest among those viewing the UK wording (31/178, 17.4% (12.5%-23.7%)), and lowest among those viewing the NZ wording (6/159, 3.8% (1.6%-8.2%)). Although the NZ wording was rated harder to understand, participants reacted to the uncertainties given in the text in the expected direction: there was a small main effect of wording on trust in the result (p=0.048), with people perceiving the test result as marginally less trustworthy after having read the NZ wording compared with the UK wording. Positive results were generally viewed as more trustworthy and as having higher quality of evidence than negative results (both p<0.001). CONCLUSIONS: The public's default assessment of the face value of both the positive and negative test results (control group) indicate an awareness that test results are not perfectly accurate. Compared with other messaging tested, participants shown the UK's 2020 wording about the interpretation of the test results appeared to interpret the results as more definitive than is warranted. Wording that acknowledges uncertainty can help people to have a more nuanced and realistic understanding of what a COVID-19 test result means, which supports decision making and behavioural response. PREREGISTRATION AND DATA REPOSITORY: Preregistration of pilot at osf.io/8n62f, preregistration of main experiment at osf.io/7rcj4, data and code available online (osf.io/pvhba).

Communicating personalized risks from COVID-19: guidelines from an empirical study.

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 personalized 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 = 5520, 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. We note that observed effect sizes generally were small. However, even small effects are meaningful and relevant when scaled up to population levels.

Susceptibility to misinformation about COVID-19 around the world.

Misinformation about COVID-19 is a major threat to public health. Using five national samples from the UK (n = 1050 and n = 1150), Ireland (n = 700), the USA (n = 700), Spain (n = 700) and Mexico (n = 700), we examine predictors of belief in the most common statements about the virus that contain misinformation. We also investigate the prevalence of belief in COVID-19 misinformation across different countries and the role of belief in such misinformation in predicting relevant health behaviours. We find that while public belief in misinformation about COVID-19 is not particularly common, a substantial proportion views this type of misinformation as highly reliable in each country surveyed. In addition, a small group of participants find common factual information about the virus highly unreliable. We also find that increased susceptibility to misinformation negatively affects people's self-reported compliance with public health guidance about COVID-19, as well as people's willingness to get vaccinated against the virus and to recommend the vaccine to vulnerable friends and family. Across all countries surveyed, we find that higher trust in scientists and having higher numeracy skills were associated with lower susceptibility to coronavirus-related misinformation. Taken together, these results demonstrate a clear link between susceptibility to misinformation and both vaccine hesitancy and a reduced likelihood to comply with health guidance measures, and suggest that interventions which aim to improve critical thinking and trust in science may be a promising avenue for future research.