We predict a riot: inequity, relative deprivation and collective destruction in the laboratory

Riots are unpredictable and dangerous. Our understanding of the factors that cause riots is based on correlational observations of population data, or post hoc introspection of individuals. To complement these accounts, we developed innovative experimental techniques, investigated the psychological factors of rioting and explored their consequences with agent-based simulations. We created a game, ‘Parklife’, that physically co-present participants played using smartphones. In two teams, participants tapped on their screen to grow trees and flowerbeds on separate but adjacent virtual parks. Participants could also tap to vandalize the other team's park. In some conditions, we surreptitiously introduced inequity between the teams so that one (the disadvantaged team) had to tap more for each reward. The experience of inequity caused the disadvantaged team to engage in more destruction, and to report higher relative deprivation and frustration. Agent-based models suggested that acts of destruction were driven by the interaction between individual level of frustration and the team's behaviour. Our results provide insights into the psychological mechanisms underlying collective action

A quantification of the reliability of self-reports following a simulated stressful event

Interviews and surveys are the most commonly used data-gathering and data-generating techniques when investigating human behaviour in emergencies. However, these approaches suffer from several limitations, including potential errors in memory accuracy, a lack of quantitative reliability. This study focuses on a survey performed on participants who had taken part in a stressful experiment. The survey was carried out three months afterwards, asking them to recall their experience. Analysis of this data quantitatively assesses their recall, across multiple different domains. This study observed several differences between experimental and control group participants, as well as differences between participants in VR and Physical experimental groups. However, it observes no increase in confabulation as a result of increased stress. The outcome of this study is to provide insight into the quantitative reliability of interviews and surveys of people involved in emergencies

Social influence matters: We follow pandemic guidelines most when our close circle does

Why do we adopt new rules, such as social distancing? Although human sciences research stresses the key role of social influence in behaviour change, most COVID-19 campaigns emphasize the disease’s medical threat. In a global data set (n = 6,674), we investigated how social influences predict people’s adherence to distancing rules during the pandemic. Bayesian regression analyses controlling for stringency of local measures showed that people distanced most when they thought their close social circle did. Such social influence mattered more than people thinking distancing was the right thing to do. People’s adherence also aligned with their fellow citizens, but only if they felt deeply bonded with their country. Self-vulnerability to the disease predicted distancing more for people with larger social circles. Collective efficacy and collectivism also significantly predicted distancing. To achieve behavioural change during crises, policymakers must emphasize shared values and harness the social influence of close friends and family

A glossary for research on human crowd dynamics

This article presents a glossary of terms that are frequently used in research on human crowds. This topic is inherently multidisciplinary as it includes work in and across computer science, engineering, mathematics, physics, psychology and social science, for example. We do not view the glossary presented here as a collection of finalised and formal definitions. Instead, we suggest it is a snapshot of current views and the starting point of an ongoing process that we hope will be useful in providing some guidance on the use of terminology to develop a mutual understanding across disciplines. The glossary was developed collaboratively during a multidisciplinary meeting. We deliberately allow several definitions of terms, to reflect the confluence of disciplines in the field. This also reflects the fact not all contributors necessarily agree with all definitions in this glossary

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

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 multi-national 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 was found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-negligible 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

Author Correction: National identity predicts public health support during a global pandemic

Correction to: Nature Communications https://doi.org/10.1038/s41467-021-27668-9, published online 26 January 2022

National identity predicts public health support during a global pandemic

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

Social and moral psychology of COVID-19 across 69 countries

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

National identity predicts public health support during a global pandemic.

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