The impact of information sources on COVID-19 knowledge accumulation and vaccination intention

The Costs of Polarizing a Pandemic: Antecedents, Consequences, and Lessons

Polarization has been rising in the United States of America for the past few decades and now poses a significant-and growing-public-health risk. One of the signature features of the American response to the COVID-19 pandemic has been the degree to which perceptions of risk and willingness to follow public-health recommendations have been politically polarized. Although COVID-19 has proven more lethal than any war or public-health crisis in American history, the deadly consequences of the pandemic were exacerbated by polarization. We review research detailing how every phase of the COVID-19 pandemic has been polarized, including judgments of risk, spatial distancing, mask wearing, and vaccination. We describe the role of political ideology, partisan identity, leadership, misinformation, and mass communication in this public-health crisis. We then assess the overall impact of polarization on infections, illness, and mortality during the pandemic; offer a psychological analysis of key policy questions; and identify a set of future research questions for scholars and policy experts. Our analysis suggests that the catastrophic death toll in the United States was largely preventable and due, in large part, to the polarization of the pandemic. Finally, we discuss implications for public policy to help avoid the same deadly mistakes in future public-health crises.

Communication Strategies to Promote COVID-19 Vaccination Intention: How Effective are Source, Appeal, Framing, and Evidence Type Approaches?

This systematic review analyzed the effectiveness of key persuasive strategies - source, appeal, framing, and evidence (SAFE) - on COVID-19 vaccination intention. Quantitative studies were searched in Web of Science, Scopus, and PubMed following the PRISMA guidelines. From the 61 studies that met inclusion criteria, source and framing are the most commonly applied SAFE strategies. However, source characteristics are a more consistent influence on vaccine intentions than message framing strategies, with expert sources and general practitioners emerging as the key sources contributing to greater vaccine intentions. In addition, a range of mediators and moderators influence the process through which SAFE message strategies impact vaccine intentions. Framing effects, in particular, are moderated by political identity, source characteristics, and vaccine perceptions. Tests of mediating processes highlight how health behavior judgments (e.g. perceived vaccine benefits, risks, trust in vaccination, perceived severity) and message response/perceptions (e.g. counterarguing, perceived similarity/empathy) operate as key intervening factors between SAFE message strategies and vaccine intentions. Overall, when practitioners apply various structural approaches (narrative elements, fear appeals, framing cues) to vaccine promotion campaigns, they should be cognizant of who is providing that appeal. Targeted populations may benefit most from different structural elements if they are integrated with sources that resonate with the audience.

The Reasoning through Evidence versus Advice (EvA) Scale: Scale Development and Validation

Our well-being can improve when people heed evidence rather than simply follow familiar or charismatic advisors who neglect evidence. We developed the Reasoning through Evidence versus Advice (EvA) scale to measure individual differences in reasoning through evidence like science and statistics versus following advisors such as politicians and celebrities. No existing scales directly measure these tendencies; moreover, it was theoretically unknown whether they reflect a single dimension (from evidence- to advice-based) or distinct tendencies to value or distrust each. Our scale validation process included qualitative interviews and four studies that involved 1583 respondents (753 college graduates, 830 non-college graduates) in which we conducted exploratory and confirmatory factor analyses and tests of convergent validity, discriminant validity, and measurement invariance by gender and education. This process yielded a 16-item EvA scale with four dimensions: Pro-evidence, Anti-evidence, Pro-advice, and Anti-advice. In assessing criterion validity, these tendencies identified individual differences in important, real-world attitudes and behaviors, including susceptibility to health misinformation, adherence to CDC guidelines on social distancing, confidence in the COVID vaccine, science curiosity, and religiosity. The EvA scale extends our understanding of individual differences in reasoning tendencies that shape critical attitudes, decisions, and behaviors and can help promote informed decisions.

The efficacy of health experts' communication in inducing support for COVID-19 measures and effect on trustworthiness: A survey in Hong Kong

To control the spread of COVID-19, governments may implement freedoms-infringing health measures. Therefore, citizens' support for these measures is important. This study investigates: (1) whether health experts' communication induces support for COVID-19 measures, and (2) whether health experts' agreeing or disagreeing with government directives affects their trustworthiness. A cross-sectional online questionnaire was completed by 1072 adults in the Hong Kong general population between May 26 and June 3, 2021. Three COVID-19 measures were examined: contact-tracing mobile application, restriction-testing, and ban of public assembly. For each, participants were randomly assigned to three groups to view, respectively: vignettes with a neutral government announcement only; vignettes with a government announcement and a health expert's quote supporting the government's decision; and vignettes with a government announcement and a health expert's quote disagreeing with the government's decision. The result shows that positive health experts' communication increased the support for banning public assembly; no effects were found for the support for contact-tracing mobile applications and restriction testing. Participants who only viewed health experts disagreeing with the government had higher trust in health experts relative to participants who viewed health experts agreeing with the government at least once. The results render doubtful the strategy that health experts can be involved for garnering support for unpopular health measures without jeopardizing public trust in them.

Online information disorder: fake news, bots and trolls

Recent years have seen a tremendous increase in the propagation of different types of misinformation and disinformation, including among others fake news, rumours, clickbait and conspiracy theories. Misinformation involved in satire and clickbait, among others, has a different intention from disinformation. Despite many attempts by the research community, the development of technology to assist experts in detecting disinformation remains an open problem due to a number of challenges. For example, there are various biases such as confirmation bias and peer pressure that hinder users from recognizing non-credible information. In addition, fake news is intentionally written to confuse the readers, often containing a mixture of false and real information. To this end, in this editorial we present current challenges in the area of fake news identification and discuss contributions published in our special issue.

AI in Combating the COVID-19 Pandemic

The SARS-CoV-2 virus, the COVID-19 disease, and the resulting pandemic have reshaped the entire world in an unprecedented manner. Massive efforts have been made by AI communities to combat the pandemic. What roles has AI played in tackling COVID-19? How has AI performed in the battle against COVID-19? Where are the gaps and opportunities? What lessons can we learn to enhance the ability of AI to battle future pandemics? These questions, despite being fundamental, are yet to be answered in full or systematically. They need to be addressed by AI communities as a priority despite the easing of the omicron infectiousness and threat. This article reviews these issues with reflections on global AI research and the literature on tackling COVID-19. It is envisaged that the demand and priority of developing "pandemic AI" will increase over time, with smart global epidemic early warning systems to be developed by a global collaborative AI effort.