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This crowdsourced project introduces a collaborative approach to improving the reproducibility of scientific research, in which findings are replicated in qualified independent laboratories before (rather than after) they are published. Our goal is to establish a non-adversarial replication process with highly informative final results. To illustrate the Pre-Publication Independent Replication (PPIR) approach, 25 research groups conducted replications of all ten moral judgment effects which the last author and his collaborators had “in the pipeline” as of August 2014. Six findings replicated according to all replication criteria, one finding replicated but with a significantly smaller effect size than the original, one finding replicated consistently in the original culture but not outside of it, and two findings failed to find support. In total, 40% of the original findings failed at least one major replication criterion. Potential ways to implement and incentivize pre-publication independent replication on a large scale are discussed.

In addition to social determinants of health, such as economic resources, education, access to care and various environmental factors, there is growing evidence that political polarization poses a substantial risk to individual and collective well-being. Here we review the impact of political polarization on public health. We describe the different forms of polarization and how they are connected to health outcomes, highlighting the COVID-19 pandemic as a case study of the health risks of polarization. We then offer strategies for mitigating potential harms associated with polarization, with an emphasis on building social trust. Finally, we propose future research directions on this topic, underscore the need for more work in a global context and encourage greater collaboration between social scientists and medical scientists. We conclude that polarization is a serious-if largely overlooked-determinant of health, whose impacts must be more thoroughly understood and mitigated., (© 2024. Springer Nature America, Inc.)

Scholars warn that partisan divisions in the mass public threaten the health of American democracy. We conducted a megastudy ( n = 32,059 participants) testing 25 treatments designed by academics and practitioners to reduce Americans' partisan animosity and antidemocratic attitudes. We find that many treatments reduced partisan animosity, most strongly by highlighting relatable sympathetic individuals with different political beliefs or by emphasizing common identities shared by rival partisans. We also identify several treatments that reduced support for undemocratic practices-most strongly by correcting misperceptions of rival partisans' views or highlighting the threat of democratic collapse-which shows that antidemocratic attitudes are not intractable. Taken together, the study's findings identify promising general strategies for reducing partisan division and improving democratic attitudes, shedding theoretical light on challenges facing American democracy.

The study of intellectual humility (IH), which is gaining increasing interest among cognitive scientists, has been dominated by a focus on individuals. We propose that IH operates at the collective level as the tendency of a collective's members to attend to each other's intellectual limitations and the limitations of their collective cognitive efforts. Given people's propensity to better recognize others' limitations than their own, IH may be more readily achievable in collectives than individuals. We describe the socio-cognitive dynamics that can interfere with collective IH and offer the solution of building intellectually humbling environments that create a culture of IH that can outlast the given membership of a collective. We conclude with promising research directions., Competing Interests: Declaration of interests No interests are declared., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Climate change is currently one of humanity's greatest threats. To help scholars understand the psychology of climate change, we conducted an online quasi-experimental survey on 59,508 participants from 63 countries (collected between July 2022 and July 2023). In a between-subjects design, we tested 11 interventions designed to promote climate change mitigation across four outcomes: climate change belief, support for climate policies, willingness to share information on social media, and performance on an effortful pro-environmental behavioural task. Participants also reported their demographic information (e.g., age, gender) and several other independent variables (e.g., political orientation, perceptions about the scientific consensus). In the no-intervention control group, we also measured important additional variables, such as environmentalist identity and trust in climate science. We report the collaboration procedure, study design, raw and cleaned data, all survey materials, relevant analysis scripts, and data visualisations. This dataset can be used to further the understanding of psychological, demographic, and national-level factors related to individual-level climate action and how these differ across countries., (© 2024. The Author(s).)

The current paper explains how modern technology interacts with human psychology to create a funhouse mirror version of social norms. We argue that norms generated on social media often tend to be more extreme than offline norms which can create false perceptions of norms-known as pluralistic ignorance. We integrate research from political science, psychology, and cognitive science to explain how online environments become saturated with false norms, who is misrepresented online, what happens when online norms deviate from offline norms, where people are affected online, and why expressions are more extreme online. We provide a framework for understanding and correcting for the distortions in our perceptions of social norms that are created by social media platforms. We argue the funhouse mirror nature of social media can be pernicious for individuals and society by increasing pluralistic ignorance and false polarization., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Jay Van Bavel reports financial support was provided by Google Jigsaw. Jay Van Bavel reports financial support was provided by John Templeton World Charity Foundation (TWCF-2022-30561). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Recent studies have documented the type of content that is most likely to spread widely, or go "viral," on social media, yet little is known about people's perceptions of what goes viral or what should go viral. This is critical to understand because there is widespread debate about how to improve or regulate social media algorithms. We recruited a sample of participants that is nationally representative of the U.S. population (according to age, gender, and race/ethnicity) and surveyed them about their perceptions of social media virality ( n = 511). In line with prior research, people believe that divisive content, moral outrage, negative content, high-arousal content, and misinformation are all likely to go viral online. However, they reported that this type of content should not go viral on social media. Instead, people reported that many forms of positive content-such as accurate content, nuanced content, and educational content-are not likely to go viral even though they think this content should go viral. These perceptions were shared among most participants and were only weakly related to political orientation, social media usage, and demographic variables. In sum, there is broad consensus around the type of content people think social media platforms should and should not amplify, which can help inform solutions for improving social media.

The social and behavioral sciences have been increasingly using automated text analysis to measure psychological constructs in text. We explore whether GPT, the large-language model (LLM) underlying the AI chatbot ChatGPT, can be used as a tool for automated psychological text analysis in several languages. Across 15 datasets ( n = 47,925 manually annotated tweets and news headlines), we tested whether different versions of GPT (3.5 Turbo, 4, and 4 Turbo) can accurately detect psychological constructs (sentiment, discrete emotions, offensiveness, and moral foundations) across 12 languages. We found that GPT ( r = 0.59 to 0.77) performed much better than English-language dictionary analysis ( r = 0.20 to 0.30) at detecting psychological constructs as judged by manual annotators. GPT performed nearly as well as, and sometimes better than, several top-performing fine-tuned machine learning models. Moreover, GPT's performance improved across successive versions of the model, particularly for lesser-spoken languages, and became less expensive. Overall, GPT may be superior to many existing methods of automated text analysis, since it achieves relatively high accuracy across many languages, requires no training data, and is easy to use with simple prompts (e.g., "is this text negative?") and little coding experience. We provide sample code and a video tutorial for analyzing text with the GPT application programming interface. We argue that GPT and other LLMs help democratize automated text analysis by making advanced natural language processing capabilities more accessible, and may help facilitate more cross-linguistic research with understudied languages., Competing Interests: Competing interests statement:The authors declare no competing interest.

The tendency for people to consider themselves morally good while behaving selfishly is known as moral hypocrisy. Influential work by Valdesolo and DeSteno (2007) found evidence for intergroup moral hypocrisy such that people were more forgiving of transgressions when they were committed by an in-group member than an out-group member. We conducted two experiments to examine moral hypocrisy and group membership in an online paradigm with Prolific workers from the United States: a direct replication of the original work with minimal groups ( N = 610; nationally representative) and a conceptual replication with political groups ( N = 606; 50% Democrats and 50% Republicans). Although the results did not replicate the original findings, we observed evidence of in-group favoritism in minimal groups and out-group derogation in political groups. The current research finds mixed evidence of intergroup moral hypocrisy and has implications for understanding the contextual dependencies of intergroup bias and partisanship.

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.

Although much of human morality evolved in an environment of small group living, almost 6 billion people use the internet in the modern era. We argue that the technological transformation has created an entirely new ecosystem that is often mismatched with our evolved adaptations for social living. We discuss how evolved responses to moral transgressions, such as compassion for victims of transgressions and punishment of transgressors, are disrupted by two main features of the online context. First, the scale of the internet exposes us to an unnaturally large quantity of extreme moral content, causing compassion fatigue and increasing public shaming. Second, the physical and psychological distance between moral actors online can lead to ineffective collective action and virtue signaling. We discuss practical implications of these mismatches and suggest directions for future research on morality in the internet era., (© The Author(s) 2024. Published by Oxford University Press on behalf of National Academy of Sciences.)

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., (© The Author(s) 2024. Published by Oxford University Press on behalf of National Academy of Sciences.)

Social media takes advantage of people's predisposition to attend to threatening stimuli by promoting content in algorithms that capture attention. However, this content is often not what people expressly state they would like to see. We propose that social media companies should weigh users' expressed preferences more heavily in algorithms. We propose modest changes to user interfaces that could reduce the abundance of threatening content in the online environment.

A major barrier to climate change mitigation is the political polarization of climate change beliefs. In a global experiment conducted in 60 countries (N = 51,224), we assess the differential impact of eleven climate interventions across the ideological divide. At baseline, we find political polarization of climate change beliefs and policy support globally, with people who reported being liberal believing and supporting climate policy more than those who reported being conservative (Cohen's d = 0.35 and 0.27, respectively). However, we find no evidence for a statistically significant difference between these groups in their engagement in a behavioral tree planting task. This conceptual-behavioral polarization incongruence results from self-identified conservatives acting despite not believing, rather than self-identified liberals not acting on their beliefs. We also find three interventions (emphasizing effective collective actions, writing a letter to a future generation member, and writing a letter from the future self) boost climate beliefs and policy support across the ideological spectrum, and one intervention (emphasizing scientific consensus) stimulates the climate action of people identifying as liberal. None of the interventions tested show evidence for a statistically significant boost in climate action for self-identified conservatives. We discuss implications for practitioners deploying targeted climate interventions., (© 2024. The Author(s).)

The spread of misinformation threatens democratic societies, hampering informed decision-making. Partisan identity biases perceptions of reality, promoting false beliefs. The Identity-based Model of Political Belief explains how social identity shapes information processing and contributes to misinformation. According to this model, social identity goals can override accuracy goals, leading to belief alignment with party members rather than facts. We propose an extended version of this model that incorporates the role of informational context in misinformation belief and sharing. Partisanship involves cognitive and motivational aspects that shape party members' beliefs and actions. This includes whether they seek further evidence, where they seek that evidence, and which sources they trust. Understanding the interplay between social identity and accuracy is crucial in addressing misinformation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The spread of misinformation is a pressing societal challenge. Prior work shows that shifting attention to accuracy increases the quality of people's news-sharing decisions. However, researchers disagree on whether accuracy-prompt interventions work for U.S. Republicans/conservatives and whether partisanship moderates the effect. In this preregistered adversarial collaboration, we tested this question using a multiverse meta-analysis ( k = 21; N = 27,828). In all 70 models, accuracy prompts improved sharing discernment among Republicans/conservatives. We observed significant partisan moderation for single-headline "evaluation" treatments (a critical test for one research team) such that the effect was stronger among Democrats than Republicans. However, this moderation was not consistently robust across different operationalizations of ideology/partisanship, exclusion criteria, or treatment type. Overall, we observed significant partisan moderation in 50% of specifications (all of which were considered critical for the other team). We discuss the conditions under which moderation is observed and offer interpretations.

Interventions to counter misinformation are often less effective for polarizing content on social media platforms. We sought to overcome this limitation by testing an identity-based intervention, which aims to promote accuracy by incorporating normative cues directly into the social media user interface. Across three pre-registered experiments in the US ( N = 1709) and UK ( N = 804), we found that crowdsourcing accuracy judgements by adding a Misleading count (next to the Like count) reduced participants' reported likelihood to share inaccurate information about partisan issues by 25% (compared with a control condition). The Misleading count was also more effective when it reflected in-group norms (from fellow Democrats/Republicans) compared with the norms of general users, though this effect was absent in a less politically polarized context (UK). Moreover, the normative intervention was roughly five times as effective as another popular misinformation intervention (i.e. the accuracy nudge reduced sharing misinformation by 5%). Extreme partisanship did not undermine the effectiveness of the intervention. Our results suggest that identity-based interventions based on the science of social norms can be more effective than identity-neutral alternatives to counter partisan misinformation in politically polarized contexts (e.g. the US). This article is part of the theme issue 'Social norm change: drivers and consequences'.

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions' effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior-several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people's initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.

Nearly five billion people around the world now use social media, and this number continues to grow. One of the primary goals of social media platforms is to capture and monetize human attention. One means by which individuals and groups can capture attention and drive engagement on these platforms is by sharing morally and emotionally evocative content. We review a growing body of research on the interrelationship of social media and morality as well its consequences for individuals and society. Moral content often goes viral on social media, and social media makes moral behavior (such as punishment) less costly. Thus, social media often acts as an accelerant for existing moral dynamics, amplifying outrage, status seeking, and intergroup conflict while also potentially amplifying more constructive facets of morality, such as social support, prosociality, and collective action. We discuss trends, heated debates, and future directions in this emerging literature.

Scientific evidence regularly guides policy decisions 1 , with behavioural science increasingly part of this process 2 . In April 2020, an influential paper 3 proposed 19 policy recommendations ('claims') detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms 'physical distancing' and 'social distancing'. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization., (© 2023. The Author(s).)

Online misinformation is disproportionality created and spread by people with extreme political attitudes, especially among the far-right. There is a debate in the literature about why people spread misinformation and what should be done about it. According to the purely cognitive account, people largely spread misinformation because they are lazy, not biased. According to a motivational account, people are also motivated to believe and spread misinformation for ideological and partisan reasons. To better understand the psychological and neurocognitive processes that underlie misinformation sharing among the far-right, we conducted a cross-cultural experiment with conservatives and far-right partisans in the Unites States and Spain ( N = 1,609) and a neuroimaging study with far-right partisans in Spain ( N = 36). Far-right partisans in Spain and U.S. Republicans who highly identify with Trump were more likely to share misinformation than center-right voters and other Republicans, especially when the misinformation was related to sacred values (e.g., immigration). Sacred values predicted misinformation sharing above and beyond familiarity, attitude strength, and salience of the issue. Moreover, far-right partisans were unresponsive to fact-checking and accuracy nudges. At a neural level, this group showed increased activity in brain regions implicated in mentalizing and norm compliance in response to posts with sacred values. These results suggest that the two components of political devotion-identity fusion and sacred values-play a key role in misinformation sharing, highlighting the identity-affirming dimension of misinformation sharing. We discuss the need for motivational and identity-based interventions to help curb misinformation for high-risk partisan groups. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Beliefs have long been theorized to predict behaviors and thus have been the target of many interventions aimed at changing false beliefs in the population. But does changing beliefs translate into predictable changes in behaviors? Here, we investigated the impact of belief change on behavioral change across two experiments ( N = 576). Participants rated the accuracy of a set of health-related statements and chose corresponding campaigns to which they could donate funds in an incentivized-choice task. They were then provided with relevant evidence in favor of the correct statements and against the incorrect statements. Finally, they rated the accuracy of the initial set of statements again and were given a chance to change their donation choices. We found that evidence changed beliefs and this, in turn, led to behavioral change. In a preregistered follow-up experiment, we replicated these findings with politically charged topics and found a partisan asymmetry in the effect, such that belief change triggered behavioral change only for Democrats on Democratic topics, but not for Democrats on Republican topics or for Republicans on either topic. We discuss the implications of this work in the context of interventions aimed at stimulating climate action or preventative health behaviors. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

System-level change is crucial for solving society's most pressing problems. However, individual-level interventions may be useful for creating behavioral change before system-level change is in place and for increasing necessary public support for system-level solutions. Participating in individual-level solutions may increase support for system-level solutions - especially if the individual-level solutions are internalized as part of one's social identity.

The extent to which belief in (mis)information reflects lack of knowledge versus a lack of motivation to be accurate is unclear. Here, across four experiments (n = 3,364), we motivated US participants to be accurate by providing financial incentives for correct responses about the veracity of true and false political news headlines. Financial incentives improved accuracy and reduced partisan bias in judgements of headlines by about 30%, primarily by increasing the perceived accuracy of true news from the opposing party (d = 0.47). Incentivizing people to identify news that would be liked by their political allies, however, decreased accuracy. Replicating prior work, conservatives were less accurate at discerning true from false headlines than liberals, yet incentives closed the gap in accuracy between conservatives and liberals by 52%. A non-financial accuracy motivation intervention was also effective, suggesting that motivation-based interventions are scalable. Altogether, these results suggest that a substantial portion of people's judgements of the accuracy of news reflects motivational factors., (© 2023. The Author(s).)

The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through persuasive messaging and collective behaviour change. To help scholars better understand the social and moral psychology behind public health behaviour, we present a dataset comprising of 51,404 individuals from 69 countries. This dataset was collected for the International Collaboration on Social & Moral Psychology of COVID-19 project (ICSMP COVID-19). This social science survey invited participants around the world to complete a series of moral and psychological measures and public health attitudes about COVID-19 during an early phase of the COVID-19 pandemic (between April and June 2020). The survey included seven broad categories of questions: COVID-19 beliefs and compliance behaviours; identity and social attitudes; ideology; health and well-being; moral beliefs and motivation; personality traits; and demographic variables. We report both raw and cleaned data, along with all survey materials, data visualisations, and psychometric evaluations of key variables., (© 2023. The Author(s).)

Online media is important for society in informing and shaping opinions, hence raising the question of what drives online news consumption. Here we analyse the causal effect of negative and emotional words on news consumption using a large online dataset of viral news stories. Specifically, we conducted our analyses using a series of randomized controlled trials (N = 22,743). Our dataset comprises ~105,000 different variations of news stories from Upworthy.com that generated ∼5.7 million clicks across more than 370 million overall impressions. Although positive words were slightly more prevalent than negative words, we found that negative words in news headlines increased consumption rates (and positive words decreased consumption rates). For a headline of average length, each additional negative word increased the click-through rate by 2.3%. Our results contribute to a better understanding of why users engage with online media., (© 2023. The Author(s).)

Conspiracy theories related to coronavirus disease 2019 (COVID-19) have propagated around the globe, leading the World Health Organization to declare the spread of misinformation an "Infodemic." We tested the hypothesis that national narcissism-a belief in the greatness of one's nation that requires external recognition-is associated with the spread of conspiracy theories during the COVID-19 pandemic. In two large-scale national surveys ( N Total = 950) conducted in the United States and the United Kingdom, and secondary analysis of data from 56 countries ( N = 50,757), we found a robust, positive relationship between national narcissism and proneness to believe and disseminate conspiracy theories related to COVID-19. Furthermore, belief in COVID-19 conspiracy theories was related to less engagement in health behaviors and less support for public-health policies to combat COVID-19. Our findings illustrate the importance of social identity factors in the spread of conspiracy theories and provide insights into the psychological processes underlying the COVID-19 pandemic.

From an early age, children are willing to pay a personal cost to punish others for violations that do not affect them directly. Various motivations underlie such "costly punishment": People may punish to enforce cooperative norms (amplifying punishment of in-groups) or to express anger at perpetrators (amplifying punishment of out-groups). Thus, group-related values and attitudes (e.g., how much one values fairness or feels out-group hostility) likely shape the development of group-related punishment. The present experiments ( N = 269, ages 3-8 from across the United States) tested whether children's punishment varies according to their parents' political ideology-a possible proxy for the value systems transmitted to children intergenerationally. As hypothesized, parents' self-reported political ideology predicted variation in the punishment behavior of their children. Specifically, parental conservatism was associated with children's punishment of out-group members, and parental liberalism was associated with children's punishment of in-group members. These findings demonstrate how differences in group-related ideologies shape punishment across generations.

While conspiracy theories may offer benefits to those who believe in them, they can also foster intergroup conflict, threaten democracy, and undercut public health. We argue that the motivations behind conspiracy theory belief are often related to social identity. Conspiracy theories are well-positioned to fulfill social identity needs such as belongingness goals, the need to think highly of one's in-group, and the need to feel secure in one's group status. Understanding the social motives that attract people to conspiracy theories should be a focus of future research, and may be key to creating more successful interventions to reduce socially harmful conspiracy theories., Competing Interests: Conflict of interest statement Nothing declared., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

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 ( N 1  = 464 Twitter users, N 2  = 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., (© The Author(s) 2022. Published by Oxford University Press on behalf of National Academy of Sciences.)

Rising partisan animosity is associated with a reduction in support for democracy and an increase in support for political violence. Here we provide a multi-level review of interventions designed to reduce partisan animosity, which we define as negative thoughts, feelings and behaviours towards a political outgroup. We introduce the TRI framework to capture three levels of intervention-thoughts (correcting misconceptions and highlighting commonalities), relationships (building dialogue skills and fostering positive contact) and institutions (changing public discourse and transforming political structures)-and connect these levels by highlighting the importance of motivation and mobilization. Our review encompasses both interventions conducted as part of academic research projects and real-world interventions led by practitioners in non-profit organizations. We also explore the challenges of durability and scalability, examine self-fulfilling polarization and interventions that backfire, and discuss future directions for reducing partisan animosity., (© 2022. Springer Nature Limited.)

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 ( N  = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution-individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic., (© The Author(s) 2022. Published by Oxford University Press on behalf of National Academy of Sciences.)

The affective animosity between the political left and right has grown steadily in many countries over the past few years, posing a threat to democratic practices and public health. There is a rising concern over the role that "bad actors" or trolls may play in the polarization of online networks. In this research, we examined the processes by which trolls may sow intergroup conflict through polarized rhetoric. We developed a dictionary to assess online polarization by measuring language associated with communications that display partisan bias in their diffusion. We validated the polarized language dictionary in 4 different contexts and across multiple time periods. The polarization dictionary made out-of-set predictions, generalized to both new political contexts (#BlackLivesMatter) and a different social media platform (Reddit), and predicted partisan differences in public opinion polls about COVID-19. Then we analyzed tweets from a known Russian troll source ( N  = 383,510) and found that their use of polarized language has increased over time. We also compared troll tweets from 3 countries ( N  = 79,833) and found that they all utilize more polarized language than regular Americans ( N  = 1,507,300) and trolls have increased their use of polarized rhetoric over time. We also find that polarized language is associated with greater engagement, but this association only holds for politically engaged users (both trolls and regular users). This research clarifies how trolls leverage polarized language and provides an open-source, simple tool for exploration of polarized communications on social media., (© The Author(s) 2022. Published by Oxford University Press on behalf of the National Academy of Sciences.)

The aim of the social and behavioral sciences is to understand human behavior across a wide array of contexts. Our theories often make sweeping claims about human nature, assuming that our ancestors or offspring will be prone to the same biases and preferences. Yet we gloss over the fact that our research is often based in a single temporal context with a limited set of stimuli. Political and moral psychology are domains in which the context and stimuli are likely to matter a great deal (Van Bavel, Mende-Siedlecki, Brady, & Reinero, 2016). In response to Yarkoni (see BBS issue), we delve into topics related to political and moral psychology that likely depend on features of the research. These topics include understanding differences between liberals and conservatives, when people are willing to sacrifice someone to save others, the behavior of political leaders, and the dynamics of intergroup conflict.

Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = -0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics., (© 2022. The Author(s).)

This article reviews the empirical evidence on the relationship between social media and political polarization. We argue that social media shapes polarization through the following social, cognitive, and technological processes: partisan selection, message content, and platform design and algorithms., Competing Interests: Declaration of interests No interests are declared., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Rationale/objective: The COVID-19 pandemic has brought far-reaching consequences on individual and societal levels. Social distancing and physical hygiene constitute effective public health measures to limit the spread of the virus. This study investigated age and gender demographics, in tandem with national levels of human development, as crucial factors influencing self-reported compliance with COVID-19-related public health measures., Methods: The present study leveraged a large multi-national sample that ranged across the adult lifespan (18-100 years) and comprised 45,772 women and men from 66 countries/territories. Data were collected in Spring (2020) during the earlier phase of the COVID-19 pandemic. Self-reports of compliance with two public health measures (spatial distancing and physical hygiene) were assessed via online survey. Human Development Index (HDI), developed by the United Nations Development Program, was used as a proxy of a country's achievement in key dimensions of human development., Results: Older age, female gender, and lower HDI were independently associated with greater self-reported compliance. A significant three-way interaction further revealed that self-reported compliance was lowest in young males from well-developed countries, while highest among females across all ages from less-developed countries., Conclusion: The study offers an integration of individual-level and country-level demographic predictors of self-reported compliance and allows for robust testing in a large multi-national adult lifespan sample for enhanced generalizability. The results highlight the potential of data-driven, tailored (i.e., towards specific demographics, countries) health campaigns and public policies in the fight against a global pandemic., (Copyright © 2021. Published by Elsevier Ltd.)