Personal hardship narrows the partisan gap in COVID-19 and climate change responses.

The COVID-19 pandemic in the United States was characterized by a partisan gap. Democrats were more concerned about this novel health threat, more willing to socially distance, and more likely to support policies aimed at mitigating the spread of the virus than Republicans. In cross-sectional analyses of three nationally representative survey waves in 2020, we find that adverse experience with COVID-19 is associated with a narrowing of the partisan gap. The mean difference between Republicans and Democrats in concern, policy support, and behavioral intentions narrows or even disappears at high levels of self-reported adverse experience. Reported experience does not depend on party affiliation and is predicted by local COVID-19 incidence rates. In contrast, analyses of longitudinal data and county-level incidence rates do not show a consistent relationship among experience, partisanship, and behavior or policy support. Our findings suggest that self-reported personal experience interacts with partisanship in complex ways and may be an important channel for concern about novel threats such as the COVID-19 pandemic. We find consistent results for self-reported experience of extreme weather events and climate change attitudes and policy preferences, although the association between extreme weather and experience and climate change is more tenuous.

Sociocultural determinants of global mask-wearing behavior.

Behavioral responses influence the trajectories of epidemics. During the COVID-19 pandemic, nonpharmaceutical interventions (NPIs) reduced pathogen transmission and mortality worldwide. However, despite the global pandemic threat, there was substantial cross-country variation in the adoption of protective behaviors that is not explained by disease prevalence alone. In particular, many countries show a pattern of slow initial mask adoption followed by sharp transitions to high acceptance rates. These patterns are characteristic of behaviors that depend on social norms or peer influence. We develop a game-theoretic model of mask wearing where the utility of wearing a mask depends on the perceived risk of infection, social norms, and mandates from formal institutions. In this model, increasing pathogen transmission or policy stringency can trigger social tipping points in collective mask wearing. We show that complex social dynamics can emerge from simple individual interactions and that sociocultural variables and local policies are important for recovering cross-country variation in the speed and breadth of mask adoption. These results have implications for public health policy and data collection.

Understanding the coevolution of mask wearing and epidemics: A network perspective.

Nonpharmaceutical interventions (NPIs) such as mask wearing can be effective in mitigating the spread of infectious diseases. Therefore, understanding the behavioral dynamics of NPIs is critical for characterizing the dynamics of disease spread. Nevertheless, standard infection models tend to focus only on disease states, overlooking the dynamics of "beneficial contagions," e.g., compliance with NPIs. In this work, we investigate the concurrent spread of disease and mask-wearing behavior over multiplex networks. Our proposed framework captures both the competing and complementary relationships between the dueling contagion processes. Further, the model accounts for various behavioral mechanisms that influence mask wearing, such as peer pressure and fear of infection. Our results reveal that under the coupled disease-behavior dynamics, the attack rate of a disease-as a function of transition probability-exhibits a critical transition. Specifically, as the transmission probability exceeds a critical threshold, the attack rate decreases abruptly due to sustained mask-wearing responses. We empirically explore the causes of the critical transition and demonstrate the robustness of the observed phenomena. Our results highlight that without proper enforcement of NPIs, reductions in the disease transmission probability via other interventions may not be sufficient to reduce the final epidemic size.

Segregation and clustering of preferences erode socially beneficial coordination.

Polarization on various issues has increased in many Western democracies over the last decades, leading to divergent beliefs, preferences, and behaviors within societies. We develop a model to investigate the effects of polarization on the likelihood that a society will coordinate on a welfare-improving action in a context in which collective benefits are acquired only if enough individuals take that action. We examine the impacts of different manifestations of polarization: heterogeneity of preferences, segregation of the social network, and the interaction between the two. In this context, heterogeneity captures differential perceived benefits from coordinating, which can lead to different intentions and sensitivity regarding the intentions of others. Segregation of the social network can create a bottleneck in information flows about others' preferences, as individuals may base their decisions only on their close neighbors. Additionally, heterogeneous preferences can be evenly distributed in the population or clustered in the local network, respectively reflecting or systematically departing from the views of the broader society. The model predicts that heterogeneity of preferences alone is innocuous and it can even be beneficial, while segregation can hamper coordination, mainly when local networks distort the distribution of valuations. We base these results on a multimethod approach including an online group experiment with 750 individuals. We randomize the range of valuations associated with different choice options and the information respondents have about others. The experimental results reinforce the idea that, even in a situation in which all could stand to gain from coordination, polarization can impede social progress.

Community-engaged research is best positioned to catalyze systemic change.

Addressing many social challenges requires both structural and behavioral change. The binary of an i- and s-frame obscures how behavioral science can help foster bottom-up collective action. Adopting a community-frame perspective moves toward a more integrative view of how social change emerges, and how it might be promoted by policymakers and publics in service of addressing challenges like climate change.

Chronic and Acute Stress Promote Overexploitation in Serial Decision Making.

Many decisions that humans make resemble foraging problems in which a currently available, known option must be weighed against an unknown alternative option. In such foraging decisions, the quality of the overall environment can be used as a proxy for estimating the value of future unknown options against which current prospects are compared. We hypothesized that such foraging-like decisions would be characteristically sensitive to stress, a physiological response that tracks biologically relevant changes in environmental context. Specifically, we hypothesized that stress would lead to more exploitative foraging behavior. To test this, we investigated how acute and chronic stress, as measured by changes in cortisol in response to an acute stress manipulation and subjective scores on a questionnaire assessing recent chronic stress, relate to performance in a virtual sequential foraging task. We found that both types of stress bias human decision makers toward overexploiting current options relative to an optimal policy. These findings suggest a possible computational role of stress in decision making in which stress biases judgments of environmental quality.SIGNIFICANCE STATEMENT Many of the most biologically relevant decisions that we make are foraging-like decisions about whether to stay with a current option or search the environment for a potentially better one. In the current study, we found that both acute physiological and chronic subjective stress are associated with greater overexploitation or staying at current options for longer than is optimal. These results suggest a domain-general way in which stress might bias foraging decisions through changing one's appraisal of the overall quality of the environment. These novel findings not only have implications for understanding how this important class of foraging decisions might be biologically implemented, but also for understanding the computational role of stress in behavior and cognition more broadly.

Learning the opportunity cost of time in a patch-foraging task.

Although most decision research concerns choice between simultaneously presented options, in many situations options are encountered serially, and the decision is whether to exploit an option or search for a better one. Such problems have a rich history in animal foraging, but we know little about the psychological processes involved. In particular, it is unknown whether learning in these problems is supported by the well-studied neurocomputational mechanisms involved in more conventional tasks. We investigated how humans learn in a foraging task, which requires deciding whether to harvest a depleting resource or switch to a replenished one. The optimal choice (given by the marginal value theorem; MVT) requires comparing the immediate return from harvesting to the opportunity cost of time, which is given by the long-run average reward. In two experiments, we varied opportunity cost across blocks, and subjects adjusted their behavior to blockwise changes in environmental characteristics. We examined how subjects learned their choice strategies by comparing choice adjustments to a learning rule suggested by the MVT (in which the opportunity cost threshold is estimated as an average over previous rewards) and to the predominant incremental-learning theory in neuroscience, temporal-difference learning (TD). Trial-by-trial decisions were explained better by the MVT threshold-learning rule. These findings expand on the foraging literature, which has focused on steady-state behavior, by elucidating a computational mechanism for learning in switching tasks that is distinct from those used in traditional tasks, and suggest connections to research on average reward rates in other domains of neuroscience.

Anticonformists catalyze societal transitions and facilitate the expression of evolving preferences.

The world is grappling with emerging, urgent, large-scale problems, such as climate change, pollution, biodiversity loss, and pandemics, which demand immediate and coordinated action. Social processes like conformity and social norms can either help maintain behaviors (e.g. cooperation in groups) or drive rapid societal change (e.g. rapid rooftop solar uptake), even without comprehensive policy measures. While the role of individual heterogeneity in such processes is well studied, there is limited work on the expression of individuals' preferences and the role of anticonformists-individuals who value acting differently from others-especially in dynamic environments. We introduce anticonformists into a game-theoretical collective decision-making framework that includes a complex network of agents with heterogeneous preferences about two alternative options. We study how anticonformists' presence changes the population's ability to express evolving personal preferences. We find that anticonformists facilitate the expression of preferences, even when they diverge from prevailing norms, breaking the "spiral of silence" whereby individuals do not act on their preferences when they believe others disapprove. Centrally placed anticonformists reduce by five-fold the number of anticonformists needed for a population to express its preferences. In dynamic environments where a previously unpopular choice becomes preferred, anticonformists catalyze social tipping and reduce the "cultural lag," even beyond the role of committed minorities-that is, individuals with a commitment to a specific cause. This research highlights the role of dissenting voices in shaping collective behavior, including their potential to catalyze the adoption of new technologies as they become favorable and to enrich democracy by facilitating the expression of views.

The expressive function of public policy: renewable energy mandates signal social norms.

Addressing collective action problems requires individuals to engage in coordinated and cooperative behaviours. Existing research suggests that individuals' propensity to work together depends in part on their belief that others support the cause in question. People form their expectations about prevalent beliefs and behaviours from many sources. To date, most of the literature has focussed on how social norm perceptions are inferred from peers or summary statistics. We explore an understudied source of norm information: the passage of policies by democratically elected institutions. Institutional signals, such as the setting of defaults, national laws or policies, can act as coordination devices, signalling or prescribing social norms to large audiences. However, their expressive function is likely to depend on whether the institution is seen as accountable to the public. In two highly powered, pre-registered experiments (N = 11 636), we examine the role of policy signals as a source of social norm information. In Study 1, Americans randomly assigned to learn that their state passed a 100% renewable energy mandate believe that a greater percentage of their state's residents support such a mandate. In Study 2, we replicate this effect for national policy and show that the influence is moderated by information about whether the government represents the will of the people. This article is part of the theme issue 'Social norm change: drivers and consequences'.

PET-measured human dopamine synthesis capacity and receptor availability predict trading rewards and time-costs during foraging.

Foraging behavior requires weighing costs of time to decide when to leave one reward patch to search for another. Computational and animal studies suggest that striatal dopamine is key to this process; however, the specific role of dopamine in foraging behavior in humans is not well characterized. We use positron emission tomography (PET) imaging to directly measure dopamine synthesis capacity and D1 and D2/3 receptor availability in 57 healthy adults who complete a computerized foraging task. Using voxelwise data and principal component analysis to identify patterns of variation across PET measures, we show that striatal D1 and D2/3 receptor availability and a pattern of mesolimbic and anterior cingulate cortex dopamine function are important for adjusting the threshold for leaving a patch to explore, with specific sensitivity to changes in travel time. These findings suggest a key role for dopamine in trading reward benefits against temporal costs to modulate behavioral adaptions to changes in the reward environment critical for foraging.

Group identities can undermine social tipping after intervention.

Social tipping can accelerate behaviour change consistent with policy objectives in diverse domains from social justice to climate change. Hypothetically, however, group identities might undermine tipping in ways that policymakers do not anticipate. To examine this, we implemented an experiment around the 2020 US federal elections. The participants faced consistent incentives to coordinate their choices. Once the participants had established a coordination norm, an intervention created pressure to tip to a new norm. Our control treatment used neutral labels for choices. Our identity treatment used partisan political images. This simple pay-off-irrelevant relabelling generated extreme differences. The control groups developed norms slowly before intervention but transitioned to new norms rapidly after intervention. The identity groups developed norms rapidly before intervention but persisted in a state of costly disagreement after intervention. Tipping was powerful but unreliable. It supported striking cultural changes when choice and identity were unlinked, but even a trivial link destroyed tipping entirely.

Scaling Up Change: A Critical Review and Practical Guide to Harnessing Social Norms for Climate Action.

Anthropogenic carbon emissions have the potential to trigger changes in climate and ecosystems that would be catastrophic for the well-being of humans and other species. Widespread shifts in production and consumption patterns are urgently needed to address climate change. Although transnational agreements and national policy are necessary for a transition to a fully decarbonized global economy, fluctuating political priorities and lobbying by vested interests have slowed these efforts. Against this backdrop, bottom-up pressure from social movements and shifting social norms may offer a complementary path to a more sustainable economy. Furthermore, norm change may be an important component of decarbonization policies by accelerating or strengthening the impacts of other demand-side measures. Individual actions and policy support are social processes-they are intimately linked to expectations about the actions and beliefs of others. Although prevailing social norms often reinforce the status quo and unsustainable development pathways, social dynamics can also create widespread and rapid shifts in cultural values and practices, including increasing pressure on politicians to enact ambitious policy. We synthesize literature on social-norm influence, measurement, and change from the perspectives of psychology, anthropology, sociology, and economics. We discuss the opportunities and challenges for the use of social-norm and social-tipping interventions to promote climate action. Social-norm interventions aimed at addressing climate change or other social dilemmas are promising but no panacea. They require in-depth contextual knowledge, ethical consideration, and situation-specific tailoring and testing to understand whether they can be effectively implemented at scale. Our review aims to provide practitioners with insights and tools to reflect on the promises and pitfalls of such interventions in diverse contexts.

Decision-making under the deep uncertainty of climate change: The psychological and political agency of narratives.

Fossil fuel-based development has resulted in climate change and biodiversity loss, threatening the ability of the biosphere to sustain civilization. However, despite the transformative change needed to address climate change, the complexity inherent in dynamic, coupled social-ecological systems can create challenges that stifle mitigation and adaptation efforts. For example, increasing urbanization can mask information about the local and distal ecological impacts of unsustainable consumption patterns. Diverse actors, powerful vested interests in the status quo, and differential impacts of climate change create inevitable tradeoffs and conflicts among stakeholders. The multitude of plausible future scenarios and their dependence on actions taken today create challenges for planning, governance, and collective action. While there is a long history in psychology and economics of studying decision-making under uncertainty, we argue that the deep uncertainty inherent in climate change cannot be easily understood using these same paradigms. In this context, narratives-stories about how the world works, what the future will look like, and our own role in this process-can extend cognition, creating shared knowledge across space and time, and shape our beliefs, values and actions in the face of tremendous uncertainty. Narratives thus have political and psychological agency and can reinforce or challenge existing power relations and trajectories. Here, we review some of this literature in the context of climate change.

Voting in a global pandemic: Assessing dueling influences of Covid-19 on turnout.

OBJECTIVE: We investigate the impact of a global health crisis on political behavior. Specifically, we assess the impact of Covid-19 incidence rates, and the impact of temporal and spatial proximity to the crisis, on voter turnout in the 2020 Brazilian municipal elections. METHODS: We use Ordinary Least Squares and Spatial Durbin Error models to evaluate sub-national variation in municipal-level Covid-19 incidence and voter turnout. We include controls for political, economic, health, and state context. RESULTS: Ceteris paribus, increasing deaths in the month leading up to the election from 0.01 to 1 per 1000 people is associated with a 5 percentage point decrease in turnout; higher cases and deaths earlier in the pandemic are generally associated with higher turnout. Covid-19 incidence rates in nearby municipalities affect local turnout in the same directions. CONCLUSION: Higher Covid-19 incidence near the time of the election decreases voter turnout, while incidence farther from the election increases voter turnout.