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This survey study measures how opinions on trusting government and misconceptions about the COVID-19 vaccine are associated with vaccine hesitancy in the Netherlands.

Abstract
Understanding how vaccine hesitancy relates to online behavior is crucial for addressing current and future disease outbreaks. We combined survey data measuring attitudes toward the COVID-19 vaccine with Twitter data in two studies (N1 = 464 Twitter users, N2 = 1,600 Twitter users) with preregistered hypotheses to examine how real-world social media behavior is associated with vaccine hesitancy in the United States (US) and the United Kingdom (UK). In Study 1, we found that following the accounts of US Republican politicians or hyper-partisan/low-quality news sites were associated with lower confidence in the COVID-19 vaccine—even when controlling for key demographics such as self-reported political ideology and education. US right-wing influencers (e.g. Candace Owens, Tucker Carlson) had followers with the lowest confidence in the vaccine. Network analysis revealed that participants who were low and high in vaccine confidence separated into two distinct communities (or "echo chambers"), and centrality in the more right-wing community was associated with vaccine hesitancy in the US, but not in the UK. In Study 2, we found that one's likelihood of not getting the vaccine was associated with retweeting and favoriting low-quality news websites on Twitter. Altogether, we show that vaccine hesitancy is associated with following, sharing, and interacting with low-quality information online, as well as centrality within a conservative-leaning online community in the US. These results illustrate the potential challenges of encouraging vaccine uptake in a polarized social media environment.

AbstractMis- and disinformation pose substantial societal challenges, and have thus become the focus of a substantive field of research. However, the field of misinformation research has recently come under scrutiny on two fronts. First, a political response has emerged, claiming that misinformation research aims to censor conservative voices. Second, some scholars have questioned the utility of misinformation research altogether, arguing that misinformation is not sufficiently identifiable or widespread to warrant much concern or action. Here, we rebut these claims. We contend that the spread of misinformation—and in particular willful disinformation—is demonstrably harmful to public health, evidence-informed policymaking, and democratic processes. We also show that disinformation and outright lies can often be identified and differ from good-faith political contestation. We conclude by showing how misinformation and disinformation can be at least partially mitigated using a variety of empirically validated, rights-preserving methods that do not involve censorship.

Abstract
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.

The World Health Organization has declared the rapid spread of COVID-19 around the world a global public health emergency. It is well-known that the spread of the disease is influenced by people's willingness to adopt preventative public health behaviors, which are often associated with public risk perception. In this study, we present the first assessment of public risk perception of COVID-19 around the world using national samples (total N = 6,991) in ten countries across Europe, America, and Asia. We find that although levels of concern are relatively high, they are highest in the UK and lowest in South Korea. Across countries, personal experience with the virus, individualistic and prosocial values, hearing about the risk from friends and family, trust in government, science, and medical professionals, and personal and collective efficacy were all significant predictors of risk perception. Although there was substantial variability across cultures, individualistic worldviews, personal experience, prosocial values, and social amplification through friends and family in particular were found to be significant determinants in greater than half of the countries examined. Risk perception correlated with reported adoption of preventative health behaviors in all ten countries. Implications for effective risk communication are discussed. ; David & Claudia Harding Foundation

Background: As several COVID-19 vaccines are rolled-out globally, it has become important to develop an effective strategy for vaccine acceptance, especially in high-risk groups, such as elderly. Vaccine misconception was declared by WHO as one of the top 10 health issues in 2019. Here we test the effectiveness of applying debunking to combat vaccine misinformation, and reduce vaccine hesitancy. Methods: Participants were recruited via a daily news show on Dutch Television, targeted to elderly viewers. The study was conducted in 980 elderly citizens during the October 2020 National Influenza Vaccination Campaign. Borrowing from the recent literature in behavioural science and psychology we conducted a two-arm randomized blinded parallel study, in which participants were allocated to exposure to a video containing social norms, vaccine information plus debunking of vaccination myths (intervention group, n = 505) or a video only containing vaccine information plus social norm (control group, n = 475). Participants who viewed either of the video's and completed both a pre- and post-intervention survey on vaccination trust and knowledge, were included in the analysis. The main outcomes of this study were improvement on vaccine knowledge and awareness. Findings: Participants were recruited from the 13th of October 2020 till the 16th of October 2020 and could immediately participate in the pre-intervention survey. Subsequently, eligible participants were randomly assigned to an interventional video and the follow-up survey, distributed through email on the 18th of October 2020, and available for participation till the 24th of October 2020. We found that exposure to the video with addition of debunking strategies on top of social norm modelling and information resulted in substantially stronger rejection of vaccination misconceptions, including the belief that: (1) vaccinations can cause Autism Spectrum Disorders; (2) vaccinations weaken the immune system; (3) influenza vaccination would hamper the COVID-19 vaccine efficacy. Additionally, we observed that exposure to debunking in the intervention resulted in enhanced trust in government. Interpretation: Utilizing debunking in media campaigns on top of vaccine information and social norm modeling is an effective means to combat misinformation and distrust associated with vaccination in elderly, and could help maximize grounds for the acceptance of vaccines, including the COVID-19 vaccines. Funding: Dutch Influenza Foundation.

Despite Greta Thunberg's popularity, research has yet to investigate her impact on the public's willingness to take collective action on climate change. Using cross‐sectional data from a nationally representative survey of U.S. adults (N = 1,303), we investigate the "Greta Thunberg Effect," or whether exposure to Greta Thunberg predicts collective efficacy and intentions to engage in collective action. We find that those who are more familiar with Greta Thunberg have higher intentions of taking collective actions to reduce global warming and that stronger collective efficacy beliefs mediate this relationship. This association between familiarity with Greta Thunberg, collective efficacy beliefs, and collective action intentions is present even after accounting for respondents' overall support for climate activism. Moderated mediation models testing age and political ideology as moderators of the "Greta Thunberg Effect" indicate that although the indirect effect of familiarity with Greta Thunberg via collective efficacy is present across all age‐groups, and across the political spectrum, it may be stronger among those who identify as more liberal (than conservative). Our findings suggest that young public figures like Greta Thunberg may motivate collective action across the U.S. public, but their effect may be stronger among those with a shared political ideology. Implications for future research and for broadening climate activists' appeals across the political spectrum are discussed.

Abstract
Generative artificial intelligence (AI) has the potential to both exacerbate and ameliorate existing socioeconomic inequalities. In this article, we provide a state-of-the-art interdisciplinary overview of the potential impacts of generative AI on (mis)information and three information-intensive domains: work, education, and healthcare. Our goal is to highlight how generative AI could worsen existing inequalities while illuminating how AI may help mitigate pervasive social problems. In the information domain, generative AI can democratize content creation and access but may dramatically expand the production and proliferation of misinformation. In the workplace, it can boost productivity and create new jobs, but the benefits will likely be distributed unevenly. In education, it offers personalized learning, but may widen the digital divide. In healthcare, it might improve diagnostics and accessibility, but could deepen pre-existing inequalities. In each section, we cover a specific topic, evaluate existing research, identify critical gaps, and recommend research directions, including explicit trade-offs that complicate the derivation of a priori hypotheses. We conclude with a section highlighting the role of policymaking to maximize generative AI's potential to reduce inequalities while mitigating its harmful effects. We discuss strengths and weaknesses of existing policy frameworks in the European Union, the United States, and the United Kingdom, observing that each fails to fully confront the socioeconomic challenges we have identified. We propose several concrete policies that could promote shared prosperity through the advancement of generative AI. This article emphasizes the need for interdisciplinary collaborations to understand and address the complex challenges of generative AI.