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Social and moral psychology of Covid-19 across 69 countries

Social and moral psychology of Covid-19 across 69 countries

https://www.nature.com/articles/s41597-023-02080-8

Background & Summary

Well over two years after the official outbreak1, it is evident that the COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies2 as well as people’s physical and mental health3. At the time of writing, the world reached 850 million confirmed infections and up to 18 million deaths4. The detrimental effects of the pandemic extend beyond physical health with evidence of increased stress levels5 and suicide rates6, along with deterioration of general well-being7. Such findings reflect the cautionary warnings by Taylor8 that the psychological and societal effects are “likely to be more pronounced, more widespread, and longer-lasting than the purely somatic effects of the infection”8, p.23.

In the early stages of the pandemic, when vaccines were not yet available, governments introduced non-pharmaceutical interventions to reduce the spread of the SARS-CoV-2 virus9. Various contact-restricting policies (e.g., stay-at-home recommendations, curfews, police hours, partial or complete lock-downs) were enacted, and citizens were advised to adhere to public health recommendations (e.g., hand washing, face masks, and spatial distancing). It quickly became clear that behavioural science had a major role to play10.

On April 11th, a team of researchers launched a call for international collaboration in social and moral psychology. The initiative quickly gained momentum, gathering a consortium of over 250 academics worldwide. The aim of this project was to collect data from as many countries as possible to serve as a public good for the scientific community by allowing future research to draw on this broad database collected during this early phase of the COVID-19 pandemic. The survey, developed by the initial team, was circulated among the national teams, who provided feedback, translated it into 32 languages, and disseminated it online. The project concluded with responses from a total of 51,404 participants from 69 countries, 77 samples, between April 22nd and June 3rd, 2020.

A key goal of the project was to test the hypothesis that national identity predicts support for public health measures during the COVID-19 pandemic, which has since been confirmed11,12. In addition to collecting variables to test this hypothesis, we collected data on a variety of other social and moral constructs to make of our multi-country large-scale survey a rich resource for future research. The survey focused on the following areas: on a) COVID-19 beliefs and compliance behaviours (COVID-19 public health support, COVID-19 risk perception, COVID-19 conspiracy beliefs, and COVID-19 testing behaviour); b) identity and social attitudes (national identification, national narcissism, and social belonging); c) ideology (political ideology); d) health and well-being (subjective physical health, a wealth ladder ranking, and psychological well-being); e) moral beliefs and motivation (generosity, morality as cooperation, moral identity, and moral circle); f) personality traits and dispositions (open-mindedness, self-esteem, trait optimism, trait self-control, narcissism, and cognitive reflection); and g) demographic variables (i.e., sex, age, marital status, number of children, and employment status).

Using this dataset, project team members have pre-registered a variety of secondary hypotheses (see icsmp-covid19.netlify.app/preregistration), several of which have already been published11,12,13,14,15,16,17,18,19,20,21,22,23. In this paper, we present the complete ICSMP datasets to facilitate its findability, accessibility, interoperability, and reuse (FAIR;24,25) and maximize its educational impact26,27,28.

Methods

When possible, we used articles published in Nature Scientific Data presenting social sciences data as blueprints5,29. Given the urgent call for COVID-19 research, this study received an umbrella ethical approval from the University of Kent (see osf.io/ce638) but also complied with local ethics, norms, and regulations in the countries where the data were collected.

Participants

A total of 51,404 individuals from 77 samples across 69 countries participated in our survey. The inclusion criteria were the following: being 18 years of age and older, and giving informed consent (although researchers were encouraged to, ideally, recruit representative samples regarding age and gender). Data were collected between April 22nd and June 3rd, 2020. Figure 1 displays where the data were collected, coloured according to national sample size. Figure 2 displays the proportion of respondents in relation to the full sample. Figure 3 shows when the data were collected in each country.

Fig. 1
figure 1

A world map visualizing the number of participants in each surveyed country. Note: This heat map shows the number of respondents from each country. The gray areas are the countries that are not covered by the data, and the colour scale shows the size of the sample in accordance with the scale on the lower left side.

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Fig. 2
figure 2

International Collaboration on the Social and Moral Psychology of COVID-19: Investigated constructs, items and variables.

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Fig. 3
figure 3

Gantt Chart illustrating the data collection periods for each surveyed country.

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Demographic variables across countries are summarised in several tables: Tables 1, 2 show the number of participants, the mean proportion of non-missing ‘valid’ answers, and age. Tables 3, 4 illustrate the distribution of gender; Tables 5, 6 show employment status; and Tables 7–9 show marital status and number of children. When multiple samples were collected within the same country, data were split into numbered subgroups (e.g., for Brazil, which has three samples, they were flagged as Brazil_1, Brazil_2 and Brazil_3). Note that in the tables above, we kept country subsamples separated to highlight they were collected by different teams, often using different sampling methodologies or languages, which impact their characteristics (e.g., representativeness).

Table 1 Sample size, average proportion of valid answers, age of respondents and the number of data collections in 69 countries (A-M).

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Table 2 Sample size, average proportion of valid answers, age of respondents and the number of data collections in 69 countries (N-V).

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Table 3 Distribution of sex in 69 countries (A-M).

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Table 4 Distribution of sex in 69 countries (N-V).

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Table 5 Distribution of employment status in 69 countries (A-M).

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Table 6 Distribution of employment status in 69 countries (N-V).

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Table 7 Distribution of marital status and number of children in 69 countries (A-H).

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Table 8 Distribution of marital status and number of children in 69 countries (I-R).

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Table 9 Distribution of marital status and number of children in 69 countries (S-V).

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For the most part, participants were recruited via professional survey research companies and were incentivised to participate. In countries that, to our knowledge, did not possess polling infrastructure30, incentivising participants was not feasible. To collect data in these countries, leaders of national teams relied on online volunteers recruited via media appeals, mailing lists, advertisements on news aggregators, local communities and bloggers, and private messaging apps such as WhatsApp or WeChat.

Materials

The measures we used are illustrated in Figs. 4, 5 along with the specific items listed for each measure. In most cases, participants’ responses were collected on a scale from 0 = ‘strongly disagree’ to 10 = ‘strongly agree’, with 5 = ‘neither disagree nor agree’. In some cases, when more appropriate, we used other response scales (e.g., the generosity measure, where a 0–100% response scale was applied to hypothetical donations). In total, we collected 98 unique variables and meta-data. To ensure participants’ anonymity, no data that would allow their identification were collected.

Fig. 4
figure 4

International Collaboration on the Social and Moral Psychology of COVID-19: Investigated constructs, items and variables.

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Fig. 5
figure 5

International Collaboration on the Social and Moral Psychology of COVID-19: Investigated constructs, items and variables.

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COVID-19 Beliefs and compliance

Four constructs: COVID-19 public health support, COVID-19 risk perception, COVID-19 conspiracy theory beliefs, and COVID-19 testing behaviour. The public health support construct, in turn, is composed of three measures: spatial distancing, physical hygiene, and policy support. These are ad-hoc scales that we developed ourselves.

Identity and social attitudes

Three constructs: national identification31, national narcissism32, and social belonging33.

Ideology

One construct: political ideology. Participants self-reported their political orientation according to a single item on a scale from 0 (“Very left-leaning”) to 10 (“Very right-leaning”). This measure has been shown to account for a significant proportion of the variance in voting intentions in American presidential elections between 1972 and 200434 and 201635,36,37. In fact, using a single-item scale to measure political ideology has been a common practice in political psychology literature, providing substantive evidence for the validity of the measure both across national and international research38,39. However, even if the symbolic ideology can be a useful and parsimonious instrument to study political attitudes, when interpreting results, users should be attentive to the political and cultural applicability, psychometric validity, and generalisability of measures of political ideology40,41,42.

Health and well-being

Three constructs: subjective physical health, wealth ladder, and psychological well-being. Each of these scales relied on well-validated instruments43,44,45.

Moral beliefs and motivation

Four constructs: generosity46, morality as cooperation47, moral identity48, and moral circle49.

Personality traits

Six constructs: open-mindedness50, self-esteem51, trait optimism52, trait self-control53, narcissism54, and cognitive reflection55.

Demographics

Six questions: age, number of children, employment status, marital status, gender, and urbanicity.

Metadata and attention check

An attention check was used to mitigate negative impact on data quality from potential non-human responses and the likelihood of biasing data and subsequent analysis of low base-rate outcomes—such as endorsement of COVID-19 conspiracies. We collected typical questionnaire metadata (e.g., start, record, and end dates, duration, and language). In addition, we created an internal participant ID, added ISO2 and ISO3 country codes, and sample representativeness.

Translation

The survey instrument was drafted in English and translated into other languages using the standard forward-backward method (i.e., members of national teams were advised to split members into forward-translating the survey into the local language and back-translating it into English, and then have the two groups discuss and resolve discrepancies). In total, the survey instrument was translated into 32 languages, including adaptations of region-specific dialects or vernaculars. Specifically, from English into Arabic, Bengali, Bulgarian, Croatian, Danish, Dutch, Finnish, French, German, Greek, Hebrew, Hungary, Italian, Japanese, Korean, Kurdish, Latvian, Macedonian, Mandarin simplified, Mandarin traditional, Nepali, Norwegian, Polish, Portuguese, Romanian, Russian, Serbian, Slovak, Spanish, Swedish, Turkish, and Ukrainian (see osf.io/tfsza at sub-folder Translations).

Data cleaning

We received individual data files from each national team. To merge these raw data, minor modifications were introduced, which we delineate in this section. First, we renamed columns to match across data sets, reordered variables alphabetically, and standardised variable labels. Furthermore, all missing values and values denoting the absence of a response were converted to NAs (not available). When ambiguous date formats were found (e.g., on start date, end date, and record date), we manually specified the correct format and standardised them. At the second stage, we introduced multiple modifications to clean the data for research. Some modifications were introduced to every national data set, while others were introduced to specific national data sets (both of which are thoroughly reported in the Data Records section). To each national data set, we recoded the attention check (attcheck) into pass (1) or fail (0); standardised generosity items (generosity1–3), recoded CRT items into intuitive (2), correct (1), and incorrect (0); converted the number of children (children) into a variable with a fixed range from zero to ten or more; recoded all participants declaring being older than 100 years old as 100; and we excluded all duplicates (i.e., in case multiple participants were recorded with identical inputs within a national database, only the first input was retained).

Data Records

All materials associated with the ICSMP COVID-19 project can be found on the project’s repository (comprising five folders) hosted by the Open Science Framework (OSF, https://doi.org/10.17605/osf.io/tfsza)56,57. The folder named Code includes an R Markdown document (ICSMP official data.Rmd; osf.io/dwpng) that loads multiple data files (from each national team), cleans them up, merges them into a single data file, generates a data-driven code-book, and saves all outputs. It also includes a reproducible report with all reported numbers, analyses and graphs in this article (Analyses-SciData.html; osf.io/s5c4p; Analyses SciData.Rmd; osf.io/9suyb). The folder named Data includes three sub-folders. The Raw data sub-folder contains the original and unmodified data files from each national team (country data files.zip; osf.io/dqmut). The sub-folder named Cleaned data contains the merged and cleaned dataset, which is provided in a non-proprietary (ICSMP_cleaned_data.csv; osf.io/ypkrc) and a labelled (ICSMP_cleaned_data.sav; at osf.io/8tyj9) file formats. In addition, we included in a sub-folder a dataset that removes observations failing the attention check or filled out less than 50% of the items, both in a non-proprietary (ICSMP_cleaned_data_nobots.csv; osf.io/98fex) and a labelled (ICSMP_cleaned_data_nobots.sav; at osf.io/3yjga) file formats. The Metadata sub-folder provides a thorough itemised description of the data cleaning process in both text (Data Cleaning.docx; osf.io/7udpt) and human-readable change-log (human-readable change log ICSMP.xlsx; osf.io/fydx2).

We also provide a data-driven codebook detailing how each measure was collected—e.g., listing variable names, variable labels, and label values (dt.codebook.xlsx; osf.io/ecva2). The IRB folder contains both the Internal Review Board Ethics application (ICSMP Kent Ethics application full.pdf; osf.io/xt9gr) and Ethics approval (ICSMP Kent Ethics approval.pdf; osf.io/ce638). The folder Sample Type & Representativeness includes the documentation for an internal survey conducted with national team leaders about the employed survey methodology for the data provided (Sample Type & Representativeness.zip; osf.io/fj5xn). The folder Survey Instrument contains the initial English version of our survey instrument along with its Qualtrics.qsf for reproducibility (Survey Instrument.zip; osf.io/nf48q). In the sub-folder Translations, we archived all 32 translated survey instruments along with a report on the languages of conducted surveys per country (i.e., several countries had their surveys in multiple languages per country; Country and language.xlsx; osf.io/wj7d2).

Potential for future research

The data contains four measures of COVID-19 beliefs and compliance, 17 social and moral psychological constructs, and six sociodemographic characteristics, amounting to 27 socially-relevant variables. To quantify the potential of this dataset—and assuming a typical research paper uses between three to five key main constructs plus sociodemographics and controls—we calculated the number of combinations of 17 constructs, taken three, four, and five at a time, yielding a grand total of 9248 possible unique designs. As a demonstration of the broad scope of the ICSMP data, published studies cover a broad range of psychological disciplines, including social psychology13,14, cognitive psychology15,17, political psychology16, moral psychology16,18, economic psychology19 and health sciences20, among others. They explore different populations in reference to the COVID-19 pandemic in terms of age (e.g., older adults see21, marital status19 or nationality (e.g., for a study on the Spanish population, see;22 for Swedish and Chinese population see23), and other socio-demographic characteristics. These all attest to the great potential of the ICSMP data to inspire further research. In sum, the present dataset affords numerous opportunities for cross-cultural research on a plethora of hypotheses. We encourage researchers who consider reusing ICSMP data to examine the list of pre-registrations before beginning a new project so as to avoid duplication (see icsmp-covid19.netlify.app/preregistration).

Data visualisation interface

In addition to the raw data, a dedicated Web application was developed to provide a general overview of the dataset (icsmp.shinyapps.io/icsmp_covid19). The application is based on an R shiny server (rstudio.com/products/shiny), together with the leaflet58 and ggplot259 graphical libraries to generate dynamic plots. All the generated figures can be exported as .png files, and all tables can be exported as .csv files. The Web application allows easy and dynamic generation of illustrations like the figures with maps for each construct with zoomable world maps and static figures and plots for sample and country characteristics. In addition, all tables are embedded with dynamic features for sorting and filtering. To make it more accessible for the readers, both tables and figures are downloadable. The Shiny app has two tabs giving general information about the project and the international consortium. The first tab contains sample descriptions such as sample size, missing data, and attention checks for each country with a Gantt chart showing the dates of data collection. The second tab displays world maps of spatial distancing, policy support, national identity, conspiracy beliefs, national narcissism and morality as cooperation as well as all tables reported in dynamic formats.

Technical Validation

To support the technical quality of the dataset, we conducted an analysis to showcase its reliability (and its diverse applicability to research questions in social sciences and beyond). For completeness, in the analyses that follow, we examined all samples-including those with very few observations, such as Puerto Rico (N = 2), Brazil_3 (N = 6), and Panama (N = 12).

We evaluated the adopted survey methodology utilised by national teams by conducting an internal survey to ensure the accuracy of reported sample types. The inspection showed that 28 samples were quota-based nationally representative samples (36%), 6 used post hoc weights to achieve an approximate level of national representation (8%) which nonetheless should be seen as convenience samples, and 43 were convenience samples (56%), many of which were from low and middle-income countries60. We codified the results of this survey into the cleaned data as the variable ‘sample_coding’ and present a summary in Table 10. National representativeness for the 28 quota-based samples relate to an approximation of the demographic characteristics of age and gender only for each country.

Table 10 Overview of the samples.

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Regarding individual-level data quality, Fig. 6 shows a world map of the 69 countries from which data were collected, coloured according to overall percentages of missing data (overall mean = 6.0%). Overall, 95.6% of participants had less than 50% missing data, 92.8% participants had less than 10% missing data, and 24.7% of participants had 0% missing data. Another indicator of data quality is the rate of attention check fails per country. On the last screen of the survey, participants were given the following instructions: “Help us get rid of bots: Please write the number 213 into the comment box.” Participants who wrote “213” were coded as passing the attention check, participants who wrote anything else were coded as failing the attention check, and those who did not reach this screen of the survey were coded as missing data. Figure 6 also shows (bottom plot) a world map coloured according to the rate of attention-check fails across countries. Overall, 90.1% of participants passed the attention check (1.0% failed), and 8.0% did not reach the final screen with the attention check.

Fig. 6
figure 6

Data quality indicators for each surveyed country. Note: The percentage of missing data considered all the questions in the survey (i.e., all sociodemographics and psychological scales”). We calculated, for each country, the mean of the participants’ proportion of missing data across all survey questions, including sociodemographics (this information is also provided in our reproducible report of Fig. 6, where the R code is provided).

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The full dataset presents N = 51,404 cases across 69 countries (from 77 samples, 28 of which are quota-based nationally representative), with an average sample size of 745 (SD = 549) and a proportion of valid answers of 95%. The mean age of respondents was 42.93 (SD = 16.04) years, and 50.9% were women (44% males, 0.3% others, and 4.8% unreported). The employment status breakdown shows 44.8% employed full-time, 10.6% part-time, 8.1% unemployed, 10% students, 10.1% retired, 11% other, and 5.3% unreported. The overall marital status shows 33% of respondents were single, 18.7% in a relationship, 42.7% married, and 5.5% unreported. The majority of our participants reported having no children (41.6%), with 16.7% having one child, 20.1%, 9.2%, and 3.9% with two, three and four children, respectively, and 1.7% had five or more children (6.9% unreported). We break down these aggregated results per country. Tables 1, 2 show the number of cases and valid answers, Table 3,4 summarises the distribution of sex, Tables 5, 6 display employment status, and Tables 7–9 illustrate both marital statuses and the number of children.

We also examined cross-cultural differences in conspiracy beliefs, morality as cooperation, spatial distancing, national narcissism, national identification, and policy support for preventative measures across 69 countries in Fig. 7. Additionally, we showcase patterns of associations between these moral and psychological constructs across gender, ideology and age in Figs. 8, 9. For the association pattern analysis, we excluded samples with less than 490 respondents as recommended for stable correlations61, as well as for the subsequent consistency measure analysis.

Fig. 7
figure 7

Cross-cultural differences in Social & Moral Psychology of COVID-19 across 69 countries. Note: Each world heat map in the figure shows the means score, at the country level, for constructs in the survey. Conspiracy Beliefs - participant’s beliefs in conspiracy theories regarding COVID-19; Morality as Cooperation - participant’s moral concern based on the morality-as-cooperation theory; Spatial Distancing - participant’s support for spatial distancing as a strategy against COVID-19; Collective Narcissism - participant’s narcissism, i.e., an inflated view regarding their ingroup (in this research we focused on nationality); National Identity - participant’s identity attached to belonging to a nation; Policy Support - participant’s support to public policies (e.g., closing parks or schools) as a strategy against COVID-19.

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Fig. 8
figure 8

Cross-cultural differences in associations of Social & Moral Psychology of COVID-19 across sex and ideology in 69 countries.

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Fig. 9
figure 9

Cross-cultural differences in associations of Social & Moral Psychology of COVID-19 across age in 69 countries.

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To examine internal consistency for the main scales, we calculated Cronbach’s Alpha, Omega, Guttman split-half reliability, and proportion of variance explained by a unidimensional factor. This table is available at osf.io/ed7yg and shows indices of internal consistency by country for measures of conspiracy beliefs, morality as cooperation, spatial distancing, national narcissism, national identification, and policy support for preventative measures, respectively. We found that the spatial distancing construct, on average, has the lowest Cronbach’s alpha, followed by morality as cooperation. On average, conspiracy beliefs have the highest Cronbach’s alpha, followed by policy support. These patterns hold for the Omega measures, but when considering Guttman’s split-half reliability, collective narcissism and national identity yield the lowest values. Figures 9–15 show these patterns visually.

Fig. 10
figure 10

Support for policies in 69 countries.

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Fig. 11
figure 11

Collective narcissism in 69 countries.

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Fig. 12
figure 12

Spatial distancing in 69 countries.

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Fig. 13
figure 13

Morality as cooperation in 69 countries.

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Fig. 14
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National identity in 69 countries.

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Fig. 15
figure 15

Cross-cultural differences in Internal Consistency Coefficients (Cronbach’s alpha, McDonald’s Omega, Guttman Split-Half), and variance explained of Social & Moral Psychology Constructs in 69 countries. Note: internal consistency typically refers to correlations between different items on the same test to evaluate the extent to which latent indicators comprising the scale measure the same construct.

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Usage Notes

The datasets are shared, cleaned, and ready for analysis. We recommend that interested researchers use the cleaned version of the data (available at https://doi.org/10.17605/osf.io/tfsza)56. The use of the labelled data is also suggested for convenience as it has all variable levels encoded, thus eliminating the need to consult the codebook when using the.csv format.

The Data were imported and cleaned using the R software for statistical analysis62 and packages readr63, haven64, readxl65, dplyr66, psych67, htmltools68, mime69, xfun70, labelled71, sjlabelled72, codebook73, lubridate74.

As previously noted5, those wishing to approximate national representativeness can apply the appropriate survey weights to demographic and countries of interest when random sampling is used (e.g., sex: https://ourworldindata.org/gender-ratio; age: http://data.un.org/Data.aspx?d=POP&f=tableCode%3A22; education: https://ourworldindata.org/global-education; marital status: https://ourworldindata.org/marriages-and-divorces).

To minimize misclassification of text-based responses to the cognitive reflection test (CRT) and the attention check, we used multiple steps of data cleaning using REGEX (regular expressions) as fully detailed in (ICSMP official data.Rmd; osf.io/dwpng) located in the folder named Code. First, we coded the predefined numerical and text values as correct (in the case of CRT, also the values predefined as intuitive). Then, iteratively, we screened the remaining responses and, using REGEX, updated answers. Remaining responses were recoded as incorrect.

Code availability

All raw and cleaned data—as well as the R-code—used for standardising national-teams data, merging, and cleaning them are available at https://doi.org/10.17605/osf.io/tfsza56.

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Acknowledgements

The ICSMP consortium would like to acknowledge the additional contributions of numerous friends and collaborators in translating and sharing the COVIDiSTRESS survey, even if contributions were small or the person did not wish their name included as a member of the consortium.

Funding

Open Access funding enabled and organized by Projekt DEAL.

Author information

Authors and Affiliations

  1. Department of Psychology, University of Cambridge, Cambridge, England

    Flavio Azevedo & Steve Rathje

  2. Institute of Communication Science, Friedrich-Schiller University Jena, Jena, Germany

    Flavio Azevedo, Tobias Rothmund, Fahima Farkhari & Carolin-Theresa Ziemer

  3. Institute of Social Sciences Ivo Pilar, Zagreb, Croatia

    Tomislav Pavlović, Renata Franc, Marina Maglić & Igor Mikloušić

  4. Social and Cognitive Neuroscience Laboratory, Mackenzie Presbyterian University, São Paulo, Brazil

    Gabriel G. Rêgo, Paulo S. Boggio & Waldir M. Sampaio

  5. Department of Economics, Norwegian School of Economics, Bergen, Norway

    F. Ceren Ay

  6. Telenor Research, Oslo, Norway

    F. Ceren Ay

  7. Macedonian Academy of Sciences and Arts, Skopje, Republic of North Macedonia

    Biljana Gjoneska

  8. Kieskompas - Election Compass, Amsterdam, Netherlands

    Tom W. Etienne, Yordan Kutiyski & Oscar Moreda Laguna

  9. Department of Political Science & Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, USA

    Tom W. Etienne

  10. Department of Psychology, Macquarie University, Sydney, NSW, Australia

    Robert M. Ross

  11. Department of Philosophy, University of St Andrews, St Andrews, Scotland

    Philipp Schönegger

  12. School of Economics and Finance, University of St Andrews, St Andrews, Scotland

    Philipp Schönegger

  13. Medicine Faculty, Cooperative University of Colombia, Villavicencio, Colombia

    Julián C. Riaño-Moreno & Maria P. Bernal-Zárate

  14. Department of Bioethics, El Bosque University, Bogotá, Colombia

    Julián C. Riaño-Moreno

  15. School of Psychology, University of Kent, Canterbury, England

    Aleksandra Cichocka & Bjarki Gronfeldt

  16. Department of Economics, Middlesex University London, London, England

    Valerio Capraro

  17. Darden School of Business, University of Virginia, Charlottesville, VA, USA

    Luca Cian

  18. Questrom School of Business, Boston University, Boston, MA, USA

    Chiara Longoni

  19. School of Economics and Finance, Queensland University of Technology, Brisbane, QLD, Australia

    Ho Fai Chan, Uwe Dulleck, Ozan Isler & Benno Torgler

  20. Center for Behavioural Economics, Society and Technology, Queensland University of Technology, Brisbane, QLD, Australia

    Ho Fai Chan, Uwe Dulleck, Ozan Isler & Benno Torgler

  21. Department of Psychology and Neural Science, New York University, New York, NY, USA

    Jay J. Van Bavel, David M. Amodio, Elizabeth Harris, Claire E. Robertson & Anni Sternisko

  22. Department of Strategy and Management, Norwegian School of Economics, Bergen, Norway

    Hallgeir Sjåstad

  23. SWPS University of Social Sciences and Humanities, Warsaw, Poland

    John B. Nezlek, Aleksandra Cislak & Marzena Cypryańska

  24. Department of Psychological Sciences, College of William and Mary, Williamsburg, VA, USA

    John B. Nezlek

  25. Department of Philosophy, Macquarie University, Sydney, NSW, Australia

    Mark Alfano & Neil Levy

  26. Stanford Graduate School of Business, Stanford University, Stanford, CA, USA

    Michele J. Gelfand

  27. School of Human Sciences, Institute for Lifecourse Development, University of Greenwich, London, England

    Michèle D. Birtel & Harry Farmer

  28. Department of Experimental Psychology, University of Oxford, Oxford, England

    Patricia L. Lockwood & Jo Cutler

  29. Center for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, England

    Patricia L. Lockwood, Matthew Apps & Jo Cutler

  30. KU Leuven, Leuven, Belgium

    Koen Abts

  31. National Research University Higher School of Economics (HSE), Moscow, Russia

    Elena Agadullina & Natalia Bogatyreva

  32. De La Salle University, Manila, Philippines

    John Jamir Benzon Aruta

  33. Department of Psychology, University of the Witwatersrand, Johannesburg, South Africa

    Sahba Nomvula Besharati, Kate Cockcroft, Michael Mark Pitman & Enid M. Schutte

  34. Department of Political Science, Aarhus University, Aarhus, Denmark

    Alexander Bor, Antoine Marie, Michael Bang Petersen & Frederik J. Jorgensen

  35. Toronto Metropolitan University, Toronto, Canada

    Becky L. Choma & Rishad Habib

  36. Department of Government, Dartmouth College, Hanover, NH, USA

    Charles David Crabtree, Yusaku Horiuchi & John Kahn

  37. Department of Psychology, University of Toronto, Toronto, ON, Canada

    William A. Cunningham, Victoria H. Davis, Elizabeth U. Long & Victoria Oldemburgo de Mello

  38. Gatton College of Business and Economics, University of Kentucky, Lexington, KY, USA

    Koustav De

  39. Department of Mass Communication, National University of Science and Technology (NUST), Islamabad, Pakistan

    Waqas Ejaz

  40. Department of Management, Aarhus University, Aarhus, Denmark

    Christian T. Elbaek & Panagiotis Mitkidis

  41. Faculty of Social and Economic Sciences, Comenius University, Bratislava, Slovakia

    Andrej Findor & Matej Hruška

  42. IntraMed, Buenos Aires, Argentina

    Daniel Flichtentrei

  43. University of Colorado Boulder, Boulder, CO, USA

    June Gruber

  44. ESEIS/COIDESO [ESEIS, Social Studies and Social Intervention Research Center; COIDESO, COIDESO, Center for Research in Contemporary Thought and Innovation for Social Development], University of Huelva, Huelva, Spain

    Estrella Gualda, E. Begoña Garcia-Navarro, Elena Morales-Marente, M. Soledad Palacios-Galvez & Iván Rodríguez-Pascual

  45. Faculty of Social Work, University of Huelva, Huelva, Spain

    Estrella Gualda

  46. WHU - Otto Beisheim School of Management, Vallendar, Germany

    Toan Luu Duc Huynh

  47. Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile

    Agustin Ibanez

  48. Cognitive Neuroscience Center (CNC), University of San Andrés, Buenos Aires, Argentina

    Agustin Ibanez

  49. Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), California, US; & Trinity College Dublin (TCD), Dublin, Ireland

    Agustin Ibanez

  50. Department of Educational and Counselling Psychology, University of Dhaka, Dhaka, Bangladesh

    Mostak Ahamed Imran & Hapsa Hossain Farhana

  51. Department of Psychology, The Hebrew University of Jerusalem, Jerusalem, Israel

    Jacob Israelashvili, Anat Perry, Eli Adler & Eran Halperin

  52. Institute of Psychology, Jagiellonian University, Kraków, Poland

    Katarzyna Jasko

  53. Institute of Security and Global Affairs, Leiden University, The Hague, Netherlands

    Jaroslaw Kantorowicz

  54. Erasmus School of Law, Erasmus University Rotterdam, Rotterdam, Netherlands

    Elena Kantorowicz-Reznichenko

  55. Department of Political Science, Vrije University (VU) Amsterdam, Amsterdam, Netherlands

    André Krouwel

  56. Department of Digital Humanities, University of Helsinki, Helsinki, Finland

    Michael Laakasuo, Anton Berg, Marianna Drosinou, Volo Herzon, Mika Koverola, Anton Kunnari, Jussi Palomöki, Silva Perander & Jukka Sundvall

  57. Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria

    Claus Lamm & Jonas P. Nitschke

  58. School of Psychology, National Autonomous University of Mexico, Mexico City, Mexico

    Caroline Leygue & Octavio Salvador-Ginez

  59. Department of Economics, National Taiwan University, Taipei, Taiwan

    Ming-Jen Lin

  60. Center for Research in Econometric Theory and Applications, National Taiwan University, Taipei, Taiwan

    Ming-Jen Lin & Hans H. Tung

  61. Tribhuvan University, Kirtipur, Nepal

    Mohammad Sabbir Mansoor, Hom Nath Chalise, Ranju Lama Gurung, Apsara Katuwal Dangol, Madhavi Sharma & Pujan Sharma

  62. Department of Leadership and Organizational Behavior, BI Norwegian Business School, Oslo, Norway

    Lewend Mayiwar

  63. Institute of Security and Global Affairs, Leiden University, Leiden, Netherlands

    Honorata Mazepus

  64. Faculty of Governance and Global Affairs, Leiden University, Leiden, Netherlands

    Honorata Mazepus

  65. Department of Psychology, University of Limerick, Limerick, Ireland

    Cillian McHugh & Siobhán M. Griffin

  66. Department of Psychology, The University of Western Ontario, London, ON, Canada

    John Paul Minda & Clara Alexandra Stafford

  67. Center for Advanced Hindsight, Duke University, Durham, NC, USA

    Panagiotis Mitkidis

  68. Department of Clinical Neuroscience, Karolinska Institute, Solna, Sweden

    Andreas Olsson, Simon Jangard, Yafeng Pan, Philip Pärnamets & Joana B. Vieira

  69. Department of Management, University of Agder, Kristiansand, Norway

    Tobias Otterbring

  70. Institute of Retail Economics, Stockholm, Sweden

    Tobias Otterbring

  71. Department of Psychology, Lehigh University, Bethlehem, PA, USA

    Dominic J. Packer

  72. Department of Psychology, Monk Prayogshala, Mumbai, India

    Arathy Puthillam

  73. Faculty of Medicine, Pontifical Javeriana University, Bogotá, Colombia

    Hernando Santamaría-García, Mateo Andres Córdoba-Delgado & Juliana Molina-Paredes

  74. Department of Management, Technology, and Economics, ETH Zürich, Zürich, Switzerland

    Petra C. Schmid, Marie Crouzevialle & Robin Willardt

  75. Department of Psychiatry and Medical Psychology, Research Institute, Medical University of Plovdiv, Plovdiv, Bulgaria

    Drozdstoy Stoyanov

  76. Humanities and Social Sciences, Indian Institute of Management, Indore, India

    Shruti Tewari & Prasad Garladinne

  77. Institute of Social Sciences, Belgrade, Serbia

    Bojan Todosijević

  78. Department of Psychology, Royal Holloway, University of London, London, England

    Manos Tsakiris

  79. Center for the Politics of Feelings, School of Advanced Study, University of London, London, England

    Manos Tsakiris

  80. Department of Behavioral and Cognitive Sciences, Faculty of Humanities, Education and Social Sciences, University of Luxembourg, Luxembourg City, Luxembourg

    Manos Tsakiris

  81. Department of Political Science, National Taiwan University, Taipei, Taiwan

    Hans H. Tung

  82. Faculty of Political Science, National School for Political Studies and Public Administration, Bucharest, Romania

    Radu G. Umbres

  83. Department of Psychology, University of Latvia, Riga, Latvia

    Edmunds Vanags & Jānis Ekmanis

  84. Department of Psychology, Princeton University, Princeton, NJ, USA

    Madalina Vlasceanu

  85. Department of Psychology, Speech, and Hearing, University of Canterbury, Christchurch, New Zealand

    Andrew Vonasch, Jessica Gale & Kumar Yogeeswaran

  86. Department of Psychology and Neuroscience, Duke University, Durham, NC, USA

    Meltem Yucel

  87. Department of Psychology, University of Virginia, Charlottesville, VA, USA

    Meltem Yucel & Annalisa Myer

  88. School of Economics and Management, Hebei University of Technology, Tianjin, PR China

    Yucheng Zhang

  89. School of Collective Intelligence, Mohammed VI Polytechnic University, Ben Guerir, Morocco

    Mohcine Abad, Hamza Alaoui Mdarhri, Cathal O’Madagain & Brent Strickland

  90. Institute for Research and Development-Kurdistan, Middle East, Iraq

    Narin Akrawi

  91. Impact For Development, North Africa, Rabat, Morocco

    Hanane Amara, Soulaimane El Mimouni & Tarik Nesh-Nash

  92. Department of Psychology, University of Amsterdam, Amsterdam, Netherlands

    David M. Amodio, Ognjan Denkovski, David T. Schultner & Iris J. Traast

  93. Department of Psychology, Jose Rizal University, Mandaluyong, Philippines

    Benedict G. Antazo

  94. Department of Philosophy, University Cheikh Anta Diop, Dakar, Senegal

    Mouhamadou Hady Ba

  95. School of Medicine and Health Sciences, University of Rosario, Bogotá, Colombia

    Sergio Barbosa

  96. Moral Psychology and Decision Sciences Research Incubator, University of Rosario, Bogotá, Colombia

    Sergio Barbosa

  97. School of Psychological Sciences, University of Melbourne, Parkville, VIC, Australia

    Brock Bastian & Jeffrey P. Thomas

  98. Department of Psychological and Social Sciences, Penn State Abington, Abington, PA, USA

    Michael Bernstein

  99. Institute of Psychology, University of Wrocław, Wrocław, Poland

    Michał Białek

  100. IMT School for Advanced Studies Lucca, Lucca, Italy

    Ennio Bilancini & Roberto Di Paolo

  101. Department of Economics and Management, University of Florence, Florence, Italy

    Leonardo Boncinelli

  102. Department of Management, London School of Economics and Political Science, London, England

    Jonathan E. Booth & Chunyun Li

  103. Toulouse Business School, University of Toulouse, Toulouse, France

    Sylvie Borau

  104. Social Policy Institute of the Ministry of Labor, Family and Social Affairs of the Slovak Republic, Bratislava, Slovakia

    Ondrej Buchel

  105. The Institute for Sociology of the Slovak Academy of Sciences, Bratislava, Slovakia

    Ondrej Buchel

  106. Department of Psychology, Penn State University, University Park, PA, USA

    C. Daryl Cameron & Julian A. Scheffer

  107. Rock Ethics Institute, Penn State University, University Park, PA, USA

    C. Daryl Cameron

  108. Department of Psychology, Federal University of Santa Catarina, Florianópolis, Brazil

    Chrissie F. Carvalho

  109. Department of Economics, University of Bologna, Bologna, Italy

    Tatiana Celadin

  110. IUSS Cognitive Neuroscience (ICoN) Center, Institute for Advanced Study of Pavia, Pavia, Italy

    Chiara Cerami & Gaia C. Santi

  111. Cognitive Computational Neuroscience Research Unit, Neurological Institute Foundation Casimiro Mondino, Pavia, Italy

    Chiara Cerami & Chiara Crespi

  112. School of Psychology, Shenzhen University, Shenzhen, PR China

    Xiaojun Cheng

  113. Institute for Advanced Study in Toulouse, Université Toulouse 1 Capitole, Toulouse, France

    Jane Conway

  114. Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy

    Chiara Crespi

  115. Cracow University of Economics, Kraków, Poland

    Justyna Dabrowska

  116. UBC Sauder School of Business, University of British Columbia, Vancouver, BC, Canada

    Michael A. Daniels, Nathan A. Dhaliwal & Katherine White

  117. Psychology Department, University of California - Los Angeles, Los Angeles, CA, USA

    Pamala N. Dayley

  118. Laboratory of Psychology: Cognition, Behavior, and Communication (LP3C), Rennes 2 University, Rennes, France

    Sylvain Delouvée

  119. Laboratory of Social and Cognitive Psychology, Clermont Auvergne University, CNRS, Clermont-Ferrand, France

    Guillaume Dezecache

  120. Cavite State University-General Trias City Campus, Cavite, Philippines

    Alelie B. Diato

  121. Crawford School of Public Policy, Australian National University, Canberra, ACT, Australia

    Uwe Dulleck

  122. CESifo, University of Munich, Munich, Germany

    Uwe Dulleck

  123. Department of International Trade, Boğaziçi University, Istanbul, Turkey

    Arhan S. Ertan

  124. Hult International Business School Dubai, Dubai, UAE

    Ali Fenwick

  125. Department of Social Policy and Intervention, University of Oxford, Oxford, England

    Kristijan Fidanovski

  126. Department of Media and Communications, University of Sydney, Sydney, NSW, Australia

    Terry Flew

  127. Department of Psychiatry, University of the Witwatersrand, Johannesburg, South Africa

    Shona Fraser

  128. University of Bayreuth, Bayreuth, Germany

    Raymond Boadi Frempong & David Stadelmann

  129. Department of Psychology, University of Waterloo, Waterloo, ON, Canada

    Jonathan A. Fugelsang & Alexander Cameron Walker

  130. Department of Peace Studies, University of Bradford, Bradford, England

    Oussama Ghajjou

  131. Philosophy and Social Studies Department, Rethymno, Greece

    Theofilos Gkinopoulos

  132. Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Kurt Gray & Frank Kachanoff

  133. Department of Economics, Koc University, Istanbul, Turkey

    Mert Gümren

  134. Department of Media and Communication, City University of Hong Kong, Kowloon Tong, Hong Kong

    Guanxiong Huang

  135. University of Regensburg, Regensburg, Germany

    Matthias F. C. Hudecek

  136. Graduate School for Transnational Studies, Free University of Berlin, Berlin, Germany

    Oleksandra Keudel

  137. Department of Management and Engineering, Linköping University, Linköping, Sweden

    Lina Koppel & Gustav Tinghög

  138. Department of Psychology, University of Koblenz-Landau, Landau, Germany

    Emily Kubin

  139. Department of Psychology, University of Alberta, Edmonton, Canada

    Josh Leota, Kyle Nash & Andy Scott

  140. LMU Center for Leadership and People Management, Ludwig Maximilian University of Munich, Munich, Germany

    Eva Lermer

  141. Augsburg University for Applied Sciences, Augsburg, Germany

    Eva Lermer

  142. Baruch Ivcher School of Psychology, Reichman University, Herzliya, Israel

    Jonathan Levy

  143. Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland

    Jonathan Levy

  144. School of Psychology, Dublin City University, Dublin, Ireland

    Darragh McCashin

  145. University of Montana, Missoula, MT, USA

    Alexander L. Metcalf

  146. Graduate School of Human Sciences, Osaka University, Suita, Japan

    Asako Miura

  147. SEELE Neuroscience, Mexico City, Mexico

    César Monroy-Fonseca

  148. School of Psychology, University of Auckland, Auckland, New Zealand

    David Moreau

  149. Faculty of Economics, Maria Curie-Skłodowska University, Lublin, Poland

    Rafał Muda

  150. Department of Psychology, The City University of New York (CUNY) Graduate Center, New York, NY, USA

    Annalisa Myer

  151. Australian National Centre for the Public Awareness of Science, Australian National University, Canberra, ACT, Australia

    Matthew S. Nurse

  152. Department of Social Psychology, Graduate School of Humanities and Sociology, University of Tokyo, Tokyo, Japan

    Yohsuke Ohtsubo

  153. Department of Public Administration and Sociology, Erasmus University Rotterdam, Rotterdam, Netherlands

    Michal Onderco

  154. Center for Social Sciences, Hungarian Academy of Sciences Center of Excellence, Budapest, Hungary

    Zsófia Papp

  155. Institute of Psychology, University of Silesia, Katowice, Poland

    Mariola Paruzel-Czachura

  156. Complutense University in Madrid, Madrid, Spain

    Mariola Paruzel-Czachura

  157. Department of Psychology, University of Belgrade, Belgrade, Serbia

    Zoran Pavlović

  158. Universidad Nacional de Colombia, Sede de La Paz, La Paz, Colombia

    César Payán-Gómez

  159. Vidyasagar College For Women, Kolkata, India

    Rajib Prasad

  160. AGH University of Science and Technology, Kraków, Poland

    Joanna Pyrkosz-Pacyna

  161. Department of Computer Science, University of Colorado Boulder, Boulder, CO, USA

    Ali Raza

  162. Institute of Cognitive Science, University of Colorado Boulder, Boulder, CO, USA

    Ali Raza

  163. Stanford University, Stanford, CA, USA

    Kasey Rhee

  164. Department of Biology, University of Turku, Turku, Finland

    Teemu Saikkonen

  165. Cooperative University of Colombia, Bogotá, Colombia

    Natalia Santiago-Tovar

  166. Newcastle Business School, University of Newcastle, Callaghan, NSW, Australia

    David Savage

  167. Department of Global Economics and Management, University of Groningen, Groningen, Netherlands

    Ahmed Skali

  168. Brain and Mind Institute, University of Western Ontario, London, ON, Canada

    Clara Alexandra Stafford

  169. Western Interdisciplinary Research Building, University of Western Ontario, London, ON, Canada

    Clara Alexandra Stafford

  170. Department of Sociology, University of Belgrade, Belgrade, Serbia

    Dragan Stanojević

  171. Department of Psychology, Carleton University, Ottawa, ON, Canada

    Anna Stefaniak & Michael J. A. Wohl

  172. National University of Political Studies and Public Administration (SNSPA), Bucharest, Romania

    Augustin Stoica

  173. Research Institute at Medical University of Plovdiv), Division of Translational Neuroscience, Plovdiv, Bulgaria

    Kristina K. Stoyanova

  174. Department of Cognitive Science, ENS, EHESS, CNRS, Institut Jean Nicod, PSL Research University, Paris, France

    Brent Strickland

  175. CREMA - Center for Research in Economics, Management and the Arts, Basel, Switzerland

    Benno Torgler

  176. The Warburg Institute, School of Advanced Study, University of London, London, England

    Raffaele Tucciarelli

  177. Institute of Cognitive Neuroscience, University College London, London, England

    Raffaele Tucciarelli

  178. Institute for Emerging Market Studies, The Hong Kong University of Science and Technology, Kowloon, Hong Kong

    Michael Tyrala

  179. Department of Psychology, Susquehanna University, Selinsgrove, PA, USA

    Nick D. Ungson

  180. Psychology Department, Dokuz Eylül University, İzmir, Turkey

    Mete S. Uysal

  181. Department of Experimental and Applied Psychology, VU Amsterdam, Amsterdam, Netherlands

    Paul A. M. Van Lange & Jan-Willem van Prooijen

  182. Faculty of Design Sciences, University of Antwerp, Antwerpen, Belgium

    Dirk van Rooy

  183. Department of Behavioural Sciences and Learning (IBL), Linköping University, Linköping, Sweden

    Daniel Västfjäll

  184. Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, Netherlands

    Peter Verkoeijen & Rolf A. Zwaan

  185. University of Koblenz-Landau, Landau, Germany

    Christian von Sikorski

  186. Health Communication Research Unit, School of Human and Community Development, University of the Witwatersrand, Johannesburg, South Africa

    Jennifer Watermeyer

  187. Department of Entrepreneurship, Innovation, and Technology, Stockholm School of Economics, Stockholm, Sweden

    Erik Wetter

  188. Harvard Business School, Harvard University, Cambridge, MA, USA

    Ashley Whillans

  189. Nicolaus Copernicus University, Toruń, Poland

    Adrian Dominik Wójcik

  190. University of California, San Diego, La Jolla, CA, USA

    Kaidi Wu

  191. Kyushu University, Fukuoka, Japan

    Yuki Yamada

  192. Department of Psychology, Kadir Has University, Istanbul, Turkey

    Onurcan Yilmaz

Authors

  1. Flavio Azevedo
  2. Tomislav Pavlović
  3. Gabriel G. Rêgo
  4. F. Ceren Ay
  5. Biljana Gjoneska
  6. Tom W. Etienne
  7. Robert M. Ross
  8. Philipp Schönegger
  9. Julián C. Riaño-Moreno
  10. Aleksandra Cichocka
  11. Valerio Capraro
  12. Luca Cian
  13. Chiara Longoni
  14. Ho Fai Chan
  15. Jay J. Van Bavel
  16. Hallgeir Sjåstad
  17. John B. Nezlek
  18. Mark Alfano
  19. Michele J. Gelfand
  20. Michèle D. Birtel
  21. Aleksandra Cislak
  22. Patricia L. Lockwood
  23. Koen Abts
  24. Elena Agadullina
  25. John Jamir Benzon Aruta
  26. Sahba Nomvula Besharati
  27. Alexander Bor
  28. Becky L. Choma
  29. Charles David Crabtree
  30. William A. Cunningham
  31. Koustav De
  32. Waqas Ejaz
  33. Christian T. Elbaek
  34. Andrej Findor
  35. Daniel Flichtentrei
  36. Renata Franc
  37. June Gruber
  38. Estrella Gualda
  39. Yusaku Horiuchi
  40. Toan Luu Duc Huynh
  41. Agustin Ibanez
  42. Mostak Ahamed Imran
  43. Jacob Israelashvili
  44. Katarzyna Jasko
  45. Jaroslaw Kantorowicz
  46. Elena Kantorowicz-Reznichenko
  47. André Krouwel
  48. Michael Laakasuo
  49. Claus Lamm
  50. Caroline Leygue
  51. Ming-Jen Lin
  52. Mohammad Sabbir Mansoor
  53. Antoine Marie
  54. Lewend Mayiwar
  55. Honorata Mazepus
  56. Cillian McHugh
  57. John Paul Minda
  58. Panagiotis Mitkidis
  59. Andreas Olsson
  60. Tobias Otterbring
  61. Dominic J. Packer
  62. Anat Perry
  63. Michael Bang Petersen
  64. Arathy Puthillam
  65. Tobias Rothmund
  66. Hernando Santamaría-García
  67. Petra C. Schmid
  68. Drozdstoy Stoyanov
  69. Shruti Tewari
  70. Bojan Todosijević
  71. Manos Tsakiris
  72. Hans H. Tung
  73. Radu G. Umbres
  74. Edmunds Vanags
  75. Madalina Vlasceanu
  76. Andrew Vonasch
  77. Meltem Yucel
  78. Yucheng Zhang
  79. Mohcine Abad
  80. Eli Adler
  81. Narin Akrawi
  82. Hamza Alaoui Mdarhri
  83. Hanane Amara
  84. David M. Amodio
  85. Benedict G. Antazo
  86. Matthew Apps
  87. Mouhamadou Hady Ba
  88. Sergio Barbosa
  89. Brock Bastian
  90. Anton Berg
  91. Maria P. Bernal-Zárate
  92. Michael Bernstein
  93. Michał Białek
  94. Ennio Bilancini
  95. Natalia Bogatyreva
  96. Leonardo Boncinelli
  97. Jonathan E. Booth
  98. Sylvie Borau
  99. Ondrej Buchel
  100. C. Daryl Cameron
  101. Chrissie F. Carvalho
  102. Tatiana Celadin
  103. Chiara Cerami
  104. Hom Nath Chalise
  105. Xiaojun Cheng
  106. Kate Cockcroft
  107. Jane Conway
  108. Mateo Andres Córdoba-Delgado
  109. Chiara Crespi
  110. Marie Crouzevialle
  111. Jo Cutler
  112. Marzena Cypryańska
  113. Justyna Dabrowska
  114. Michael A. Daniels
  115. Victoria H. Davis
  116. Pamala N. Dayley
  117. Sylvain Delouvée
  118. Ognjan Denkovski
  119. Guillaume Dezecache
  120. Nathan A. Dhaliwal
  121. Alelie B. Diato
  122. Roberto Di Paolo
  123. Marianna Drosinou
  124. Uwe Dulleck
  125. Jānis Ekmanis
  126. Arhan S. Ertan
  127. Hapsa Hossain Farhana
  128. Fahima Farkhari
  129. Harry Farmer
  130. Ali Fenwick
  131. Kristijan Fidanovski
  132. Terry Flew
  133. Shona Fraser
  134. Raymond Boadi Frempong
  135. Jonathan A. Fugelsang
  136. Jessica Gale
  137. E. Begoña Garcia-Navarro
  138. Prasad Garladinne
  139. Oussama Ghajjou
  140. Theofilos Gkinopoulos
  141. Kurt Gray
  142. Siobhán M. Griffin
  143. Bjarki Gronfeldt
  144. Mert Gümren
  145. Ranju Lama Gurung
  146. Eran Halperin
  147. Elizabeth Harris
  148. Volo Herzon
  149. Matej Hruška
  150. Guanxiong Huang
  151. Matthias F. C. Hudecek
  152. Ozan Isler
  153. Simon Jangard
  154. Frederik J. Jorgensen
  155. Frank Kachanoff
  156. John Kahn
  157. Apsara Katuwal Dangol
  158. Oleksandra Keudel
  159. Lina Koppel
  160. Mika Koverola
  161. Emily Kubin
  162. Anton Kunnari
  163. Yordan Kutiyski
  164. Oscar Moreda Laguna
  165. Josh Leota
  166. Eva Lermer
  167. Jonathan Levy
  168. Neil Levy
  169. Chunyun Li
  170. Elizabeth U. Long
  171. Marina Maglić
  172. Darragh McCashin
  173. Alexander L. Metcalf
  174. Igor Mikloušić
  175. Soulaimane El Mimouni
  176. Asako Miura
  177. Juliana Molina-Paredes
  178. César Monroy-Fonseca
  179. Elena Morales-Marente
  180. David Moreau
  181. Rafał Muda
  182. Annalisa Myer
  183. Kyle Nash
  184. Tarik Nesh-Nash
  185. Jonas P. Nitschke
  186. Matthew S. Nurse
  187. Yohsuke Ohtsubo
  188. Victoria Oldemburgo de Mello
  189. Cathal O’Madagain
  190. Michal Onderco
  191. M. Soledad Palacios-Galvez
  192. Jussi Palomöki
  193. Yafeng Pan
  194. Zsófia Papp
  195. Philip Pärnamets
  196. Mariola Paruzel-Czachura
  197. Zoran Pavlović
  198. César Payán-Gómez
  199. Silva Perander
  200. Michael Mark Pitman
  201. Rajib Prasad
  202. Joanna Pyrkosz-Pacyna
  203. Steve Rathje
  204. Ali Raza
  205. Kasey Rhee
  206. Claire E. Robertson
  207. Iván Rodríguez-Pascual
  208. Teemu Saikkonen
  209. Octavio Salvador-Ginez
  210. Gaia C. Santi
  211. Natalia Santiago-Tovar
  212. David Savage
  213. Julian A. Scheffer
  214. David T. Schultner
  215. Enid M. Schutte
  216. Andy Scott
  217. Madhavi Sharma
  218. Pujan Sharma
  219. Ahmed Skali
  220. David Stadelmann
  221. Clara Alexandra Stafford
  222. Dragan Stanojević
  223. Anna Stefaniak
  224. Anni Sternisko
  225. Augustin Stoica
  226. Kristina K. Stoyanova
  227. Brent Strickland
  228. Jukka Sundvall
  229. Jeffrey P. Thomas
  230. Gustav Tinghög
  231. Benno Torgler
  232. Iris J. Traast
  233. Raffaele Tucciarelli
  234. Michael Tyrala
  235. Nick D. Ungson
  236. Mete S. Uysal
  237. Paul A. M. Van Lange
  238. Jan-Willem van Prooijen
  239. Dirk van Rooy
  240. Daniel Västfjäll
  241. Peter Verkoeijen
  242. Joana B. Vieira
  243. Christian von Sikorski
  244. Alexander Cameron Walker
  245. Jennifer Watermeyer
  246. Erik Wetter
  247. Ashley Whillans
  248. Katherine White
  249. Rishad Habib
  250. Robin Willardt
  251. Michael J. A. Wohl
  252. Adrian Dominik Wójcik
  253. Kaidi Wu
  254. Yuki Yamada
  255. Onurcan Yilmaz
  256. Kumar Yogeeswaran
  257. Carolin-Theresa Ziemer
  258. Rolf A. Zwaan
  259. Paulo S. Boggio
  260. Waldir M. Sampaio

Contributions

Conceptualization: F.A. Data curation: F.A., T.P., W.M.S. and G.R. Formal analysis: F.A., F.C.A., T.P., T.E. and J.C.R. Investigation: F.A. Methodology: F.A. Project administration: F.A. Resources: F.A. Software: F.A. and T.P. Supervision: F.A. Validation: F.A. and R.M.R. Visualization: F.A., F.C.A., T.E., H.F.C., L.C., C.L. and J.C.R. Writing - original draft: F.A., B.G., R.M.R. and P.S. Writing - review & editing: ICSMP Collaborators.

Corresponding author

Correspondence to Flavio Azevedo.

Ethics declarations

Competing interests

André Krouwel (ownership and stocks in Kieskompas BV, a data collector in this project). No payment was received by the author. No other authors reported a competing interest.

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Azevedo, F., Pavlović, T., Rêgo, G.G. et al. Social and moral psychology of COVID-19 across 69 countries. Sci Data 10, 272 (2023). https://doi.org/10.1038/s41597-023-02080-8

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  • Received: 31 May 2022

  • Accepted: 16 March 2023

  • Published: 11 May 2023

  • DOI: https://doi.org/10.1038/s41597-023-02080-8

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{
  "url": "https://www.nature.com/articles/s41597-023-02080-8",
  "title": "Social and moral psychology of COVID-19 across 69 countries - Scientific Data",
  "description": "Background & SummaryWell over two years after the official outbreak1, it is evident that the COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of...",
  "links": [
    "https://www.nature.com/articles/s41597-023-02080-8"
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  "image": "https://media.springernature.com/m685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig1_HTML.png",
  "content": "<div>\n                        <div><h2 id=\"Sec1\">Background &amp; Summary</h2><div><p>Well over two years after the official outbreak<sup><a target=\"_blank\" title=\"Cucinotta, D. &amp; Vanelli, M. Who declares COVID-19 a pandemic. Acta Biomed. 91, 157 (2020).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR1\">1</a></sup>, it is evident that the COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies<sup><a target=\"_blank\" title=\"Nicola, M. et al. The socio-economic implications of the coronavirus and COVID-19 pandemic: A review. Int. J. Surg. (2020).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR2\">2</a></sup> as well as people’s physical and mental health<sup><a target=\"_blank\" title=\"Holmes, E. A. et al. Multidisciplinary research priorities for the COVID-19 pandemic: A call for action for mental health science. The Lancet Psychiatry (2020).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR3\">3</a></sup>. At the time of writing, the world reached 850 million confirmed infections and up to 18 million deaths<sup><a target=\"_blank\" title=\"Adam, D. et al. Covid’s true death toll: Much higher than official records. Nature 603, 562–562 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR4\">4</a></sup>. The detrimental effects of the pandemic extend beyond physical health with evidence of increased stress levels<sup><a target=\"_blank\" title=\"Yamada, Y. et al. COVIDiSTRESS global survey dataset on psychological and behavioural consequences of the COVID-19 outbreak. Sci. Data. 8, 1–23 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR5\">5</a></sup> and suicide rates<sup><a target=\"_blank\" title=\"John, A. et al. The impact of the COVID-19 pandemic on self-harm and suicidal behaviour: A living systematic review. F1000Research 9, 1097 (2020).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR6\">6</a></sup>, along with deterioration of general well-being<sup><a target=\"_blank\" title=\"Serafini, G. et al. The psychological impact of COVID-19 on the mental health in the general population. QJM 113, 531–537 (2020).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR7\">7</a></sup>. Such findings reflect the cautionary warnings by Taylor<sup><a target=\"_blank\" title=\"Taylor, S. The psychology of pandemics: Preparing for the next global outbreak of infectious disease (Cambridge Scholars Publishing, Newcastle upon Tyne, 2019).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR8\">8</a></sup> that the psychological and societal effects are “likely to be more pronounced, more widespread, and longer-lasting than the purely somatic effects of the infection”<sup><a target=\"_blank\" title=\"Taylor, S. The psychology of pandemics: Preparing for the next global outbreak of infectious disease (Cambridge Scholars Publishing, Newcastle upon Tyne, 2019).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR8\">8</a></sup>, p.23.</p><p>In the early stages of the pandemic, when vaccines were not yet available, governments introduced non-pharmaceutical interventions to reduce the spread of the SARS-CoV-2 virus<sup><a target=\"_blank\" title=\"Haug, N. et al. Ranking the effectiveness of worldwide COVID-19 government interventions. Nat. Hum. Behav. 4, 1303–1312 (2020).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR9\">9</a></sup>. Various contact-restricting policies (e.g., stay-at-home recommendations, curfews, police hours, partial or complete lock-downs) were enacted, and citizens were advised to adhere to public health recommendations (e.g., hand washing, face masks, and spatial distancing). It quickly became clear that behavioural science had a major role to play<sup><a target=\"_blank\" title=\"Van Bavel, J. J. et al. Using social and behavioural science to support COVID-19 pandemic response. Nature Human Behaviour 4, 460–471 (2020).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR10\">10</a></sup>.</p><p>On April 11th, a team of researchers launched a call for international collaboration in social and moral psychology. The initiative quickly gained momentum, gathering a consortium of over 250 academics worldwide. The aim of this project was to collect data from as many countries as possible to serve as a public good for the scientific community by allowing future research to draw on this broad database collected during this early phase of the COVID-19 pandemic. The survey, developed by the initial team, was circulated among the national teams, who provided feedback, translated it into 32 languages, and disseminated it online. The project concluded with responses from a total of 51,404 participants from 69 countries, 77 samples, between April 22nd and June 3rd, 2020.</p><p>A key goal of the project was to test the hypothesis that national identity predicts support for public health measures during the COVID-19 pandemic, which has since been confirmed<sup><a target=\"_blank\" title=\"Van Bavel, J. J. et al. National identity predicts public health support during a global pandemic. Nature Communications 13, 517 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR11\">11</a>,<a target=\"_blank\" title=\"Pavlović, T. et al. Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning. PNAS Nexus 1, \n                  https://doi.org/10.1093/pnasnexus/pgac093\n                 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR12\">12</a></sup>. In addition to collecting variables to test this hypothesis, we collected data on a variety of other social and moral constructs to make of our multi-country large-scale survey a rich resource for future research. The survey focused on the following areas: on a) COVID-19 beliefs and compliance behaviours (COVID-19 public health support, COVID-19 risk perception, COVID-19 conspiracy beliefs, and COVID-19 testing behaviour); b) identity and social attitudes (national identification, national narcissism, and social belonging); c) ideology (political ideology); d) health and well-being (subjective physical health, a wealth ladder ranking, and psychological well-being); e) moral beliefs and motivation (generosity, morality as cooperation, moral identity, and moral circle); f) personality traits and dispositions (open-mindedness, self-esteem, trait optimism, trait self-control, narcissism, and cognitive reflection); and g) demographic variables (i.e., sex, age, marital status, number of children, and employment status).</p><p>Using this dataset, project team members have pre-registered a variety of secondary hypotheses (see <a target=\"_blank\" href=\"https://icsmp-covid19.netlify.app/preregistration.html\">icsmp-covid19.netlify.app/preregistration</a>), several of which have already been published<sup><a target=\"_blank\" title=\"Van Bavel, J. J. et al. National identity predicts public health support during a global pandemic. Nature Communications 13, 517 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR11\">11</a>,<a target=\"_blank\" title=\"Pavlović, T. et al. Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning. PNAS Nexus 1, \n                  https://doi.org/10.1093/pnasnexus/pgac093\n                 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR12\">12</a>,<a target=\"_blank\" title=\"Sternisko, A., Cichocka, A., Cislak, A. &amp; Van Bavel, J. J. National narcissism predicts the belief in and the dissemination of conspiracy theories during the COVID-19 pandemic: Evidence from 56 countries. Personality and Social Psychology Bulletin 01461672211054947 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR13\">13</a>,<a target=\"_blank\" title=\"Cichocka, A. et al. Globalization is associated with lower levels of national narcissism: Evidence from 56 countries. Social Psychological and Personality Science (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR14\">14</a>,<a target=\"_blank\" title=\"Nurse, M. S., Ross, R. M., Isler, O. &amp; Van Rooy, D. Analytic thinking predicts accuracy ratings and willingness to share covid-19 misinformation in Australia. Memory &amp; Cognition 50, 425–434 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR15\">15</a>,<a target=\"_blank\" title=\"McHugh, C. et al. Moral identity predicts adherence to COVID-19 mitigation procedures depending on political ideology: A comparison between the USA and New Zealand. Political Psychology. Ahead of print (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR16\">16</a>,<a target=\"_blank\" title=\"Maglić, M., Pavlović, T. &amp; Franc, R. Analytic thinking and political orientation in the corona crisis. Frontiers in psychology 2711 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR17\">17</a>,<a target=\"_blank\" title=\"Gkinopoulos, T., Elbæk, C. T. &amp; Mitkidis, P. Morality in the echo chamber: The relationship between belief in COVID-19 conspiracy theories and public health support and the mediating role of moral identity and morality-as-cooperation across 67 countries. PLOS ONE 17, e0273172 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR18\">18</a>,<a target=\"_blank\" title=\"Borau, S., Couprie, H. &amp; Hopfensitz, A. The prosociality of married people: Evidence from a large multinational sample. Journal of Economic Psychology 92, 102545 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR19\">19</a>,<a target=\"_blank\" title=\"Bonetto, E., Delouvée, S., Mahfud, Y. &amp; Adam-Troian, J. National identification, a social cure for COVID-19? Evidence from 67 countries. International Journal of Social Psychiatry 68, 1116–1126 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR20\">20</a>,<a target=\"_blank\" title=\"Cutler, J., Nitschke, J. P., Lamm, C. &amp; Lockwood, P. L. Older adults across the globe exhibit increased prosocial behavior but also greater in-group preferences. Nature Aging 1, 880–888 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR21\">21</a>,<a target=\"_blank\" title=\"Gualda, E. et al. Social distancing and COVID-19: Factors associated with compliance with social distancing norms in Spain. Frontiers in Psychology 12 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR22\">22</a>,<a target=\"_blank\" title=\"Pan, Y. et al. Psychological well-being is associated with prosociality during the COVID-19 pandemic: A comparison of Swedish and Chinese samples. Emotion. Advance online publication at \n                  https://doi.org/10.1037/emo0001121\n                 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR23\">23</a></sup>. In this paper, we present the complete ICSMP datasets to facilitate its findability, accessibility, interoperability, and reuse (FAIR;<sup><a target=\"_blank\" title=\"Wilkinson, M. D. et al. The fair guiding principles for scientific data management and stewardship. Scientific data 3, 1–9 (2016).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR24\">24</a>,<a target=\"_blank\" title=\"Parsons, S. et al. A community-sourced glossary of open scholarship terms. Nature human behaviour 6, 312–318 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR25\">25</a></sup>) and maximize its educational impact<sup><a target=\"_blank\" title=\"Pownall, M. et al. Embedding open and reproducible science into teaching: A bank of lesson plans and resources. Scholarship of Teaching and Learning in Psychology. \n                  https://doi.org/10.1037/stl0000307\n                 (2021). Advance online publication at.\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR26\">26</a>,<a target=\"_blank\" title=\"Pownall, M. et al. Teaching Open and Reproducible Scholarship: A Critical Review of the Evidence Base for Current Pedagogical Methods and their Outcomes. Preprint at \n                  https://doi.org/10.31222/osf.io/9e526\n                 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR27\">27</a>,<a target=\"_blank\" title=\"Azevedo, F. et al. Introducing a framework for open and reproducible research training (FORRT). OSF Preprints. Preprint at \n                  https://doi.org/10.31219/osf.io/bnh7p\n                 (2019).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR28\">28</a></sup>.</p></div></div><div><h2 id=\"Sec2\">Methods</h2><div><p>When possible, we used articles published in Nature Scientific Data presenting social sciences data as blueprints<sup><a target=\"_blank\" title=\"Yamada, Y. et al. COVIDiSTRESS global survey dataset on psychological and behavioural consequences of the COVID-19 outbreak. Sci. Data. 8, 1–23 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR5\">5</a>,<a target=\"_blank\" title=\"Jong, J. et al. Traumatic life experiences and religiosity in eight countries. Scientific data 7, 1–8 (2020).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR29\">29</a></sup>. Given the urgent call for COVID-19 research, this study received an umbrella ethical approval from the University of Kent (see <a target=\"_blank\" href=\"https://osf.io/ce638/\">osf.io/ce638</a>) but also complied with local ethics, norms, and regulations in the countries where the data were collected.</p><h3 id=\"Sec3\">Participants</h3><p>A total of 51,404 individuals from 77 samples across 69 countries participated in our survey. The inclusion criteria were the following: being 18 years of age and older, and giving informed consent (although researchers were encouraged to, ideally, recruit representative samples regarding age and gender). Data were collected between April 22nd and June 3rd, 2020. Figure <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Fig1\">1</a> displays <i>where</i> the data were collected, coloured according to national sample size. Figure <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Fig2\">2</a> displays the proportion of respondents in relation to the full sample. Figure <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Fig3\">3</a> shows <i>when</i> the data were collected in each country.</p><div><figure><figcaption><b>Fig. 1</b></figcaption><div><div><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/1\"><picture><source type=\"image/webp\" srcset=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig1_HTML.png?as=webp\"></source><img src=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig1_HTML.png\" alt=\"figure 1\" /></picture></a></div><p>A world map visualizing the number of participants in each surveyed country. <b><i>Note:</i></b> This heat map shows the number of respondents from each country. The gray areas are the countries that are not covered by the data, and the colour scale shows the size of the sample in accordance with the scale on the lower left side.</p></div><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/1\"><span>Full size image</span></a></p></figure></div><div><figure><figcaption><b>Fig. 2</b></figcaption><div><div><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/2\"><picture><source type=\"image/webp\" srcset=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig2_HTML.png?as=webp\"></source><img src=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig2_HTML.png\" alt=\"figure 2\" /></picture></a></div><p>International Collaboration on the Social and Moral Psychology of COVID-19: Investigated constructs, items and variables.</p></div><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/2\"><span>Full size image</span></a></p></figure></div><div><figure><figcaption><b>Fig. 3</b></figcaption><div><div><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/3\"><picture><source type=\"image/webp\" srcset=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig3_HTML.png?as=webp\"></source><img src=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig3_HTML.png\" alt=\"figure 3\" /></picture></a></div><p>Gantt Chart illustrating the data collection periods for each surveyed country.</p></div><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/3\"><span>Full size image</span></a></p></figure></div><p>Demographic variables across countries are summarised in several tables: Tables <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab1\">1</a>, <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab2\">2</a> show the number of participants, the mean proportion of non-missing ‘valid’ answers, and age. Tables <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab3\">3</a>, <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab4\">4</a> illustrate the distribution of gender; Tables <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab5\">5</a>, <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab6\">6</a> show employment status; and Tables <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab7\">7</a>–<a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab9\">9</a> show marital status and number of children. When multiple samples were collected within the same country, data were split into numbered subgroups (e.g., for Brazil, which has three samples, they were flagged as Brazil_1, Brazil_2 and Brazil_3). Note that in the tables above, we kept country subsamples separated to highlight they were collected by different teams, often using different sampling methodologies or languages, which impact their characteristics (e.g., representativeness).</p><div><figure><figcaption><b>Table 1 Sample size, average proportion of valid answers, age of respondents and the number of data collections in 69 countries (A-M).</b></figcaption><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/tables/1\"><span>Full size table</span></a></p></figure></div><div><figure><figcaption><b>Table 2 Sample size, average proportion of valid answers, age of respondents and the number of data collections in 69 countries (N-V).</b></figcaption><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/tables/2\"><span>Full size table</span></a></p></figure></div><div><figure><figcaption><b>Table 3 Distribution of sex in 69 countries (A-M).</b></figcaption><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/tables/3\"><span>Full size table</span></a></p></figure></div><div><figure><figcaption><b>Table 4 Distribution of sex in 69 countries (N-V).</b></figcaption><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/tables/4\"><span>Full size table</span></a></p></figure></div><div><figure><figcaption><b>Table 5 Distribution of employment status in 69 countries (A-M).</b></figcaption><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/tables/5\"><span>Full size table</span></a></p></figure></div><div><figure><figcaption><b>Table 6 Distribution of employment status in 69 countries (N-V).</b></figcaption><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/tables/6\"><span>Full size table</span></a></p></figure></div><div><figure><figcaption><b>Table 7 Distribution of marital status and number of children in 69 countries (A-H).</b></figcaption><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/tables/7\"><span>Full size table</span></a></p></figure></div><div><figure><figcaption><b>Table 8 Distribution of marital status and number of children in 69 countries (I-R).</b></figcaption><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/tables/8\"><span>Full size table</span></a></p></figure></div><div><figure><figcaption><b>Table 9 Distribution of marital status and number of children in 69 countries (S-V).</b></figcaption><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/tables/9\"><span>Full size table</span></a></p></figure></div><p>For the most part, participants were recruited via professional survey research companies and were incentivised to participate. In countries that, to our knowledge, did not possess polling infrastructure<sup><a target=\"_blank\" title=\"Azevedo, F. et al. An international investigation of the psychology of COVID-19. Behavioural and Social Sciences at Nature Portfolio. Blog post at \n                  https://go.nature.com/3JtupRd\n                 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR30\">30</a></sup>, incentivising participants was not feasible. To collect data in these countries, leaders of national teams relied on online volunteers recruited via media appeals, mailing lists, advertisements on news aggregators, local communities and bloggers, and private messaging apps such as WhatsApp or WeChat.</p><h3 id=\"Sec4\">Materials</h3><p>The measures we used are illustrated in Figs. <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Fig4\">4</a>, <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Fig5\">5</a> along with the specific items listed for each measure. In most cases, participants’ responses were collected on a scale from 0 = ‘strongly disagree’ to 10 = ‘strongly agree’, with 5 = ‘neither disagree nor agree’. In some cases, when more appropriate, we used other response scales (e.g., the generosity measure, where a 0–100% response scale was applied to hypothetical donations). In total, we collected 98 unique variables and meta-data. To ensure participants’ anonymity, no data that would allow their identification were collected.</p><div><figure><figcaption><b>Fig. 4</b></figcaption><div><div><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/4\"><picture><source type=\"image/webp\" srcset=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig4_HTML.png?as=webp\"></source><img src=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig4_HTML.png\" alt=\"figure 4\" /></picture></a></div><p>International Collaboration on the Social and Moral Psychology of COVID-19: Investigated constructs, items and variables.</p></div><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/4\"><span>Full size image</span></a></p></figure></div><div><figure><figcaption><b>Fig. 5</b></figcaption><div><div><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/5\"><picture><source type=\"image/webp\" srcset=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig5_HTML.png?as=webp\"></source><img src=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig5_HTML.png\" alt=\"figure 5\" /></picture></a></div><p>International Collaboration on the Social and Moral Psychology of COVID-19: Investigated constructs, items and variables.</p></div><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/5\"><span>Full size image</span></a></p></figure></div><h4 id=\"Sec5\">COVID-19 Beliefs and compliance</h4><p>Four constructs: COVID-19 public health support, COVID-19 risk perception, COVID-19 conspiracy theory beliefs, and COVID-19 testing behaviour. The public health support construct, in turn, is composed of three measures: spatial distancing, physical hygiene, and policy support. These are ad-hoc scales that we developed ourselves.</p><h4 id=\"Sec6\">Identity and social attitudes</h4><p>Three constructs: national identification<sup><a target=\"_blank\" title=\"Postmes, T., Haslam, S. A. &amp; Jans, L. A single-item measure of social identification: Reliability, validity, and utility. Br. J. Soc. Psychol. 52, 597–617 (2013).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR31\">31</a></sup>, national narcissism<sup><a target=\"_blank\" title=\"de Zavala, A. G., Cichocka, A., Eidelson, R. &amp; Jayawickreme, N. Collective narcissism and its social consequences. Journal of Personality and Social Psychology 97, 1074–1096 (2009).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR32\">32</a></sup>, and social belonging<sup><a target=\"_blank\" title=\"Malone, G. P., Pillow, D. R. &amp; Osman, A. The general belongingness scale (GBS): Assessing achieved belongingness. Personality and Individual Differences 52, 311–316 (2012).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR33\">33</a></sup>.</p><h4 id=\"Sec7\">Ideology</h4><p>One construct: political ideology. Participants self-reported their political orientation according to a single item on a scale from 0 (“Very left-leaning”) to 10 (“Very right-leaning”). This measure has been shown to account for a significant proportion of the variance in voting intentions in American presidential elections between 1972 and 2004<sup><a target=\"_blank\" title=\"Jost, J. T. The end of the end of ideology. American Psychologist 61, 651–670 (2006).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR34\">34</a></sup> and 2016<sup><a target=\"_blank\" title=\"Azevedo, F., Jost, J. T., Rothmund, T. &amp; Sterling, J. Neoliberal ideology and the justification of inequality in capitalist societies: Why social and economic dimensions of ideology are intertwined. Journal of Social Issues 75, 49–88 (2019).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR35\">35</a>,<a target=\"_blank\" title=\"Azevedo, F., Jost, J. T. &amp; Rothmund, T. “making america great again”: System justification in the us presidential election of 2016. Translational Issues in Psychological Science 3, 231 (2017).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR36\">36</a>,<a target=\"_blank\" title=\"Azevedo, F. &amp; Jost, J. T. The ideological basis of antiscientific attitudes: Effects of authoritarianism, conservatism, religiosity, social dominance, and system justification. Group Processes &amp; Intergroup Relations 24, 518–549 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR37\">37</a></sup>. In fact, using a single-item scale to measure political ideology has been a common practice in political psychology literature, providing substantive evidence for the validity of the measure both across national and international research<sup><a target=\"_blank\" title=\"Imhoff, R. et al. Conspiracy mentality and political orientation across 26 countries. Nature Human Behaviour 6, 392–403 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR38\">38</a>,<a target=\"_blank\" title=\"Van der Linden, S., Panagopoulos, C., Azevedo, F. &amp; Jost, J. T. The paranoid style in american politics revisited: An ideological asymmetry in conspiratorial thinking. Political Psychology 42, 23–51 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR39\">39</a></sup>. However, even if the symbolic ideology can be a useful and parsimonious instrument to study political attitudes, when interpreting results, users should be attentive to the political and cultural applicability, psychometric validity, and generalisability of measures of political ideology<sup><a target=\"_blank\" title=\"Azevedo, F. &amp; Bolesta, D. Measuring ideology: Current practices, consequences, and recommendations. Manuscript in preparation (forthcoming). Preprint at \n                  https://measuring.ideology.flavioazevedo.com\n                .\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR40\">40</a>,<a target=\"_blank\" title=\"Azevedo, F., Marques, T. &amp; Micheli, L. In pursuit of racial equality: Identifying the determinants of support for the black lives matter movement with a systematic review and multiple meta-analyses. Perspectives on Politics 1–23 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR41\">41</a>,<a target=\"_blank\" title=\"Azevedo, F., Bolesta, D. &amp; Micheli, L. Does stereotype threat contribute to the political knowledge gender gap? a preregistered replication study of ihme and tausendpfund. Journal of Experimental Political Science (in press) (2018).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR42\">42</a></sup>.</p><h4 id=\"Sec8\">Health and well-being</h4><p>Three constructs: subjective physical health, wealth ladder, and psychological well-being. Each of these scales relied on well-validated instruments<sup><a target=\"_blank\" title=\"Pinquart, M. Correlates of subjective health in older adults: a meta-analysis. Psychology and Aging 16, 414–426 (2001).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR43\">43</a>,<a target=\"_blank\" title=\"Adler, N. E., Epel, E. S., Castellazzo, G. &amp; Ickovics, J. R. Relationship of subjective and objective social status with psychological and physiological functioning: Preliminary data in healthy, white women. Health psychology 19, 586 (2000).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR44\">44</a>,<a target=\"_blank\" title=\"Bjørnskov, C. How comparable are the gallup world poll life satisfaction data? J. Happiness Stud. 11, 41–60 (2010).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR45\">45</a></sup>.</p><h4 id=\"Sec9\">Moral beliefs and motivation</h4><p>Four constructs: generosity<sup><a target=\"_blank\" title=\"Sjåstad, H. Short-sighted greed? focusing on the future promotes reputation-based generosity. Judgm. Decis. Mak 14, 199–213 (2019).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR46\">46</a></sup>, morality as cooperation<sup><a target=\"_blank\" title=\"Curry, O. S., Chesters, M. J. &amp; Van Lissa, C. J. Mapping morality with a compass: Testing the theory of ‘morality-as-cooperation’ with a new questionnaire. J. Res. Pers. 78, 106–124 (2019).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR47\">47</a></sup>, moral identity<sup><a target=\"_blank\" title=\"Aquino, K. &amp; Reed, A. II The self-importance of moral identity. J. Pers. Soc. Psychol. 83, 1423 (2002).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR48\">48</a></sup>, and moral circle<sup><a target=\"_blank\" title=\"Waytz, A., Iyer, R., Young, L., Haidt, J. &amp; Graham, J. Ideological differences in the expanse of the moral circle. Nat. Commun. 10, 1–12 (2019).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR49\">49</a></sup>.</p><h4 id=\"Sec10\">Personality traits</h4><p>Six constructs: open-mindedness<sup><a target=\"_blank\" title=\"Alfano, M. et al. Development and validation of a multi-dimensional measure of intellectual humility. PloS ONE 12, e0182950 (2017).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR50\">50</a></sup>, self-esteem<sup><a target=\"_blank\" title=\"Scheier, M. F., Carver, C. S. &amp; Bridges, M. W. Distinguishing optimism from neuroticism (and trait anxiety, self-mastery, and self-esteem): A reevaluation of the life orientation test. J. Pers. Soc. Psychol. 67, 1063 (1994).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR51\">51</a></sup>, trait optimism<sup><a target=\"_blank\" title=\"Robins, R. W., Hendin, H. M. &amp; Trzesniewski, K. H. Measuring global self-esteem: Construct validation of a single-item measure and the rosenberg self-esteem scale. Personality and Social Psychology Bulletin 27, 151–161 (2001).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR52\">52</a></sup>, trait self-control<sup><a target=\"_blank\" title=\"Tangney, J. P., Baumeister, R. F. &amp; Boone, A. L. High self-control predicts good adjustment, less pathology, better grades, and interpersonal success. J. Pers. 72, 271–324 (2004).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR53\">53</a></sup>, narcissism<sup><a target=\"_blank\" title=\"Back, M. D. et al. Narcissistic admiration and rivalry: Disentangling the bright and dark sides of narcissism. J. Pers. Soc. Psychol. 105, 1013 (2013).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR54\">54</a></sup>, and cognitive reflection<sup><a target=\"_blank\" title=\"Primi, C., Morsanyi, K., Chiesi, F., Donati, M. A. &amp; Hamilton, J. The development and testing of a new version of the cognitive reflection test applying item response theory (IRT). Journal of Behavioral Decision Making 29, 453–469 (2016).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR55\">55</a></sup>.</p><h4 id=\"Sec11\">Demographics</h4><p>Six questions: age, number of children, employment status, marital status, gender, and urbanicity.</p><h4 id=\"Sec12\">Metadata and attention check</h4><p>An attention check was used to mitigate negative impact on data quality from potential non-human responses and the likelihood of biasing data and subsequent analysis of low base-rate outcomes—such as endorsement of COVID-19 conspiracies. We collected typical questionnaire metadata (e.g., start, record, and end dates, duration, and language). In addition, we created an internal participant ID, added ISO2 and ISO3 country codes, and sample representativeness.</p><h3 id=\"Sec13\">Translation</h3><p>The survey instrument was drafted in English and translated into other languages using the standard forward-backward method (i.e., members of national teams were advised to split members into forward-translating the survey into the local language and back-translating it into English, and then have the two groups discuss and resolve discrepancies). In total, the survey instrument was translated into 32 languages, including adaptations of region-specific dialects or vernaculars. Specifically, from English into Arabic, Bengali, Bulgarian, Croatian, Danish, Dutch, Finnish, French, German, Greek, Hebrew, Hungary, Italian, Japanese, Korean, Kurdish, Latvian, Macedonian, Mandarin simplified, Mandarin traditional, Nepali, Norwegian, Polish, Portuguese, Romanian, Russian, Serbian, Slovak, Spanish, Swedish, Turkish, and Ukrainian (see <a target=\"_blank\" href=\"https://osf.io/tfsza/\">osf.io/tfsza</a> at sub-folder <i>Translations</i>).</p><h3 id=\"Sec14\">Data cleaning</h3><p>We received individual data files from each national team. To merge these raw data, minor modifications were introduced, which we delineate in this section. First, we renamed columns to match across data sets, reordered variables alphabetically, and standardised variable labels. Furthermore, all missing values and values denoting the absence of a response were converted to <i>NAs</i> (not available). When ambiguous date formats were found (e.g., on start date, end date, and record date), we manually specified the correct format and standardised them. At the second stage, we introduced multiple modifications to clean the data for research. Some modifications were introduced to every national data set, while others were introduced to specific national data sets (both of which are thoroughly reported in the Data Records section). To each national data set, we recoded the attention check (attcheck) into pass (1) or fail (0); standardised generosity items (generosity1–3), recoded CRT items into intuitive (2), correct (1), and incorrect (0); converted the number of children (children) into a variable with a fixed range from zero to ten or more; recoded all participants declaring being older than 100 years old as 100; and we excluded all duplicates (i.e., in case multiple participants were recorded with identical inputs within a national database, only the first input was retained).</p></div></div><div><h2 id=\"Sec15\">Data Records</h2><div><p>All materials associated with the ICSMP COVID-19 project can be found on the project’s repository (comprising five folders) hosted by the Open Science Framework (OSF, <a target=\"_blank\" href=\"https://doi.org/10.17605/osf.io/tfsza\">https://doi.org/10.17605/osf.io/tfsza</a>)<sup><a target=\"_blank\" title=\"Azevedo, F. et al. Social &amp; Moral Psychology of COVID-19., Open Science Framework, \n                  https://doi.org/10.17605/osf.io/tfsza\n                 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR56\">56</a>,<a target=\"_blank\" title=\"Azevedo, F. et al. Social and moral psychology of covid-19 across 69 countries \n                  https://doi.org/10.31234/osf.io/a3562\n                 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR57\">57</a></sup>. The folder named <i>Code</i> includes an R Markdown document (ICSMP official data.Rmd; <a target=\"_blank\" href=\"https://osf.io/dwpng/\">osf.io/dwpng</a>) that loads multiple data files (from each national team), cleans them up, merges them into a single data file, generates a data-driven code-book, and saves all outputs. It also includes a reproducible report with all reported numbers, analyses and graphs in this article (Analyses-SciData.html; <a target=\"_blank\" href=\"https://osf.io/s5c4p\">osf.io/s5c4p</a>; Analyses SciData.Rmd; <a target=\"_blank\" href=\"https://osf.io/9suyb/\">osf.io/9suyb</a>). The folder named <i>Data</i> includes three sub-folders. The <i>Raw data</i> sub-folder contains the original and unmodified data files from each national team (country data files.zip; <a target=\"_blank\" href=\"https://osf.io/dqmut\">osf.io/dqmut</a>). The sub-folder named <i>Cleaned data</i> contains the merged and cleaned dataset, which is provided in a non-proprietary (ICSMP_cleaned_data.csv; <a target=\"_blank\" href=\"https://osf.io/ypkrc/\">osf.io/ypkrc</a>) and a labelled (ICSMP_cleaned_data.sav; at <a target=\"_blank\" href=\"https://osf.io/8tyj9/\">osf.io/8tyj9</a>) file formats. In addition, we included in a sub-folder a dataset that removes observations failing the attention check or filled out less than 50% of the items, both in a non-proprietary (ICSMP_cleaned_data_nobots.csv; <a target=\"_blank\" href=\"https://osf.io/98fex/\">osf.io/98fex</a>) and a labelled (ICSMP_cleaned_data_nobots.sav; at <a target=\"_blank\" href=\"https://osf.io/3yjga/\">osf.io/3yjga</a>) file formats. The <i>Metadata</i> sub-folder provides a thorough itemised description of the data cleaning process in both text (Data Cleaning.docx; <a target=\"_blank\" href=\"https://osf.io/7udpt/\">osf.io/7udpt</a>) and human-readable change-log (human-readable change log ICSMP.xlsx; <a target=\"_blank\" href=\"https://osf.io/fydx2/\">osf.io/fydx2</a>).</p><p>We also provide a data-driven codebook detailing how each measure was collected—e.g., listing variable names, variable labels, and label values (dt.codebook.xlsx; <a target=\"_blank\" href=\"https://osf.io/ecva2/\">osf.io/ecva2</a>). The <i>IRB</i> folder contains both the Internal Review Board Ethics application (ICSMP Kent Ethics application full.pdf; <a target=\"_blank\" href=\"https://osf.io/xt9gr/\">osf.io/xt9gr</a>) and Ethics approval (ICSMP Kent Ethics approval.pdf; <a target=\"_blank\" href=\"https://osf.io/ce638/\">osf.io/ce638</a>). The folder <i>Sample Type &amp; Representativeness</i> includes the documentation for an internal survey conducted with national team leaders about the employed survey methodology for the data provided (Sample Type &amp; Representativeness.zip; <a target=\"_blank\" href=\"https://osf.io/fj5xn/\">osf.io/fj5xn</a>). The folder <i>Survey Instrument</i> contains the initial English version of our survey instrument along with its Qualtrics.qsf for reproducibility (Survey Instrument.zip; <a target=\"_blank\" href=\"https://osf.io/nf48q/\">osf.io/nf48q</a>). In the sub-folder <i>Translations</i>, we archived all 32 translated survey instruments along with a report on the languages of conducted surveys per country (i.e., several countries had their surveys in multiple languages per country; Country and language.xlsx; <a target=\"_blank\" href=\"https://osf.io/wj7d2/\">osf.io/wj7d2</a>).</p><h3 id=\"Sec16\">Potential for future research</h3><p>The data contains four measures of COVID-19 beliefs and compliance, 17 social and moral psychological constructs, and six sociodemographic characteristics, amounting to 27 socially-relevant variables. To quantify the potential of this dataset—and assuming a typical research paper uses between three to five key main constructs plus sociodemographics and controls—we calculated the number of combinations of 17 constructs, taken three, four, and five at a time, yielding a grand total of 9248 possible unique designs. As a demonstration of the broad scope of the ICSMP data, published studies cover a broad range of psychological disciplines, including social psychology<sup><a target=\"_blank\" title=\"Sternisko, A., Cichocka, A., Cislak, A. &amp; Van Bavel, J. J. National narcissism predicts the belief in and the dissemination of conspiracy theories during the COVID-19 pandemic: Evidence from 56 countries. Personality and Social Psychology Bulletin 01461672211054947 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR13\">13</a>,<a target=\"_blank\" title=\"Cichocka, A. et al. Globalization is associated with lower levels of national narcissism: Evidence from 56 countries. Social Psychological and Personality Science (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR14\">14</a></sup>, cognitive psychology<sup><a target=\"_blank\" title=\"Nurse, M. S., Ross, R. M., Isler, O. &amp; Van Rooy, D. Analytic thinking predicts accuracy ratings and willingness to share covid-19 misinformation in Australia. Memory &amp; Cognition 50, 425–434 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR15\">15</a>,<a target=\"_blank\" title=\"Maglić, M., Pavlović, T. &amp; Franc, R. Analytic thinking and political orientation in the corona crisis. Frontiers in psychology 2711 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR17\">17</a></sup>, political psychology<sup><a target=\"_blank\" title=\"McHugh, C. et al. Moral identity predicts adherence to COVID-19 mitigation procedures depending on political ideology: A comparison between the USA and New Zealand. Political Psychology. Ahead of print (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR16\">16</a></sup>, moral psychology<sup><a target=\"_blank\" title=\"McHugh, C. et al. Moral identity predicts adherence to COVID-19 mitigation procedures depending on political ideology: A comparison between the USA and New Zealand. Political Psychology. Ahead of print (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR16\">16</a>,<a target=\"_blank\" title=\"Gkinopoulos, T., Elbæk, C. T. &amp; Mitkidis, P. Morality in the echo chamber: The relationship between belief in COVID-19 conspiracy theories and public health support and the mediating role of moral identity and morality-as-cooperation across 67 countries. PLOS ONE 17, e0273172 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR18\">18</a></sup>, economic psychology<sup><a target=\"_blank\" title=\"Borau, S., Couprie, H. &amp; Hopfensitz, A. The prosociality of married people: Evidence from a large multinational sample. Journal of Economic Psychology 92, 102545 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR19\">19</a></sup> and health sciences<sup><a target=\"_blank\" title=\"Bonetto, E., Delouvée, S., Mahfud, Y. &amp; Adam-Troian, J. National identification, a social cure for COVID-19? Evidence from 67 countries. International Journal of Social Psychiatry 68, 1116–1126 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR20\">20</a></sup>, among others. They explore different populations in reference to the COVID-19 pandemic in terms of age (e.g., older adults see<sup><a target=\"_blank\" title=\"Cutler, J., Nitschke, J. P., Lamm, C. &amp; Lockwood, P. L. Older adults across the globe exhibit increased prosocial behavior but also greater in-group preferences. Nature Aging 1, 880–888 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR21\">21</a></sup>, marital status<sup><a target=\"_blank\" title=\"Borau, S., Couprie, H. &amp; Hopfensitz, A. The prosociality of married people: Evidence from a large multinational sample. Journal of Economic Psychology 92, 102545 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR19\">19</a></sup> or nationality (e.g., for a study on the Spanish population, see;<sup><a target=\"_blank\" title=\"Gualda, E. et al. Social distancing and COVID-19: Factors associated with compliance with social distancing norms in Spain. Frontiers in Psychology 12 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR22\">22</a></sup> for Swedish and Chinese population see<sup><a target=\"_blank\" title=\"Pan, Y. et al. Psychological well-being is associated with prosociality during the COVID-19 pandemic: A comparison of Swedish and Chinese samples. Emotion. Advance online publication at \n                  https://doi.org/10.1037/emo0001121\n                 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR23\">23</a></sup>), and other socio-demographic characteristics. These all attest to the great potential of the ICSMP data to inspire further research. In sum, the present dataset affords numerous opportunities for cross-cultural research on a plethora of hypotheses. We encourage researchers who consider reusing ICSMP data to examine the list of pre-registrations before beginning a new project so as to avoid duplication (see <a target=\"_blank\" href=\"https://icsmp-covid19.netlify.app/preregistration.html\">icsmp-covid19.netlify.app/preregistration</a>).</p><h3 id=\"Sec17\">Data visualisation interface</h3><p>In addition to the raw data, a dedicated Web application was developed to provide a general overview of the dataset (<a target=\"_blank\" href=\"https://icsmp.shinyapps.io/icsmp_covid19/\">icsmp.shinyapps.io/icsmp_covid19</a>). The application is based on an R shiny server (<a target=\"_blank\" href=\"https://rstudio.com/products/shiny/\">rstudio.com/products/shiny</a>), together with the <i>leaflet</i><sup><a target=\"_blank\" title=\"Graul, C. leafletR: Interactive Web-Maps Based on the Leaflet JavaScript Library. R package version 0.4-0 (2016).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR58\">58</a></sup> and <i>ggplot2</i><sup><a target=\"_blank\" title=\"Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag New York, 2016).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR59\">59</a></sup> graphical libraries to generate dynamic plots. All the generated figures can be exported as .png files, and all tables can be exported as .csv files. The Web application allows easy and dynamic generation of illustrations like the figures with maps for each construct with zoomable world maps and static figures and plots for sample and country characteristics. In addition, all tables are embedded with dynamic features for sorting and filtering. To make it more accessible for the readers, both tables and figures are downloadable. The Shiny app has two tabs giving general information about the project and the international consortium. The first tab contains sample descriptions such as sample size, missing data, and attention checks for each country with a Gantt chart showing the dates of data collection. The second tab displays world maps of spatial distancing, policy support, national identity, conspiracy beliefs, national narcissism and morality as cooperation as well as all tables reported in dynamic formats.</p></div></div><div><h2 id=\"Sec18\">Technical Validation</h2><div><p>To support the technical quality of the dataset, we conducted an analysis to showcase its reliability (and its diverse applicability to research questions in social sciences and beyond). For completeness, in the analyses that follow, we examined all samples-including those with very few observations, such as Puerto Rico (N = 2), Brazil_3 (N = 6), and Panama (N = 12).</p><p>We evaluated the adopted survey methodology utilised by national teams by conducting an internal survey to ensure the accuracy of reported sample types. The inspection showed that 28 samples were quota-based nationally representative samples (36%), 6 used <i>post hoc</i> weights to achieve an approximate level of national representation (8%) which nonetheless should be seen as convenience samples, and 43 were convenience samples (56%), many of which were from low and middle-income countries<sup><a target=\"_blank\" title=\"Ghai, S. It’s time to reimagine sample diversity and retire the weird dichotomy. Nature Human Behaviour 5, 971–972 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR60\">60</a></sup>. We codified the results of this survey into the cleaned data as the variable ‘sample_coding’ and present a summary in Table <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab10\">10</a>. National representativeness for the 28 quota-based samples relate to an approximation of the demographic characteristics of age and gender only for each country.</p><div><figure><figcaption><b>Table 10 Overview of the samples.</b></figcaption><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/tables/10\"><span>Full size table</span></a></p></figure></div><p>Regarding individual-level data quality, Fig. <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Fig6\">6</a> shows a world map of the 69 countries from which data were collected, coloured according to overall percentages of missing data (overall mean = 6.0%). Overall, 95.6% of participants had less than 50% missing data, 92.8% participants had less than 10% missing data, and 24.7% of participants had 0% missing data. Another indicator of data quality is the rate of attention check fails per country. On the last screen of the survey, participants were given the following instructions: “Help us get rid of bots: Please write the number 213 into the comment box.” Participants who wrote “213” were coded as passing the attention check, participants who wrote anything else were coded as failing the attention check, and those who did not reach this screen of the survey were coded as missing data. Figure <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Fig6\">6</a> also shows (bottom plot) a world map coloured according to the rate of attention-check fails across countries. Overall, 90.1% of participants passed the attention check (1.0% failed), and 8.0% did not reach the final screen with the attention check.</p><div><figure><figcaption><b>Fig. 6</b></figcaption><div><div><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/6\"><picture><source type=\"image/webp\" srcset=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig6_HTML.png?as=webp\"></source><img src=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig6_HTML.png\" alt=\"figure 6\" /></picture></a></div><p>Data quality indicators for each surveyed country. <b><i>Note:</i></b> The percentage of missing data considered all the questions in the survey (i.e., all sociodemographics and psychological scales”). We calculated, for each country, the mean of the participants’ proportion of missing data across all survey questions, including sociodemographics (this information is also provided in our reproducible report of Fig. <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Fig6\">6</a>, where the R code is provided).</p></div><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/6\"><span>Full size image</span></a></p></figure></div><p>The full dataset presents <i>N</i> = 51,404 cases across 69 countries (from 77 samples, 28 of which are quota-based nationally representative), with an average sample size of 745 (SD = 549) and a proportion of valid answers of 95%. The mean age of respondents was 42.93 (SD = 16.04) years, and 50.9% were women (44% males, 0.3% others, and 4.8% unreported). The employment status breakdown shows 44.8% employed full-time, 10.6% part-time, 8.1% unemployed, 10% students, 10.1% retired, 11% other, and 5.3% unreported. The overall marital status shows 33% of respondents were single, 18.7% in a relationship, 42.7% married, and 5.5% unreported. The majority of our participants reported having no children (41.6%), with 16.7% having one child, 20.1%, 9.2%, and 3.9% with two, three and four children, respectively, and 1.7% had five or more children (6.9% unreported). We break down these aggregated results per country. Tables <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab1\">1</a>, <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab2\">2</a> show the number of cases and valid answers, Table <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab3\">3</a>,<a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab4\">4</a> summarises the distribution of sex, Tables <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab5\">5</a>, <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab6\">6</a> display employment status, and Tables <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab7\">7</a>–<a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Tab9\">9</a> illustrate both marital statuses and the number of children.</p><p>We also examined cross-cultural differences in conspiracy beliefs, morality as cooperation, spatial distancing, national narcissism, national identification, and policy support for preventative measures across 69 countries in Fig. <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Fig7\">7</a>. Additionally, we showcase patterns of associations between these moral and psychological constructs across gender, ideology and age in Figs. <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Fig8\">8</a>, <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Fig9\">9</a>. For the association pattern analysis, we excluded samples with less than 490 respondents as recommended for stable correlations<sup><a target=\"_blank\" title=\"Kretzschmar, A. &amp; Gignac, G. E. At what sample size do latent variable correlations stabilize? Journal of Research in Personality 80, 17–22 (2019).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR61\">61</a></sup>, as well as for the subsequent consistency measure analysis.</p><div><figure><figcaption><b>Fig. 7</b></figcaption><div><div><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/7\"><picture><source type=\"image/webp\" srcset=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig7_HTML.png?as=webp\"></source><img src=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig7_HTML.png\" alt=\"figure 7\" /></picture></a></div><p>Cross-cultural differences in Social &amp; Moral Psychology of COVID-19 across 69 countries. <b><i>Note:</i></b> Each world heat map in the figure shows the means score, at the country level, for constructs in the survey. Conspiracy Beliefs - participant’s beliefs in conspiracy theories regarding COVID-19; Morality as Cooperation - participant’s moral concern based on the morality-as-cooperation theory; Spatial Distancing - participant’s support for spatial distancing as a strategy against COVID-19; Collective Narcissism - participant’s narcissism, i.e., an inflated view regarding their ingroup (in this research we focused on nationality); National Identity - participant’s identity attached to belonging to a nation; Policy Support - participant’s support to public policies (e.g., closing parks or schools) as a strategy against COVID-19.</p></div><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/7\"><span>Full size image</span></a></p></figure></div><div><figure><figcaption><b>Fig. 8</b></figcaption><div><div><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/8\"><picture><source type=\"image/webp\" srcset=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig8_HTML.png?as=webp\"></source><img src=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig8_HTML.png\" alt=\"figure 8\" /></picture></a></div><p>Cross-cultural differences in associations of Social &amp; Moral Psychology of COVID-19 across sex and ideology in 69 countries.</p></div><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/8\"><span>Full size image</span></a></p></figure></div><div><figure><figcaption><b>Fig. 9</b></figcaption><div><div><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/9\"><picture><source type=\"image/webp\" srcset=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig9_HTML.png?as=webp\"></source><img src=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig9_HTML.png\" alt=\"figure 9\" /></picture></a></div><p>Cross-cultural differences in associations of Social &amp; Moral Psychology of COVID-19 across age in 69 countries.</p></div><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/9\"><span>Full size image</span></a></p></figure></div><p>To examine internal consistency for the main scales, we calculated Cronbach’s Alpha, Omega, Guttman split-half reliability, and proportion of variance explained by a unidimensional factor. This table is available at <a target=\"_blank\" href=\"https://osf.io/ed7yg\">osf.io/ed7yg</a> and shows indices of internal consistency by country for measures of conspiracy beliefs, morality as cooperation, spatial distancing, national narcissism, national identification, and policy support for preventative measures, respectively. We found that the spatial distancing construct, on average, has the lowest Cronbach’s alpha, followed by morality as cooperation. On average, conspiracy beliefs have the highest Cronbach’s alpha, followed by policy support. These patterns hold for the Omega measures, but when considering Guttman’s split-half reliability, collective narcissism and national identity yield the lowest values. Figures <a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Fig9\">9</a>–<a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8#Fig15\">15</a> show these patterns visually.</p><div><figure><figcaption><b>Fig. 10</b></figcaption><div><div><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/10\"><picture><source type=\"image/webp\" srcset=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig10_HTML.png?as=webp\"></source><img src=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig10_HTML.png\" alt=\"figure 10\" /></picture></a></div><p>Support for policies in 69 countries.</p></div><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/10\"><span>Full size image</span></a></p></figure></div><div><figure><figcaption><b>Fig. 11</b></figcaption><div><div><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/11\"><picture><source type=\"image/webp\" srcset=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig11_HTML.png?as=webp\"></source><img src=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig11_HTML.png\" alt=\"figure 11\" /></picture></a></div><p>Collective narcissism in 69 countries.</p></div><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/11\"><span>Full size image</span></a></p></figure></div><div><figure><figcaption><b>Fig. 12</b></figcaption><div><div><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/12\"><picture><source type=\"image/webp\" srcset=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig12_HTML.png?as=webp\"></source><img src=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig12_HTML.png\" alt=\"figure 12\" /></picture></a></div><p>Spatial distancing in 69 countries.</p></div><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/12\"><span>Full size image</span></a></p></figure></div><div><figure><figcaption><b>Fig. 13</b></figcaption><div><div><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/13\"><picture><source type=\"image/webp\" srcset=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig13_HTML.png?as=webp\"></source><img src=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig13_HTML.png\" alt=\"figure 13\" /></picture></a></div><p>Morality as cooperation in 69 countries.</p></div><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/13\"><span>Full size image</span></a></p></figure></div><div><figure><figcaption><b>Fig. 14</b></figcaption><div><div><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/14\"><picture><source type=\"image/webp\" srcset=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig14_HTML.png?as=webp\"></source><img src=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig14_HTML.png\" alt=\"figure 14\" /></picture></a></div><p>National identity in 69 countries.</p></div><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/14\"><span>Full size image</span></a></p></figure></div><div><figure><figcaption><b>Fig. 15</b></figcaption><div><div><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/15\"><picture><source type=\"image/webp\" srcset=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig15_HTML.png?as=webp\"></source><img src=\"https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41597-023-02080-8/MediaObjects/41597_2023_2080_Fig15_HTML.png\" alt=\"figure 15\" /></picture></a></div><p>Cross-cultural differences in Internal Consistency Coefficients (Cronbach’s alpha, McDonald’s Omega, Guttman Split-Half), and variance explained of Social &amp; Moral Psychology Constructs in 69 countries. <b><i>Note:</i></b> internal consistency typically refers to correlations between different items on the same test to evaluate the extent to which latent indicators comprising the scale measure the same construct.</p></div><p><a target=\"_blank\" href=\"https://www.nature.com/articles/s41597-023-02080-8/figures/15\"><span>Full size image</span></a></p></figure></div></div></div><div><h2 id=\"Sec19\">Usage Notes</h2><div><p>The datasets are shared, cleaned, and ready for analysis. We recommend that interested researchers use the cleaned version of the data (available at <a target=\"_blank\" href=\"https://doi.org/10.17605/osf.io/tfsza\">https://doi.org/10.17605/osf.io/tfsza</a>)<sup><a target=\"_blank\" title=\"Azevedo, F. et al. Social &amp; Moral Psychology of COVID-19., Open Science Framework, \n                  https://doi.org/10.17605/osf.io/tfsza\n                 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR56\">56</a></sup>. The use of the labelled data is also suggested for convenience as it has all variable levels encoded, thus eliminating the need to consult the codebook when using the.csv format.</p><p>The Data were imported and cleaned using the R software for statistical analysis<sup><a target=\"_blank\" title=\"R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2019).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR62\">62</a></sup> and packages <i>readr</i><sup><a target=\"_blank\" title=\"Wickham, H. &amp; Hester, J. readr: Read Rectangular Text Data. R package version 1.4.0 (2020).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR63\">63</a></sup>, <i>haven</i><sup><a target=\"_blank\" title=\"Wickham, H. &amp; Miller, E. haven: Import and Export SPSS, Stata and SAS Files. R package version 2.4.1 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR64\">64</a></sup>, <i>readxl</i><sup><a target=\"_blank\" title=\"Wickham, H. &amp; Bryan, J. readxl: Read Excel Files. R package version 1.3.1 (2019).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR65\">65</a></sup>, <i>dplyr</i><sup><a target=\"_blank\" title=\"Wickham, H., François, R., Henry, L. &amp; Müller, K. dplyr: A Grammar of Data Manipulation. R package version 1.0.6 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR66\">66</a></sup>, <i>psych</i><sup><a target=\"_blank\" title=\"Revelle, W. psych: Procedures for Psychological, Psychometric, and Personality Research. R package version 2.1.6 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR67\">67</a></sup>, <i>htmltools</i><sup><a target=\"_blank\" title=\"Cheng, J., Sievert, C., Chang, W., Xie, Y. &amp; Allen, J. htmltools: Tools for HTML. R package version 0.5.1 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR68\">68</a></sup>, mime<sup><a target=\"_blank\" title=\"Xie, Y. mime: Map Filenames to MIME Types. R package version 0.11 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR69\">69</a></sup>, <i>xfun</i><sup><a target=\"_blank\" title=\"Xie, Y. xfun: Supporting Functions for Packages Maintained by Yihui Xie. R package version 0.25 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR70\">70</a></sup>, <i>labelled</i><sup><a target=\"_blank\" title=\"Larmarange, J. labelled: Manipulating Labelled Data. R package version 2.9.0 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR71\">71</a></sup>, <i>sjlabelled</i><sup><a target=\"_blank\" title=\"Lüdecke, D. sjlabelled: Labelled Data Utility Functions. R package version 1.1.6 (2020).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR72\">72</a></sup>, <i>codebook</i><sup><a target=\"_blank\" title=\"Arslan, R. codebook: Automatic Codebooks from Metadata Encoded in Dataset Attributes. R package version 0.9.2 (2020).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR73\">73</a></sup>, <i>lubridate</i><sup><a target=\"_blank\" title=\"Spinu, V., Grolemund, G. &amp; Wickham, H. lubridate: Make Dealing with Dates a Little Easier. R package version 1.7.10 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR74\">74</a></sup>.</p><p>As previously noted<sup><a target=\"_blank\" title=\"Yamada, Y. et al. COVIDiSTRESS global survey dataset on psychological and behavioural consequences of the COVID-19 outbreak. Sci. Data. 8, 1–23 (2021).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR5\">5</a></sup>, those wishing to approximate national representativeness can apply the appropriate survey weights to demographic and countries of interest when random sampling is used (e.g., sex: <a target=\"_blank\" href=\"https://ourworldindata.org/gender-ratio\">https://ourworldindata.org/gender-ratio</a>; age: <a target=\"_blank\" href=\"http://data.un.org/Data.aspx?d=POP&amp;f=tableCode%3A22\">http://data.un.org/Data.aspx?d=POP&amp;f=tableCode%3A22</a>; education: <a target=\"_blank\" href=\"https://ourworldindata.org/global-education\">https://ourworldindata.org/global-education</a>; marital status: <a target=\"_blank\" href=\"https://ourworldindata.org/marriages-and-divorces\">https://ourworldindata.org/marriages-and-divorces</a>).</p><p>To minimize misclassification of text-based responses to the cognitive reflection test (CRT) and the attention check, we used multiple steps of data cleaning using REGEX (regular expressions) as fully detailed in (ICSMP official data.Rmd; <a target=\"_blank\" href=\"https://osf.io/dwpng/\">osf.io/dwpng</a>) located in the folder named <i>Code</i>. First, we coded the predefined numerical and text values as correct (in the case of CRT, also the values predefined as intuitive). Then, iteratively, we screened the remaining responses and, using REGEX, updated answers. Remaining responses were recoded as incorrect.</p></div></div>\n                </div><div>\n                <div><h2 id=\"code-availability\">Code availability</h2><p>All raw and cleaned data—as well as the R-code—used for standardising national-teams data, merging, and cleaning them are available at <a target=\"_blank\" href=\"https://doi.org/10.17605/osf.io/tfsza\">https://doi.org/10.17605/osf.io/tfsza</a><sup><a target=\"_blank\" title=\"Azevedo, F. et al. Social &amp; Moral Psychology of COVID-19., Open Science Framework, \n                  https://doi.org/10.17605/osf.io/tfsza\n                 (2022).\" href=\"https://www.nature.com/articles/s41597-023-02080-8#ref-CR56\">56</a></sup>.</p></div><div><h2 id=\"Bib1\">References</h2><div><ol><li><p>Cucinotta, D. &amp; Vanelli, M. 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Rêgo, Paulo S. Boggio &amp; Waldir M. Sampaio</p></li><li><p>Department of Economics, Norwegian School of Economics, Bergen, Norway</p><p>F. Ceren Ay</p></li><li><p>Telenor Research, Oslo, Norway</p><p>F. Ceren Ay</p></li><li><p>Macedonian Academy of Sciences and Arts, Skopje, Republic of North Macedonia</p><p>Biljana Gjoneska</p></li><li><p>Kieskompas - Election Compass, Amsterdam, Netherlands</p><p>Tom W. Etienne, Yordan Kutiyski &amp; Oscar Moreda Laguna</p></li><li><p>Department of Political Science &amp; Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, USA</p><p>Tom W. Etienne</p></li><li><p>Department of Psychology, Macquarie University, Sydney, NSW, Australia</p><p>Robert M. Ross</p></li><li><p>Department of Philosophy, University of St Andrews, St Andrews, Scotland</p><p>Philipp Schönegger</p></li><li><p>School of Economics and Finance, University of St Andrews, St Andrews, Scotland</p><p>Philipp Schönegger</p></li><li><p>Medicine Faculty, Cooperative University of Colombia, Villavicencio, Colombia</p><p>Julián C. Riaño-Moreno &amp; Maria P. Bernal-Zárate</p></li><li><p>Department of Bioethics, El Bosque University, Bogotá, Colombia</p><p>Julián C. Riaño-Moreno</p></li><li><p>School of Psychology, University of Kent, Canterbury, England</p><p>Aleksandra Cichocka &amp; Bjarki Gronfeldt</p></li><li><p>Department of Economics, Middlesex University London, London, England</p><p>Valerio Capraro</p></li><li><p>Darden School of Business, University of Virginia, Charlottesville, VA, USA</p><p>Luca Cian</p></li><li><p>Questrom School of Business, Boston University, Boston, MA, USA</p><p>Chiara Longoni</p></li><li><p>School of Economics and Finance, Queensland University of Technology, Brisbane, QLD, Australia</p><p>Ho Fai Chan, Uwe Dulleck, Ozan Isler &amp; Benno Torgler</p></li><li><p>Center for Behavioural Economics, Society and Technology, Queensland University of Technology, Brisbane, QLD, Australia</p><p>Ho Fai Chan, Uwe Dulleck, Ozan Isler &amp; Benno Torgler</p></li><li><p>Department of Psychology and Neural Science, New York University, New York, NY, USA</p><p>Jay J. Van Bavel, David M. Amodio, Elizabeth Harris, Claire E. Robertson &amp; Anni Sternisko</p></li><li><p>Department of Strategy and Management, Norwegian School of Economics, Bergen, Norway</p><p>Hallgeir Sjåstad</p></li><li><p>SWPS University of Social Sciences and Humanities, Warsaw, Poland</p><p>John B. Nezlek, Aleksandra Cislak &amp; Marzena Cypryańska</p></li><li><p>Department of Psychological Sciences, College of William and Mary, Williamsburg, VA, USA</p><p>John B. Nezlek</p></li><li><p>Department of Philosophy, Macquarie University, Sydney, NSW, Australia</p><p>Mark Alfano &amp; Neil Levy</p></li><li><p>Stanford Graduate School of Business, Stanford University, Stanford, CA, USA</p><p>Michele J. Gelfand</p></li><li><p>School of Human Sciences, Institute for Lifecourse Development, University of Greenwich, London, England</p><p>Michèle D. Birtel &amp; Harry Farmer</p></li><li><p>Department of Experimental Psychology, University of Oxford, Oxford, England</p><p>Patricia L. Lockwood &amp; Jo Cutler</p></li><li><p>Center for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, England</p><p>Patricia L. Lockwood, Matthew Apps &amp; Jo Cutler</p></li><li><p>KU Leuven, Leuven, Belgium</p><p>Koen Abts</p></li><li><p>National Research University Higher School of Economics (HSE), Moscow, Russia</p><p>Elena Agadullina &amp; Natalia Bogatyreva</p></li><li><p>De La Salle University, Manila, Philippines</p><p>John Jamir Benzon Aruta</p></li><li><p>Department of Psychology, University of the Witwatersrand, Johannesburg, South Africa</p><p>Sahba Nomvula Besharati, Kate Cockcroft, Michael Mark Pitman &amp; Enid M. Schutte</p></li><li><p>Department of Political Science, Aarhus University, Aarhus, Denmark</p><p>Alexander Bor, Antoine Marie, Michael Bang Petersen &amp; Frederik J. Jorgensen</p></li><li><p>Toronto Metropolitan University, Toronto, Canada</p><p>Becky L. Choma &amp; Rishad Habib</p></li><li><p>Department of Government, Dartmouth College, Hanover, NH, USA</p><p>Charles David Crabtree, Yusaku Horiuchi &amp; John Kahn</p></li><li><p>Department of Psychology, University of Toronto, Toronto, ON, Canada</p><p>William A. Cunningham, Victoria H. Davis, Elizabeth U. Long &amp; Victoria Oldemburgo de Mello</p></li><li><p>Gatton College of Business and Economics, University of Kentucky, Lexington, KY, USA</p><p>Koustav De</p></li><li><p>Department of Mass Communication, National University of Science and Technology (NUST), Islamabad, Pakistan</p><p>Waqas Ejaz</p></li><li><p>Department of Management, Aarhus University, Aarhus, Denmark</p><p>Christian T. Elbaek &amp; Panagiotis Mitkidis</p></li><li><p>Faculty of Social and Economic Sciences, Comenius University, Bratislava, Slovakia</p><p>Andrej Findor &amp; Matej Hruška</p></li><li><p>IntraMed, Buenos Aires, Argentina</p><p>Daniel Flichtentrei</p></li><li><p>University of Colorado Boulder, Boulder, CO, USA</p><p>June Gruber</p></li><li><p>ESEIS/COIDESO [ESEIS, Social Studies and Social Intervention Research Center; COIDESO, COIDESO, Center for Research in Contemporary Thought and Innovation for Social Development], University of Huelva, Huelva, Spain</p><p>Estrella Gualda, E. Begoña Garcia-Navarro, Elena Morales-Marente, M. Soledad Palacios-Galvez &amp; Iván Rodríguez-Pascual</p></li><li><p>Faculty of Social Work, University of Huelva, Huelva, Spain</p><p>Estrella Gualda</p></li><li><p>WHU - Otto Beisheim School of Management, Vallendar, Germany</p><p>Toan Luu Duc Huynh</p></li><li><p>Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile</p><p>Agustin Ibanez</p></li><li><p>Cognitive Neuroscience Center (CNC), University of San Andrés, Buenos Aires, Argentina</p><p>Agustin Ibanez</p></li><li><p>Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), California, US; &amp; Trinity College Dublin (TCD), Dublin, Ireland</p><p>Agustin Ibanez</p></li><li><p>Department of Educational and Counselling Psychology, University of Dhaka, Dhaka, Bangladesh</p><p>Mostak Ahamed Imran &amp; Hapsa Hossain Farhana</p></li><li><p>Department of Psychology, The Hebrew University of Jerusalem, Jerusalem, Israel</p><p>Jacob Israelashvili, Anat Perry, Eli Adler &amp; Eran Halperin</p></li><li><p>Institute of Psychology, Jagiellonian University, Kraków, Poland</p><p>Katarzyna Jasko</p></li><li><p>Institute of Security and Global Affairs, Leiden University, The Hague, Netherlands</p><p>Jaroslaw Kantorowicz</p></li><li><p>Erasmus School of Law, Erasmus University Rotterdam, Rotterdam, Netherlands</p><p>Elena Kantorowicz-Reznichenko</p></li><li><p>Department of Political Science, Vrije University (VU) Amsterdam, Amsterdam, Netherlands</p><p>André Krouwel</p></li><li><p>Department of Digital Humanities, University of Helsinki, Helsinki, Finland</p><p>Michael Laakasuo, Anton Berg, Marianna Drosinou, Volo Herzon, Mika Koverola, Anton Kunnari, Jussi Palomöki, Silva Perander &amp; Jukka Sundvall</p></li><li><p>Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria</p><p>Claus Lamm &amp; Jonas P. Nitschke</p></li><li><p>School of Psychology, National Autonomous University of Mexico, Mexico City, Mexico</p><p>Caroline Leygue &amp; Octavio Salvador-Ginez</p></li><li><p>Department of Economics, National Taiwan University, Taipei, Taiwan</p><p>Ming-Jen Lin</p></li><li><p>Center for Research in Econometric Theory and Applications, National Taiwan University, Taipei, Taiwan</p><p>Ming-Jen Lin &amp; Hans H. Tung</p></li><li><p>Tribhuvan University, Kirtipur, Nepal</p><p>Mohammad Sabbir Mansoor, Hom Nath Chalise, Ranju Lama Gurung, Apsara Katuwal Dangol, Madhavi Sharma &amp; Pujan Sharma</p></li><li><p>Department of Leadership and Organizational Behavior, BI Norwegian Business School, Oslo, Norway</p><p>Lewend Mayiwar</p></li><li><p>Institute of Security and Global Affairs, Leiden University, Leiden, Netherlands</p><p>Honorata Mazepus</p></li><li><p>Faculty of Governance and Global Affairs, Leiden University, Leiden, Netherlands</p><p>Honorata Mazepus</p></li><li><p>Department of Psychology, University of Limerick, Limerick, Ireland</p><p>Cillian McHugh &amp; Siobhán M. Griffin</p></li><li><p>Department of Psychology, The University of Western Ontario, London, ON, Canada</p><p>John Paul Minda &amp; Clara Alexandra Stafford</p></li><li><p>Center for Advanced Hindsight, Duke University, Durham, NC, USA</p><p>Panagiotis Mitkidis</p></li><li><p>Department of Clinical Neuroscience, Karolinska Institute, Solna, Sweden</p><p>Andreas Olsson, Simon Jangard, Yafeng Pan, Philip Pärnamets &amp; Joana B. Vieira</p></li><li><p>Department of Management, University of Agder, Kristiansand, Norway</p><p>Tobias Otterbring</p></li><li><p>Institute of Retail Economics, Stockholm, Sweden</p><p>Tobias Otterbring</p></li><li><p>Department of Psychology, Lehigh University, Bethlehem, PA, USA</p><p>Dominic J. Packer</p></li><li><p>Department of Psychology, Monk Prayogshala, Mumbai, India</p><p>Arathy Puthillam</p></li><li><p>Faculty of Medicine, Pontifical Javeriana University, Bogotá, Colombia</p><p>Hernando Santamaría-García, Mateo Andres Córdoba-Delgado &amp; Juliana Molina-Paredes</p></li><li><p>Department of Management, Technology, and Economics, ETH Zürich, Zürich, Switzerland</p><p>Petra C. Schmid, Marie Crouzevialle &amp; Robin Willardt</p></li><li><p>Department of Psychiatry and Medical Psychology, Research Institute, Medical University of Plovdiv, Plovdiv, Bulgaria</p><p>Drozdstoy Stoyanov</p></li><li><p>Humanities and Social Sciences, Indian Institute of Management, Indore, India</p><p>Shruti Tewari &amp; Prasad Garladinne</p></li><li><p>Institute of Social Sciences, Belgrade, Serbia</p><p>Bojan Todosijević</p></li><li><p>Department of Psychology, Royal Holloway, University of London, London, England</p><p>Manos Tsakiris</p></li><li><p>Center for the Politics of Feelings, School of Advanced Study, University of London, London, England</p><p>Manos Tsakiris</p></li><li><p>Department of Behavioral and Cognitive Sciences, Faculty of Humanities, Education and Social Sciences, University of Luxembourg, Luxembourg City, Luxembourg</p><p>Manos Tsakiris</p></li><li><p>Department of Political Science, National Taiwan University, Taipei, Taiwan</p><p>Hans H. Tung</p></li><li><p>Faculty of Political Science, National School for Political Studies and Public Administration, Bucharest, Romania</p><p>Radu G. Umbres</p></li><li><p>Department of Psychology, University of Latvia, Riga, Latvia</p><p>Edmunds Vanags &amp; Jānis Ekmanis</p></li><li><p>Department of Psychology, Princeton University, Princeton, NJ, USA</p><p>Madalina Vlasceanu</p></li><li><p>Department of Psychology, Speech, and Hearing, University of Canterbury, Christchurch, New Zealand</p><p>Andrew Vonasch, Jessica Gale &amp; Kumar Yogeeswaran</p></li><li><p>Department of Psychology and Neuroscience, Duke University, Durham, NC, USA</p><p>Meltem Yucel</p></li><li><p>Department of Psychology, University of Virginia, Charlottesville, VA, USA</p><p>Meltem Yucel &amp; Annalisa Myer</p></li><li><p>School of Economics and Management, Hebei University of Technology, Tianjin, PR China</p><p>Yucheng Zhang</p></li><li><p>School of Collective Intelligence, Mohammed VI Polytechnic University, Ben Guerir, Morocco</p><p>Mohcine Abad, Hamza Alaoui Mdarhri, Cathal O’Madagain &amp; Brent Strickland</p></li><li><p>Institute for Research and Development-Kurdistan, Middle East, Iraq</p><p>Narin Akrawi</p></li><li><p>Impact For Development, North Africa, Rabat, Morocco</p><p>Hanane Amara, Soulaimane El Mimouni &amp; Tarik Nesh-Nash</p></li><li><p>Department of Psychology, University of Amsterdam, Amsterdam, Netherlands</p><p>David M. Amodio, Ognjan Denkovski, David T. Schultner &amp; Iris J. Traast</p></li><li><p>Department of Psychology, Jose Rizal University, Mandaluyong, Philippines</p><p>Benedict G. Antazo</p></li><li><p>Department of Philosophy, University Cheikh Anta Diop, Dakar, Senegal</p><p>Mouhamadou Hady Ba</p></li><li><p>School of Medicine and Health Sciences, University of Rosario, Bogotá, Colombia</p><p>Sergio Barbosa</p></li><li><p>Moral Psychology and Decision Sciences Research Incubator, University of Rosario, Bogotá, Colombia</p><p>Sergio Barbosa</p></li><li><p>School of Psychological Sciences, University of Melbourne, Parkville, VIC, Australia</p><p>Brock Bastian &amp; Jeffrey P. Thomas</p></li><li><p>Department of Psychological and Social Sciences, Penn State Abington, Abington, PA, USA</p><p>Michael Bernstein</p></li><li><p>Institute of Psychology, University of Wrocław, Wrocław, Poland</p><p>Michał Białek</p></li><li><p>IMT School for Advanced Studies Lucca, Lucca, Italy</p><p>Ennio Bilancini &amp; Roberto Di Paolo</p></li><li><p>Department of Economics and Management, University of Florence, Florence, Italy</p><p>Leonardo Boncinelli</p></li><li><p>Department of Management, London School of Economics and Political Science, London, England</p><p>Jonathan E. Booth &amp; Chunyun Li</p></li><li><p>Toulouse Business School, University of Toulouse, Toulouse, France</p><p>Sylvie Borau</p></li><li><p>Social Policy Institute of the Ministry of Labor, Family and Social Affairs of the Slovak Republic, Bratislava, Slovakia</p><p>Ondrej Buchel</p></li><li><p>The Institute for Sociology of the Slovak Academy of Sciences, Bratislava, Slovakia</p><p>Ondrej Buchel</p></li><li><p>Department of Psychology, Penn State University, University Park, PA, USA</p><p>C. Daryl Cameron &amp; Julian A. Scheffer</p></li><li><p>Rock Ethics Institute, Penn State University, University Park, PA, USA</p><p>C. Daryl Cameron</p></li><li><p>Department of Psychology, Federal University of Santa Catarina, Florianópolis, Brazil</p><p>Chrissie F. Carvalho</p></li><li><p>Department of Economics, University of Bologna, Bologna, Italy</p><p>Tatiana Celadin</p></li><li><p>IUSS Cognitive Neuroscience (ICoN) Center, Institute for Advanced Study of Pavia, Pavia, Italy</p><p>Chiara Cerami &amp; Gaia C. Santi</p></li><li><p>Cognitive Computational Neuroscience Research Unit, Neurological Institute Foundation Casimiro Mondino, Pavia, Italy</p><p>Chiara Cerami &amp; Chiara Crespi</p></li><li><p>School of Psychology, Shenzhen University, Shenzhen, PR China</p><p>Xiaojun Cheng</p></li><li><p>Institute for Advanced Study in Toulouse, Université Toulouse 1 Capitole, Toulouse, France</p><p>Jane Conway</p></li><li><p>Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy</p><p>Chiara Crespi</p></li><li><p>Cracow University of Economics, Kraków, Poland</p><p>Justyna Dabrowska</p></li><li><p>UBC Sauder School of Business, University of British Columbia, Vancouver, BC, Canada</p><p>Michael A. Daniels, Nathan A. Dhaliwal &amp; Katherine White</p></li><li><p>Psychology Department, University of California - Los Angeles, Los Angeles, CA, USA</p><p>Pamala N. Dayley</p></li><li><p>Laboratory of Psychology: Cognition, Behavior, and Communication (LP3C), Rennes 2 University, Rennes, France</p><p>Sylvain Delouvée</p></li><li><p>Laboratory of Social and Cognitive Psychology, Clermont Auvergne University, CNRS, Clermont-Ferrand, France</p><p>Guillaume Dezecache</p></li><li><p>Cavite State University-General Trias City Campus, Cavite, Philippines</p><p>Alelie B. Diato</p></li><li><p>Crawford School of Public Policy, Australian National University, Canberra, ACT, Australia</p><p>Uwe Dulleck</p></li><li><p>CESifo, University of Munich, Munich, Germany</p><p>Uwe Dulleck</p></li><li><p>Department of International Trade, Boğaziçi University, Istanbul, Turkey</p><p>Arhan S. Ertan</p></li><li><p>Hult International Business School Dubai, Dubai, UAE</p><p>Ali Fenwick</p></li><li><p>Department of Social Policy and Intervention, University of Oxford, Oxford, England</p><p>Kristijan Fidanovski</p></li><li><p>Department of Media and Communications, University of Sydney, Sydney, NSW, Australia</p><p>Terry Flew</p></li><li><p>Department of Psychiatry, University of the Witwatersrand, Johannesburg, South Africa</p><p>Shona Fraser</p></li><li><p>University of Bayreuth, Bayreuth, Germany</p><p>Raymond Boadi Frempong &amp; David Stadelmann</p></li><li><p>Department of Psychology, University of Waterloo, Waterloo, ON, Canada</p><p>Jonathan A. Fugelsang &amp; Alexander Cameron Walker</p></li><li><p>Department of Peace Studies, University of Bradford, Bradford, England</p><p>Oussama Ghajjou</p></li><li><p>Philosophy and Social Studies Department, Rethymno, Greece</p><p>Theofilos Gkinopoulos</p></li><li><p>Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA</p><p>Kurt Gray &amp; Frank Kachanoff</p></li><li><p>Department of Economics, Koc University, Istanbul, Turkey</p><p>Mert Gümren</p></li><li><p>Department of Media and Communication, City University of Hong Kong, Kowloon Tong, Hong Kong</p><p>Guanxiong Huang</p></li><li><p>University of Regensburg, Regensburg, Germany</p><p>Matthias F. C. Hudecek</p></li><li><p>Graduate School for Transnational Studies, Free University of Berlin, Berlin, Germany</p><p>Oleksandra Keudel</p></li><li><p>Department of Management and Engineering, Linköping University, Linköping, Sweden</p><p>Lina Koppel &amp; Gustav Tinghög</p></li><li><p>Department of Psychology, University of Koblenz-Landau, Landau, Germany</p><p>Emily Kubin</p></li><li><p>Department of Psychology, University of Alberta, Edmonton, Canada</p><p>Josh Leota, Kyle Nash &amp; Andy Scott</p></li><li><p>LMU Center for Leadership and People Management, Ludwig Maximilian University of Munich, Munich, Germany</p><p>Eva Lermer</p></li><li><p>Augsburg University for Applied Sciences, Augsburg, Germany</p><p>Eva Lermer</p></li><li><p>Baruch Ivcher School of Psychology, Reichman University, Herzliya, Israel</p><p>Jonathan Levy</p></li><li><p>Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland</p><p>Jonathan Levy</p></li><li><p>School of Psychology, Dublin City University, Dublin, Ireland</p><p>Darragh McCashin</p></li><li><p>University of Montana, Missoula, MT, USA</p><p>Alexander L. Metcalf</p></li><li><p>Graduate School of Human Sciences, Osaka University, Suita, Japan</p><p>Asako Miura</p></li><li><p>SEELE Neuroscience, Mexico City, Mexico</p><p>César Monroy-Fonseca</p></li><li><p>School of Psychology, University of Auckland, Auckland, New Zealand</p><p>David Moreau</p></li><li><p>Faculty of Economics, Maria Curie-Skłodowska University, Lublin, Poland</p><p>Rafał Muda</p></li><li><p>Department of Psychology, The City University of New York (CUNY) Graduate Center, New York, NY, USA</p><p>Annalisa Myer</p></li><li><p>Australian National Centre for the Public Awareness of Science, Australian National University, Canberra, ACT, Australia</p><p>Matthew S. Nurse</p></li><li><p>Department of Social Psychology, Graduate School of Humanities and Sociology, University of Tokyo, Tokyo, Japan</p><p>Yohsuke Ohtsubo</p></li><li><p>Department of Public Administration and Sociology, Erasmus University Rotterdam, Rotterdam, Netherlands</p><p>Michal Onderco</p></li><li><p>Center for Social Sciences, Hungarian Academy of Sciences Center of Excellence, Budapest, Hungary</p><p>Zsófia Papp</p></li><li><p>Institute of Psychology, University of Silesia, Katowice, Poland</p><p>Mariola Paruzel-Czachura</p></li><li><p>Complutense University in Madrid, Madrid, Spain</p><p>Mariola Paruzel-Czachura</p></li><li><p>Department of Psychology, University of Belgrade, Belgrade, Serbia</p><p>Zoran Pavlović</p></li><li><p>Universidad Nacional de Colombia, Sede de La Paz, La Paz, Colombia</p><p>César Payán-Gómez</p></li><li><p>Vidyasagar College For Women, Kolkata, India</p><p>Rajib Prasad</p></li><li><p>AGH University of Science and Technology, Kraków, Poland</p><p>Joanna Pyrkosz-Pacyna</p></li><li><p>Department of Computer Science, University of Colorado Boulder, Boulder, CO, USA</p><p>Ali Raza</p></li><li><p>Institute of Cognitive Science, University of Colorado Boulder, Boulder, CO, USA</p><p>Ali Raza</p></li><li><p>Stanford University, Stanford, CA, USA</p><p>Kasey Rhee</p></li><li><p>Department of Biology, University of Turku, Turku, Finland</p><p>Teemu Saikkonen</p></li><li><p>Cooperative University of Colombia, Bogotá, Colombia</p><p>Natalia Santiago-Tovar</p></li><li><p>Newcastle Business School, University of Newcastle, Callaghan, NSW, Australia</p><p>David Savage</p></li><li><p>Department of Global Economics and Management, University of Groningen, Groningen, Netherlands</p><p>Ahmed Skali</p></li><li><p>Brain and Mind Institute, University of Western Ontario, London, ON, Canada</p><p>Clara Alexandra Stafford</p></li><li><p>Western Interdisciplinary Research Building, University of Western Ontario, London, ON, Canada</p><p>Clara Alexandra Stafford</p></li><li><p>Department of Sociology, University of Belgrade, Belgrade, Serbia</p><p>Dragan Stanojević</p></li><li><p>Department of Psychology, Carleton University, Ottawa, ON, Canada</p><p>Anna Stefaniak &amp; Michael J. A. Wohl</p></li><li><p>National University of Political Studies and Public Administration (SNSPA), Bucharest, Romania</p><p>Augustin Stoica</p></li><li><p>Research Institute at Medical University of Plovdiv), Division of Translational Neuroscience, Plovdiv, Bulgaria</p><p>Kristina K. Stoyanova</p></li><li><p>Department of Cognitive Science, ENS, EHESS, CNRS, Institut Jean Nicod, PSL Research University, Paris, France</p><p>Brent Strickland</p></li><li><p>CREMA - Center for Research in Economics, Management and the Arts, Basel, Switzerland</p><p>Benno Torgler</p></li><li><p>The Warburg Institute, School of Advanced Study, University of London, London, England</p><p>Raffaele Tucciarelli</p></li><li><p>Institute of Cognitive Neuroscience, University College London, London, England</p><p>Raffaele Tucciarelli</p></li><li><p>Institute for Emerging Market Studies, The Hong Kong University of Science and Technology, Kowloon, Hong Kong</p><p>Michael Tyrala</p></li><li><p>Department of Psychology, Susquehanna University, Selinsgrove, PA, USA</p><p>Nick D. Ungson</p></li><li><p>Psychology Department, Dokuz Eylül University, İzmir, Turkey</p><p>Mete S. Uysal</p></li><li><p>Department of Experimental and Applied Psychology, VU Amsterdam, Amsterdam, Netherlands</p><p>Paul A. M. Van Lange &amp; Jan-Willem van Prooijen</p></li><li><p>Faculty of Design Sciences, University of Antwerp, Antwerpen, Belgium</p><p>Dirk van Rooy</p></li><li><p>Department of Behavioural Sciences and Learning (IBL), Linköping University, Linköping, Sweden</p><p>Daniel Västfjäll</p></li><li><p>Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, Netherlands</p><p>Peter Verkoeijen &amp; Rolf A. Zwaan</p></li><li><p>University of Koblenz-Landau, Landau, Germany</p><p>Christian von Sikorski</p></li><li><p>Health Communication Research Unit, School of Human and Community Development, University of the Witwatersrand, Johannesburg, South Africa</p><p>Jennifer Watermeyer</p></li><li><p>Department of Entrepreneurship, Innovation, and Technology, Stockholm School of Economics, Stockholm, Sweden</p><p>Erik Wetter</p></li><li><p>Harvard Business School, Harvard University, Cambridge, MA, USA</p><p>Ashley Whillans</p></li><li><p>Nicolaus Copernicus University, Toruń, Poland</p><p>Adrian Dominik Wójcik</p></li><li><p>University of California, San Diego, La Jolla, CA, USA</p><p>Kaidi Wu</p></li><li><p>Kyushu University, Fukuoka, Japan</p><p>Yuki Yamada</p></li><li><p>Department of Psychology, Kadir Has University, Istanbul, Turkey</p><p>Onurcan Yilmaz</p></li></ol><div><p><span>Authors</span></p><ol><li><span>Flavio Azevedo</span></li><li><span>Tomislav Pavlović</span></li><li><span>Gabriel G. Rêgo</span></li><li><span>F. Ceren Ay</span></li><li><span>Biljana Gjoneska</span></li><li><span>Tom W. Etienne</span></li><li><span>Robert M. Ross</span></li><li><span>Philipp Schönegger</span></li><li><span>Julián C. Riaño-Moreno</span></li><li><span>Aleksandra Cichocka</span></li><li><span>Valerio Capraro</span></li><li><span>Luca Cian</span></li><li><span>Chiara Longoni</span></li><li><span>Ho Fai Chan</span></li><li><span>Jay J. Van Bavel</span></li><li><span>Hallgeir Sjåstad</span></li><li><span>John B. Nezlek</span></li><li><span>Mark Alfano</span></li><li><span>Michele J. Gelfand</span></li><li><span>Michèle D. Birtel</span></li><li><span>Aleksandra Cislak</span></li><li><span>Patricia L. Lockwood</span></li><li><span>Koen Abts</span></li><li><span>Elena Agadullina</span></li><li><span>John Jamir Benzon Aruta</span></li><li><span>Sahba Nomvula Besharati</span></li><li><span>Alexander Bor</span></li><li><span>Becky L. Choma</span></li><li><span>Charles David Crabtree</span></li><li><span>William A. Cunningham</span></li><li><span>Koustav De</span></li><li><span>Waqas Ejaz</span></li><li><span>Christian T. Elbaek</span></li><li><span>Andrej Findor</span></li><li><span>Daniel Flichtentrei</span></li><li><span>Renata Franc</span></li><li><span>June Gruber</span></li><li><span>Estrella Gualda</span></li><li><span>Yusaku Horiuchi</span></li><li><span>Toan Luu Duc Huynh</span></li><li><span>Agustin Ibanez</span></li><li><span>Mostak Ahamed Imran</span></li><li><span>Jacob Israelashvili</span></li><li><span>Katarzyna Jasko</span></li><li><span>Jaroslaw Kantorowicz</span></li><li><span>Elena Kantorowicz-Reznichenko</span></li><li><span>André Krouwel</span></li><li><span>Michael Laakasuo</span></li><li><span>Claus Lamm</span></li><li><span>Caroline Leygue</span></li><li><span>Ming-Jen Lin</span></li><li><span>Mohammad Sabbir Mansoor</span></li><li><span>Antoine Marie</span></li><li><span>Lewend Mayiwar</span></li><li><span>Honorata Mazepus</span></li><li><span>Cillian McHugh</span></li><li><span>John Paul Minda</span></li><li><span>Panagiotis Mitkidis</span></li><li><span>Andreas Olsson</span></li><li><span>Tobias Otterbring</span></li><li><span>Dominic J. Packer</span></li><li><span>Anat Perry</span></li><li><span>Michael Bang Petersen</span></li><li><span>Arathy Puthillam</span></li><li><span>Tobias Rothmund</span></li><li><span>Hernando Santamaría-García</span></li><li><span>Petra C. Schmid</span></li><li><span>Drozdstoy Stoyanov</span></li><li><span>Shruti Tewari</span></li><li><span>Bojan Todosijević</span></li><li><span>Manos Tsakiris</span></li><li><span>Hans H. Tung</span></li><li><span>Radu G. Umbres</span></li><li><span>Edmunds Vanags</span></li><li><span>Madalina Vlasceanu</span></li><li><span>Andrew Vonasch</span></li><li><span>Meltem Yucel</span></li><li><span>Yucheng Zhang</span></li><li><span>Mohcine Abad</span></li><li><span>Eli Adler</span></li><li><span>Narin Akrawi</span></li><li><span>Hamza Alaoui Mdarhri</span></li><li><span>Hanane Amara</span></li><li><span>David M. Amodio</span></li><li><span>Benedict G. Antazo</span></li><li><span>Matthew Apps</span></li><li><span>Mouhamadou Hady Ba</span></li><li><span>Sergio Barbosa</span></li><li><span>Brock Bastian</span></li><li><span>Anton Berg</span></li><li><span>Maria P. Bernal-Zárate</span></li><li><span>Michael Bernstein</span></li><li><span>Michał Białek</span></li><li><span>Ennio Bilancini</span></li><li><span>Natalia Bogatyreva</span></li><li><span>Leonardo Boncinelli</span></li><li><span>Jonathan E. Booth</span></li><li><span>Sylvie Borau</span></li><li><span>Ondrej Buchel</span></li><li><span>C. Daryl Cameron</span></li><li><span>Chrissie F. Carvalho</span></li><li><span>Tatiana Celadin</span></li><li><span>Chiara Cerami</span></li><li><span>Hom Nath Chalise</span></li><li><span>Xiaojun Cheng</span></li><li><span>Kate Cockcroft</span></li><li><span>Jane Conway</span></li><li><span>Mateo Andres Córdoba-Delgado</span></li><li><span>Chiara Crespi</span></li><li><span>Marie Crouzevialle</span></li><li><span>Jo Cutler</span></li><li><span>Marzena Cypryańska</span></li><li><span>Justyna Dabrowska</span></li><li><span>Michael A. Daniels</span></li><li><span>Victoria H. Davis</span></li><li><span>Pamala N. Dayley</span></li><li><span>Sylvain Delouvée</span></li><li><span>Ognjan Denkovski</span></li><li><span>Guillaume Dezecache</span></li><li><span>Nathan A. Dhaliwal</span></li><li><span>Alelie B. Diato</span></li><li><span>Roberto Di Paolo</span></li><li><span>Marianna Drosinou</span></li><li><span>Uwe Dulleck</span></li><li><span>Jānis Ekmanis</span></li><li><span>Arhan S. Ertan</span></li><li><span>Hapsa Hossain Farhana</span></li><li><span>Fahima Farkhari</span></li><li><span>Harry Farmer</span></li><li><span>Ali Fenwick</span></li><li><span>Kristijan Fidanovski</span></li><li><span>Terry Flew</span></li><li><span>Shona Fraser</span></li><li><span>Raymond Boadi Frempong</span></li><li><span>Jonathan A. Fugelsang</span></li><li><span>Jessica Gale</span></li><li><span>E. Begoña Garcia-Navarro</span></li><li><span>Prasad Garladinne</span></li><li><span>Oussama Ghajjou</span></li><li><span>Theofilos Gkinopoulos</span></li><li><span>Kurt Gray</span></li><li><span>Siobhán M. Griffin</span></li><li><span>Bjarki Gronfeldt</span></li><li><span>Mert Gümren</span></li><li><span>Ranju Lama Gurung</span></li><li><span>Eran Halperin</span></li><li><span>Elizabeth Harris</span></li><li><span>Volo Herzon</span></li><li><span>Matej Hruška</span></li><li><span>Guanxiong Huang</span></li><li><span>Matthias F. C. Hudecek</span></li><li><span>Ozan Isler</span></li><li><span>Simon Jangard</span></li><li><span>Frederik J. Jorgensen</span></li><li><span>Frank Kachanoff</span></li><li><span>John Kahn</span></li><li><span>Apsara Katuwal Dangol</span></li><li><span>Oleksandra Keudel</span></li><li><span>Lina Koppel</span></li><li><span>Mika Koverola</span></li><li><span>Emily Kubin</span></li><li><span>Anton Kunnari</span></li><li><span>Yordan Kutiyski</span></li><li><span>Oscar Moreda Laguna</span></li><li><span>Josh Leota</span></li><li><span>Eva Lermer</span></li><li><span>Jonathan Levy</span></li><li><span>Neil Levy</span></li><li><span>Chunyun Li</span></li><li><span>Elizabeth U. Long</span></li><li><span>Marina Maglić</span></li><li><span>Darragh McCashin</span></li><li><span>Alexander L. Metcalf</span></li><li><span>Igor Mikloušić</span></li><li><span>Soulaimane El Mimouni</span></li><li><span>Asako Miura</span></li><li><span>Juliana Molina-Paredes</span></li><li><span>César Monroy-Fonseca</span></li><li><span>Elena Morales-Marente</span></li><li><span>David Moreau</span></li><li><span>Rafał Muda</span></li><li><span>Annalisa Myer</span></li><li><span>Kyle Nash</span></li><li><span>Tarik Nesh-Nash</span></li><li><span>Jonas P. Nitschke</span></li><li><span>Matthew S. Nurse</span></li><li><span>Yohsuke Ohtsubo</span></li><li><span>Victoria Oldemburgo de Mello</span></li><li><span>Cathal O’Madagain</span></li><li><span>Michal Onderco</span></li><li><span>M. Soledad Palacios-Galvez</span></li><li><span>Jussi Palomöki</span></li><li><span>Yafeng Pan</span></li><li><span>Zsófia Papp</span></li><li><span>Philip Pärnamets</span></li><li><span>Mariola Paruzel-Czachura</span></li><li><span>Zoran Pavlović</span></li><li><span>César Payán-Gómez</span></li><li><span>Silva Perander</span></li><li><span>Michael Mark Pitman</span></li><li><span>Rajib Prasad</span></li><li><span>Joanna Pyrkosz-Pacyna</span></li><li><span>Steve Rathje</span></li><li><span>Ali Raza</span></li><li><span>Kasey Rhee</span></li><li><span>Claire E. Robertson</span></li><li><span>Iván Rodríguez-Pascual</span></li><li><span>Teemu Saikkonen</span></li><li><span>Octavio Salvador-Ginez</span></li><li><span>Gaia C. Santi</span></li><li><span>Natalia Santiago-Tovar</span></li><li><span>David Savage</span></li><li><span>Julian A. Scheffer</span></li><li><span>David T. Schultner</span></li><li><span>Enid M. Schutte</span></li><li><span>Andy Scott</span></li><li><span>Madhavi Sharma</span></li><li><span>Pujan Sharma</span></li><li><span>Ahmed Skali</span></li><li><span>David Stadelmann</span></li><li><span>Clara Alexandra Stafford</span></li><li><span>Dragan Stanojević</span></li><li><span>Anna Stefaniak</span></li><li><span>Anni Sternisko</span></li><li><span>Augustin Stoica</span></li><li><span>Kristina K. Stoyanova</span></li><li><span>Brent Strickland</span></li><li><span>Jukka Sundvall</span></li><li><span>Jeffrey P. Thomas</span></li><li><span>Gustav Tinghög</span></li><li><span>Benno Torgler</span></li><li><span>Iris J. Traast</span></li><li><span>Raffaele Tucciarelli</span></li><li><span>Michael Tyrala</span></li><li><span>Nick D. Ungson</span></li><li><span>Mete S. Uysal</span></li><li><span>Paul A. M. Van Lange</span></li><li><span>Jan-Willem van Prooijen</span></li><li><span>Dirk van Rooy</span></li><li><span>Daniel Västfjäll</span></li><li><span>Peter Verkoeijen</span></li><li><span>Joana B. Vieira</span></li><li><span>Christian von Sikorski</span></li><li><span>Alexander Cameron Walker</span></li><li><span>Jennifer Watermeyer</span></li><li><span>Erik Wetter</span></li><li><span>Ashley Whillans</span></li><li><span>Katherine White</span></li><li><span>Rishad Habib</span></li><li><span>Robin Willardt</span></li><li><span>Michael J. A. Wohl</span></li><li><span>Adrian Dominik Wójcik</span></li><li><span>Kaidi Wu</span></li><li><span>Yuki Yamada</span></li><li><span>Onurcan Yilmaz</span></li><li><span>Kumar Yogeeswaran</span></li><li><span>Carolin-Theresa Ziemer</span></li><li><span>Rolf A. Zwaan</span></li><li><span>Paulo S. Boggio</span></li><li><span>Waldir M. Sampaio</span></li></ol></div><h3 id=\"contributions\">Contributions</h3><p>Conceptualization: F.A. Data curation: F.A., T.P., W.M.S. and G.R. Formal analysis: F.A., F.C.A., T.P., T.E. and J.C.R. Investigation: F.A. Methodology: F.A. Project administration: F.A. Resources: F.A. Software: F.A. and T.P. Supervision: F.A. Validation: F.A. and R.M.R. Visualization: F.A., F.C.A., T.E., H.F.C., L.C., C.L. and J.C.R. Writing - original draft: F.A., B.G., R.M.R. and P.S. Writing - review &amp; editing: ICSMP Collaborators.</p><h3 id=\"corresponding-author\">Corresponding author</h3><p>Correspondence to\n                <a target=\"_blank\" href=\"mailto:[email protected]\">Flavio Azevedo</a>.</p></div></div><div><h2 id=\"ethics\">Ethics declarations</h2><div>\n                <h3 id=\"FPar1\">Competing interests</h3>\n                <p>André Krouwel (ownership and stocks in Kieskompas BV, a data collector in this project). No payment was received by the author. No other authors reported a competing interest.</p>\n            </div></div><div><h2 id=\"additional-information\">Additional information</h2><p><b>Publisher’s note</b> Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></div><div><h2 id=\"rightslink\">Rights and permissions</h2><div>\n                <p><b>Open Access</b>  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit <a target=\"_blank\" href=\"http://creativecommons.org/licenses/by/4.0/\">http://creativecommons.org/licenses/by/4.0/</a>.</p>\n              <p><a target=\"_blank\" href=\"https://s100.copyright.com/AppDispatchServlet?title=Social%20and%20moral%20psychology%20of%20COVID-19%20across%2069%20countries&amp;author=Flavio%20Azevedo%20et%20al&amp;contentID=10.1038%2Fs41597-023-02080-8&amp;copyright=The%20Author%28s%29&amp;publication=2052-4463&amp;publicationDate=2023-05-11&amp;publisherName=SpringerNature&amp;orderBeanReset=true&amp;oa=CC%20BY\">Reprints and permissions</a></p></div></div><div><h2 id=\"article-info\">About this article</h2><div><h3 id=\"citeas\">Cite this article</h3><p>Azevedo, F., Pavlović, T., Rêgo, G.G. <i>et al.</i> Social and moral psychology of COVID-19 across 69 countries.\n                    <i>Sci Data</i> <b>10</b>, 272 (2023). https://doi.org/10.1038/s41597-023-02080-8</p><p><a target=\"_blank\" href=\"https://citation-needed.springer.com/v2/references/10.1038/s41597-023-02080-8?format=refman&amp;flavour=citation\">Download citation</a></p><ul><li><p>Received<span>: </span><span>31 May 2022</span></p></li><li><p>Accepted<span>: </span><span>16 March 2023</span></p></li><li><p>Published<span>: </span><span>11 May 2023</span></p></li><li><p><abbr title=\"Digital Object Identifier\">DOI</abbr><span>: </span><span>https://doi.org/10.1038/s41597-023-02080-8</span></p></li></ul></div></div>\n            </div>",
  "author": "Sampaio, Waldir M.",
  "favicon": "https://www.nature.com/static/images/favicons/nature/favicon.ico",
  "source": "nature.com",
  "published": "2023-05-11",
  "ttr": 1714,
  "type": "article"
}