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.

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.

This systematic review sought to synthesize and evaluate the quantitative findings regarding the inequality-radicalization relationship while considering their multidimensionality. The comprehensive search resulted in the screening of more than 5,000 items and the final inclusion of 141 publications. The findings of narrative synthesis suggested that socio-political inequality is more consistently positively related to terrorism/cognitive radicalization than economic inequality, which is more relevant for behavioral radicalization. The findings are discussed in terms of the importance of differentiating between dimensions, indicators, and levels of inequality and radicalization, complex relations, as well as shortcomings of existing evidence base and opportunities for improvement.

Despite multiple studies providing evidence of subjective inequality and dark personality traits as predictors of extremism, their interactive effect on extremism has not been studied. As such interactions are implied in multiple models of radicalization, this research was focused on testing them. While Study 1 (N = 279), based on a convenient student sample, established the interaction between perceived group relative socio-political deprivation and Dark Triad traits in the prediction of support for political violence, Study 2 (N = 461), based on a quota sample, specified it in the context of radicalized intentions: emotional component of group deprivation (anger, contempt, and disgust) interacts with the Dark Tetrad in the prediction of radicalized but not activist intentions, even after correcting for social desirability bias. Their combined explanatory power (up to 25% of explained variance) robustly confirms the role of individual dispositions and (responses to the perception of) contextual factors, as well as their interactions, in radicalization.

In this paper basic information of Homer software for PV system electricity generation, NASA - Surface meteorology and solar energy database, RETScreen, PVGIS and HMIRS (Hydrometeorological Institute of Republic of Serbia) solar databases are given. The comparison of the monthly average values for daily solar radiation per square meter received by the horizontal surface taken from NASA, RETScreen, PVGIS and HMIRS solar databases for three locations in Serbia (Belgrade, Negotin and Zlatibor) is given. It was found that the annual average values of daily solar radiation taken from RETScreen solar database are the closest to the annual average values of daily solar radiation taken from HMIRS solar database for Belgrade, Negotin and Zlatibor. Monthly and total for year values of electricity production of fixed on-grid PV system of 1 kW with optimal inclinated and south oriented solar modules, in Belgrade, Negotin and Zlatibor using HOMER software simulation based on data for daily solar radiation taken from NASA, RETScreen, PVGIS and HMIRS databases are calculated. The relative deviation of electricity production of fixed on-grid PV system of 1 kW using HOMER software simulation based on data for daily solar radiation taken from NASA, RETScreen, and PVGIS databases compared to electricity production of fixed on-grid PV system of 1 kW using HOMER software simulation based on data for daily solar radiation taken from HMIRS databases in Belgrade, Negotin and Zlatibor are given.