COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak

COVIDiSTRESS Global Survey Consortium

doi:10.1038/s41597-020-00784-9

COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak

COVIDiSTRESS Global Survey Consortium

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Abstract

This N = 173,426 social science dataset was collected through the collaborative COVIDiSTRESS Global Survey – an open science effort to improve understanding of the human experiences of the 2020 COVID-19 pandemic between 30th March and 30th May, 2020. The dataset allows a cross-cultural study of psychological and behavioural responses to the Coronavirus pandemic and associated government measures like cancellation of public functions and stay at home orders implemented in many countries. The dataset contains demographic background variables as well as measures of Asian Disease Problem, perceived stress (PSS-10), availability of social provisions (SPS-10), trust in various authorities, trust in governmental measures to contain the virus (OECD trust), personality traits (BFF-15), information behaviours, agreement with the level of government intervention, and compliance with preventive measures, along with a rich pool of exploratory variables and written experiences. A global consortium from 39 countries and regions worked together to build and translate a survey with variables of shared interests, and recruited participants in 47 languages and dialects. Raw plus cleaned data and dynamic visualizations are available.

Original language	English
Article number	3
Pages (from-to)	1-27
Number of pages	27
Journal	Scientific Data
Volume	8
Issue number	1
DOIs	https://doi.org/10.1038/s41597-020-00784-9
Publication status	Published - Dec 2021

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ArticleFinal published version, 1.21 MBLicence: CC BY

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@article{26b54871a879420281a33cb9ada8c2e1,

title = "COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak",

abstract = "This N = 173,426 social science dataset was collected through the collaborative COVIDiSTRESS Global Survey – an open science effort to improve understanding of the human experiences of the 2020 COVID-19 pandemic between 30th March and 30th May, 2020. The dataset allows a cross-cultural study of psychological and behavioural responses to the Coronavirus pandemic and associated government measures like cancellation of public functions and stay at home orders implemented in many countries. The dataset contains demographic background variables as well as measures of Asian Disease Problem, perceived stress (PSS-10), availability of social provisions (SPS-10), trust in various authorities, trust in governmental measures to contain the virus (OECD trust), personality traits (BFF-15), information behaviours, agreement with the level of government intervention, and compliance with preventive measures, along with a rich pool of exploratory variables and written experiences. A global consortium from 39 countries and regions worked together to build and translate a survey with variables of shared interests, and recruited participants in 47 languages and dialects. Raw plus cleaned data and dynamic visualizations are available.",

author = "{COVIDiSTRESS Global Survey Consortium} and Yuki Yamada and {\'C}epuli{\'c}, {Dominik Borna} and Tao Coll-Mart{\'i}n and St{\'e}phane Debove and Guillaume Gautreau and Hyemin Han and Jesper Rasmussen and Tran, {Thao P.} and Travaglino, {Giovanni A.} and Blackburn, {Ang{\'e}lique M.} and Lo{\"i}s Boullu and Mila Buji{\'c} and Grace Byrne and Cani{\"e}ls, {Marjolein C.J.} and Ivan Flis and Marta Kowal and Rachev, {Nikolay R.} and Vicenta Reynoso-Alc{\'a}ntara and Oulmann Zerhouni and Oli Ahmed and Rizwana Amin and Sibele Aquino and Areias, {Jo{\~a}o Carlos} and Aruta, {John Jamir Benzon R.} and Dastan Bamwesigye and Jozef Bavolar and Bender, {Andrew R.} and Pratik Bhandari and Tuba Bircan and Huseyin Cakal and Tereza Capelos and Ji{\v r}{\'i} {\v C}en{\v e}k and Brendan Ch{\textquoteright}ng and Chen, {Fang Yu} and Stavroula Chrona and Contreras-Ib{\'a}{\~n}ez, {Carlos C.} and Correa, {Pablo Sebasti{\'a}n} and Irene Cristofori and Wilson Cyrus-Lai and Guillermo Delgado-Garcia and Eliane Deschrijver and Carlos D{\'i}az and İlknur Dilekler and Vilius Dranseika and Dmitrii Dubrov and Kristina Eichel and Eda Ermagan-Caglar and Rebekah Gelp{\'i} and Gonz{\'a}lez, {Rub{\'e}n Flores} and Amanda Griffin and Hakim, {Moh Abdul} and Krzysztof Hanusz and Ho, {Yuen Wan} and Dayana Hristova and Barbora Hubena and Keiko Ihaya and Gozde Ikizer and Islam, {Md Nurul} and Alma Jeftic and Shruti Jha and Ju{\'a}rez, {Fernanda P{\'e}rez Gay} and Pavol Kacmar and Kalina Kalinova and Kavanagh, {Phillip S.} and Mehmet Kosa and Karolina Kosza{\l}kowska and Raisa Kumaga and David Lacko and Yookyung Lee and Lentoor, {Antonio G.} and {De Leon}, {Gabriel A.} and Lin, {Shiang Yi} and Samuel Lins and L{\'o}pez, {Claudio Rafael Castro} and Lys, {Agnieszka E.} and Samkelisiwe Mahlungulu and Tsvetelina Makaveeva and Salom{\'e} Mamede and Silvia Mari and Marot, {Tiago A.} and Liz Martinez and Dar Meshi and Mola, {D{\'e}bora Jeanette} and Sara Morales-Izquierdo and Arian Musliu and Naidu, {Priyanka A.} and Arooj Najmussaqib and Natividade, {Jean C.} and Steve Nebel and Jana Nezkusilova and Irina Nikolova and Manuel Ninaus and Valdas Noreika and Ortiz, {Mar{\'i}a Victoria} and Ozery, {Daphna Hausman} and Daniel Pankowski and Tiziana Pennato and Martin P{\'i}rko and Lotte Pummerer and Cecilia Reyna and Eugenia Romano and Hafize Sahin and Sanli, {Aybegum Memisoglu} and G{\"u}lden Sayılan and Alessia Scarpaci and Cristina Sechi and Maor Shani and Aya Shata and Pilleriin Sikka and Nidhi Sinha and Sabrina St{\"o}ckli and Anna Studzinska and Emilija Sungailaite and Zea Szebeni and Benjamin Tag and Mihaela Taranu and Franco Tisocco and Jarno Tuominen and Fidan Turk and Uddin, {Muhammad Kamal} and Ena Uzelac and Sara Vestergren and Roosevelt Vilar and Wang, {Austin Horng En} and West, {J. No{\"e}l} and Wu, {Charles K.S.} and Teodora Yaneva and Yeh, {Yao Yuan} and Andreas Lieberoth",

note = "Funding Information: The COVIDiSTRESS 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. All funding information is listed in the supplementary material (Figure S1). We also want to address thanks to the IFB (Institut Fran\u00E7ais de Bioinformatique, https://www.france-bioinformatique.fr/) for hosting the server Shiny illustrating our results. This research was supported by JSPS KAKENHI Grants JP17H00875, JP18K12015, JP20H04581, JP20K14222, Czech Science Foundation GC19-09265J, Consejo Nacional de Ciencia y Tecnologia (Conacyt), Full National Scholarship - MSc degree (CVU: 613905), Research Foundation Flanders (FWO) postdoctoral fellowship, and The HSE University Basic Research Program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: {\textcopyright} 2021, The Author(s).",

year = "2021",

month = dec,

doi = "10.1038/s41597-020-00784-9",

language = "English",

volume = "8",

pages = "1--27",

journal = "Scientific Data",

issn = "2052-4463",

publisher = "Nature Publishing Group",

number = "1",

}

TY - JOUR

T1 - COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak

AU - COVIDiSTRESS Global Survey Consortium

AU - Yamada, Yuki

AU - Ćepulić, Dominik Borna

AU - Coll-Martín, Tao

AU - Debove, Stéphane

AU - Gautreau, Guillaume

AU - Han, Hyemin

AU - Rasmussen, Jesper

AU - Tran, Thao P.

AU - Travaglino, Giovanni A.

AU - Blackburn, Angélique M.

AU - Boullu, Loïs

AU - Bujić, Mila

AU - Byrne, Grace

AU - Caniëls, Marjolein C.J.

AU - Flis, Ivan

AU - Kowal, Marta

AU - Rachev, Nikolay R.

AU - Reynoso-Alcántara, Vicenta

AU - Zerhouni, Oulmann

AU - Ahmed, Oli

AU - Amin, Rizwana

AU - Aquino, Sibele

AU - Areias, João Carlos

AU - Aruta, John Jamir Benzon R.

AU - Bamwesigye, Dastan

AU - Bavolar, Jozef

AU - Bender, Andrew R.

AU - Bhandari, Pratik

AU - Bircan, Tuba

AU - Cakal, Huseyin

AU - Capelos, Tereza

AU - Čeněk, Jiří

AU - Ch’ng, Brendan

AU - Chen, Fang Yu

AU - Chrona, Stavroula

AU - Contreras-Ibáñez, Carlos C.

AU - Correa, Pablo Sebastián

AU - Cristofori, Irene

AU - Cyrus-Lai, Wilson

AU - Delgado-Garcia, Guillermo

AU - Deschrijver, Eliane

AU - Díaz, Carlos

AU - Dilekler, İlknur

AU - Dranseika, Vilius

AU - Dubrov, Dmitrii

AU - Eichel, Kristina

AU - Ermagan-Caglar, Eda

AU - Gelpí, Rebekah

AU - González, Rubén Flores

AU - Griffin, Amanda

AU - Hakim, Moh Abdul

AU - Hanusz, Krzysztof

AU - Ho, Yuen Wan

AU - Hristova, Dayana

AU - Hubena, Barbora

AU - Ihaya, Keiko

AU - Ikizer, Gozde

AU - Islam, Md Nurul

AU - Jeftic, Alma

AU - Jha, Shruti

AU - Juárez, Fernanda Pérez Gay

AU - Kacmar, Pavol

AU - Kalinova, Kalina

AU - Kavanagh, Phillip S.

AU - Kosa, Mehmet

AU - Koszałkowska, Karolina

AU - Kumaga, Raisa

AU - Lacko, David

AU - Lee, Yookyung

AU - Lentoor, Antonio G.

AU - De Leon, Gabriel A.

AU - Lin, Shiang Yi

AU - Lins, Samuel

AU - López, Claudio Rafael Castro

AU - Lys, Agnieszka E.

AU - Mahlungulu, Samkelisiwe

AU - Makaveeva, Tsvetelina

AU - Mamede, Salomé

AU - Mari, Silvia

AU - Marot, Tiago A.

AU - Martinez, Liz

AU - Meshi, Dar

AU - Mola, Débora Jeanette

AU - Morales-Izquierdo, Sara

AU - Musliu, Arian

AU - Naidu, Priyanka A.

AU - Najmussaqib, Arooj

AU - Natividade, Jean C.

AU - Nebel, Steve

AU - Nezkusilova, Jana

AU - Nikolova, Irina

AU - Ninaus, Manuel

AU - Noreika, Valdas

AU - Ortiz, María Victoria

AU - Ozery, Daphna Hausman

AU - Pankowski, Daniel

AU - Pennato, Tiziana

AU - Pírko, Martin

AU - Pummerer, Lotte

AU - Reyna, Cecilia

AU - Romano, Eugenia

AU - Sahin, Hafize

AU - Sanli, Aybegum Memisoglu

AU - Sayılan, Gülden

AU - Scarpaci, Alessia

AU - Sechi, Cristina

AU - Shani, Maor

AU - Shata, Aya

AU - Sikka, Pilleriin

AU - Sinha, Nidhi

AU - Stöckli, Sabrina

AU - Studzinska, Anna

AU - Sungailaite, Emilija

AU - Szebeni, Zea

AU - Tag, Benjamin

AU - Taranu, Mihaela

AU - Tisocco, Franco

AU - Tuominen, Jarno

AU - Turk, Fidan

AU - Uddin, Muhammad Kamal

AU - Uzelac, Ena

AU - Vestergren, Sara

AU - Vilar, Roosevelt

AU - Wang, Austin Horng En

AU - West, J. Noël

AU - Wu, Charles K.S.

AU - Yaneva, Teodora

AU - Yeh, Yao Yuan

AU - Lieberoth, Andreas

N1 - Funding Information: The COVIDiSTRESS 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. All funding information is listed in the supplementary material (Figure S1). We also want to address thanks to the IFB (Institut Fran\u00E7ais de Bioinformatique, https://www.france-bioinformatique.fr/) for hosting the server Shiny illustrating our results. This research was supported by JSPS KAKENHI Grants JP17H00875, JP18K12015, JP20H04581, JP20K14222, Czech Science Foundation GC19-09265J, Consejo Nacional de Ciencia y Tecnologia (Conacyt), Full National Scholarship - MSc degree (CVU: 613905), Research Foundation Flanders (FWO) postdoctoral fellowship, and The HSE University Basic Research Program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: © 2021, The Author(s).

PY - 2021/12

Y1 - 2021/12

N2 - This N = 173,426 social science dataset was collected through the collaborative COVIDiSTRESS Global Survey – an open science effort to improve understanding of the human experiences of the 2020 COVID-19 pandemic between 30th March and 30th May, 2020. The dataset allows a cross-cultural study of psychological and behavioural responses to the Coronavirus pandemic and associated government measures like cancellation of public functions and stay at home orders implemented in many countries. The dataset contains demographic background variables as well as measures of Asian Disease Problem, perceived stress (PSS-10), availability of social provisions (SPS-10), trust in various authorities, trust in governmental measures to contain the virus (OECD trust), personality traits (BFF-15), information behaviours, agreement with the level of government intervention, and compliance with preventive measures, along with a rich pool of exploratory variables and written experiences. A global consortium from 39 countries and regions worked together to build and translate a survey with variables of shared interests, and recruited participants in 47 languages and dialects. Raw plus cleaned data and dynamic visualizations are available.

AB - This N = 173,426 social science dataset was collected through the collaborative COVIDiSTRESS Global Survey – an open science effort to improve understanding of the human experiences of the 2020 COVID-19 pandemic between 30th March and 30th May, 2020. The dataset allows a cross-cultural study of psychological and behavioural responses to the Coronavirus pandemic and associated government measures like cancellation of public functions and stay at home orders implemented in many countries. The dataset contains demographic background variables as well as measures of Asian Disease Problem, perceived stress (PSS-10), availability of social provisions (SPS-10), trust in various authorities, trust in governmental measures to contain the virus (OECD trust), personality traits (BFF-15), information behaviours, agreement with the level of government intervention, and compliance with preventive measures, along with a rich pool of exploratory variables and written experiences. A global consortium from 39 countries and regions worked together to build and translate a survey with variables of shared interests, and recruited participants in 47 languages and dialects. Raw plus cleaned data and dynamic visualizations are available.

UR - http://www.scopus.com/inward/record.url?scp=85098661855&partnerID=8YFLogxK

U2 - 10.1038/s41597-020-00784-9

DO - 10.1038/s41597-020-00784-9

M3 - Article

C2 - 33398078

AN - SCOPUS:85098661855

SN - 2052-4463

VL - 8

SP - 1

EP - 27

JO - Scientific Data

JF - Scientific Data

IS - 1

M1 - 3

ER -

COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak

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