Concern with COVID-19 pandemic threat and attitudes towards immigrants: The mediating effect of the desire for tightness

Tightening social norms is thought to be adaptive for dealing with collective threat yet it may have negative consequences for increasing prejudice. The present research investigated the role of desire for cultural tightness, triggered by the COVID-19 pandemic, in increasing negative attitudes towards immigrants. We used participant-level data from 41 countries (N = 55,015) collected as part of the PsyCorona project, a crossnational longitudinal study on responses to COVID-19. Our predictions were tested through multilevel and SEM models, treating participants as nested within countries. Results showed that people’s concern with COVID19 threat was related to greater desire for tightness which, in turn, was linked to more negative attitudes towards immigrants. These findings were followed up with a longitudinal model (N = 2,349) which also showed that people’s heightened concern with COVID-19 in an earlier stage of the pandemic was associated with an increase in their desire for tightness and negative attitudes towards immigrants later in time. Our findings offer insight into the trade-offs that tightening social norms under collective threat has for human groups

Trust in government regarding COVID-19 and its associations with preventive health behaviour and prosocial behaviour during the pandemic: a cross-sectional and longitudinal study

Background. The effective implementation of government policies and measures for controlling the coronavirus disease 2019 (COVID-19) pandemic requires compliance from the public. This study aimed to examine cross-sectional and longitudinal associations of trust ingovernment regarding COVID-19 control with the adoption of recommended health behaviours and prosocial behaviours, and potential determinants of trust in government duringthe pandemic.Methods. This study analysed data from the PsyCorona Survey, an international project onCOVID-19 that included 23 733 participants from 23 countries (representative in age andgender distributions by country) at baseline survey and 7785 participants who also completedfollow-up surveys. Specification curve analysis was used to examine concurrent associationsbetween trust in government and self-reported behaviours. We further used structural equation model to explore potential determinants of trust in government. Multilevel linear regressions were used to examine associations between baseline trust and longitudinal behavioural changes.Results. Higher trust in government regarding COVID-19 control was significantly associatedwith higher adoption of health behaviours (handwashing, avoiding crowded space, self-quarantine) and prosocial behaviours in specification curve analyses (median standardised β =0.173 and 0.229, p < 0.001). Government perceived as well organised, disseminating clear messages and knowledge on COVID-19, and perceived fairness were positively associated withtrust in government (standardised β = 0.358, 0.230, 0.056, and 0.249, p < 0.01). Higher trustat baseline survey was significantly associated with lower rate of decline in health behavioursover time ( p for interaction = 0.001).Conclusions. These results highlighted the importance of trust in government in the control of Covid-19

.Using machine learning to identify important predictors of COVID-19 infection prevention behaviors during the early phase of the pandemic

Before vaccines for coronavirus disease 2019 (COVID-19) became available, a set of infection-prevention behaviors constituted the primary means to mitigate the virus spread. Our study aimed to identify important predictors of this set of behaviors. Whereas social and health psychological theories suggest a limited set of predictors, machine-learning analyses can identify correlates from a larger pool of candidate predictors. We used random forests to rank 115 candidate correlates of infection-prevention behavior in 56,072 participants across 28 countries, administered in March to May 2020. The machine-learning model predicted 52% of the variance in infection-prevention behavior in a separate test sample—exceeding the performance of psychological models of health behavior. Results indicated the two most important predictors related to individuallevel injunctive norms. Illustrating how data-driven methods can complement theory, some of the most important predictors were not derived from theories of health behavior—and some theoretically derived predictors were relatively unimportant

‘We are all in the same boat’ : how societal discontent affects intention to help during the COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) pandemic has caused a global health crisis. Consequently, many countries have adopted restrictive measures that caused a substantial change in society. Within this framework, it is reasonable to suppose that a sentiment of societal discontent, defined as generalized concern about the precarious state of society, has arisen. Literature shows that collectively experienced situations can motivate people to help each other. Since societal discontent is conceptualized as a collective phenomenon, we argue that it could influence intention to help others, particularly those who suffer from coronavirus. Thus, in the present study, we aimed (a) to explore the relationship between societal discontent and intention to help at the individual level and (b) to investigate a possible moderating effect of societal discontent at the country level on this relationship. To fulfil our purposes, we used data collected in 42 countries (N = 61,734) from the PsyCorona Survey, a cross-national longitudinal study. Results of multilevel analysis showed that, when societal discontent is experienced by the entire community, individuals dissatisfied with society are more prone to help others. Testing the model with longitudinal data (N = 3,817) confirmed our results. Implications for those findings are discussed in relation to crisis management. Please refer to the Supplementary Material section to find this article's Community and Social Impact Statement

COVID-19 stressors and health behaviors. A multilevel longitudinal study across 86 countries

Anxiety associated with the COVID-19 pandemic and home confinement has been associated with adverse health behaviors, such as unhealthy eating, smoking, and drinking. However, most studies have been limited by regional sampling, which precludes the examination of behavioral consequences associated with the pandemic at a global level. Further, few studies operationalized pandemic-related stressors to enable the investigation of the impact of different types of stressors on health outcomes. This study examined the association between perceived risk of COVID-19 infection and economic burden of COVID-19 with health-promoting and health-damaging behaviors using data from the PsyCorona Study: an international, longitudinal online study of psychological and behavioral correlates of COVID-19. Analyses utilized data from 7,402 participants from 86 countries across three waves of assessment between May 16 and June 13, 2020. Participants completed self-report measures of COVID-19 infection risk, COVID-19-related economic burden, physical exercise, diet quality, cigarette smoking, sleep quality, and binge drinking. Multilevel structural equation modeling analyses showed that across three time points, perceived economic burden was associated with reduced diet quality and sleep quality, as well as increased smoking. Diet quality and sleep quality were lowest among respondents who perceived high COVID-19 infection risk combined with high economic burden. Neither binge drinking nor exercise were associated with perceived COVID-19 infection risk, economic burden, or their interaction. Findings point to the value of developing interventions to address COVID-related stressors, which have an impact on health behaviors that, in turn, may 111 influence vulnerability to COVID-19 and other health outcomes

PsyCorona: A world of reactions to COVID-19:How an online data visualization tool reports data from an international psychological survey

The purpose of this data visualization tool is twofold. First, it serves as a resource for researchers, analysts, and practitioners to understand people’s thoughts, feelings, and responses to the coronavirus as well as the extraordinary societal measures taken against it. Such knowledge could provide pilot data for researchers, inform current policies to contain the pandemic, or help society prepare for similar events in the future. Second, it serves as a test case for how psychological scientists can use data visualization to engage the public and share results with respondents. Tens of thou-sands of respondents invested time and effort to share their experiences, and the app affords them access and agency over the data as well as an interactive experience of how data can be used

Predictors of adherence to public health behaviors for fighting COVID-19 derived from longitudinal data.

The present paper examines longitudinally how subjective perceptions about COVID-19, one's community, and the government predict adherence to public health measures to reduce the spread of the virus. Using an international survey (N = 3040), we test how infection risk perception, trust in the governmental response and communications about COVID-19, conspiracy beliefs, social norms on distancing, tightness of culture, and community punishment predict various containment-related attitudes and behavior. Autoregressive analyses indicate that, at the personal level, personal hygiene behavior was predicted by personal infection risk perception. At social level, social distancing behaviors such as abstaining from face-to-face contact were predicted by perceived social norms. Support for behavioral mandates was predicted by confidence in the government and cultural tightness, whereas support for anti-lockdown protests was predicted by (lower) perceived clarity of communication about the virus. Results are discussed in light of policy implications and creating effective interventions

Trust in government and its associations with health behaviour and prosocial behaviour during the COVID-19 pandemic

Previous studies suggested that public trust in government is vital for implementations of social policies that rely on public's behavioural responses. This study examined associations of trust in government regarding COVID-19 control with recommended health behaviours and prosocial behaviours. Data from an international survey with representative samples (N=23,733) of 23 countries were analysed. Specification curve analysis showed that higher trust in government was significantly associated with higher adoption of health and prosocial behaviours in all reasonable specifications of multilevel linear models (median standardised β=0.173 and 0.244, P<0.001). We further used structural equation modelling to explore potential determinants of trust in government regarding pandemic control. Governments perceived as well organised, disseminating clear messages and knowledge on COVID-19, and perceived fairness were positively associated with trust in government (standardised β=0.358, 0.230, 0.055, and 0.250, P<0.01). These results highlighted the importance of trust in government in the control of COVID-19