COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak
- Autores
- Yamada, Yuki; Ćepulić, Dominik Borna; Coll Martín, Tao; Debove, Stéphane; Gautreau, Guillaume; Han, Hyemin; Rasmussen, Jesper; Tran, Thao P.; Travaglino, Giovanni A.; Blackburn, Angélique M.; Boullu, Loïs; Bujić, Mila; Byrne, Grace; Caniëls, Marjolein C. J.; Flis, Ivan; Kowal, Marta; Rachev, Nikolay R.; Reynoso Alcántara, Vicenta; Zerhouni, Oulmann; Ahmed, Oli; Amin, Rizwana; Aquino, Sibele; Areias, João Carlos; Aruta, John Jamir Benzon R.; Bamwesigye, Dastan; Bavolar, Jozef; Bender, Andrew R.; Bhandari, Pratik; Bircan, Tuba; Reyna, Cecilia
- Año de publicación
- 2021
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- 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.
Fil: Yamada, Yuki. Kyushu University; Japón
Fil: Ćepulić, Dominik Borna. Catholic University of Croatia; Croacia
Fil: Coll Martín, Tao. Universidad de Granada; España
Fil: Debove, Stéphane. Independent Researcher; Francia
Fil: Gautreau, Guillaume. Universite Paris Saclay; Francia
Fil: Han, Hyemin. University of Alabama at Birmingahm; Estados Unidos
Fil: Rasmussen, Jesper. University Aarhus; Dinamarca
Fil: Tran, Thao P.. State University of Colorado - Fort Collins; Estados Unidos
Fil: Travaglino, Giovanni A.. University Of Kent; Reino Unido
Fil: Blackburn, Angélique M.. Texas A&M University; Estados Unidos
Fil: Boullu, Loïs. Independent Researcher; Francia
Fil: Bujić, Mila. Universidad de Tampere; Finlandia
Fil: Byrne, Grace. Vrije Universiteit Amsterdam; Países Bajos
Fil: Caniëls, Marjolein C. J.. Open University of The Netherlands; Países Bajos
Fil: Flis, Ivan. Catholic University of Croatia; Croacia
Fil: Kowal, Marta. University of Wroclaw; Polonia
Fil: Rachev, Nikolay R.. Sofia University St. Kliment Ohridski; Bulgaria
Fil: Reynoso Alcántara, Vicenta. Universidad Nacional Autónoma de México; México
Fil: Zerhouni, Oulmann. Université Paris Nanterre; Francia
Fil: Ahmed, Oli. University of Chittagong; Bangladesh
Fil: Amin, Rizwana. Bahria University; Pakistán
Fil: Aquino, Sibele. Pontifícia Universidade Católica do Rio de Janeiro; Brasil
Fil: Areias, João Carlos. Universidad de Porto; Portugal
Fil: Aruta, John Jamir Benzon R.. de la Salle University; Filipinas
Fil: Bamwesigye, Dastan. Mendel University in Brno; República Checa
Fil: Bavolar, Jozef. Pavol Jozef Safarik University; Eslovaquia
Fil: Bender, Andrew R.. Michigan State University; Estados Unidos
Fil: Bhandari, Pratik. Universitat Saarland; Alemania
Fil: Bircan, Tuba. Vrije Unviversiteit Brussel; Bélgica
Fil: Reyna, Cecilia. Universidad Nacional de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina - Materia
-
dataset
psychology
COVID-19 - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
.jpg)
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/135516
Ver los metadatos del registro completo
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COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreakYamada, YukiĆepulić, Dominik BornaColl Martín, TaoDebove, StéphaneGautreau, GuillaumeHan, HyeminRasmussen, JesperTran, Thao P.Travaglino, Giovanni A.Blackburn, Angélique M.Boullu, LoïsBujić, MilaByrne, GraceCaniëls, Marjolein C. J.Flis, IvanKowal, MartaRachev, Nikolay R.Reynoso Alcántara, VicentaZerhouni, OulmannAhmed, OliAmin, RizwanaAquino, SibeleAreias, João CarlosAruta, John Jamir Benzon R.Bamwesigye, DastanBavolar, JozefBender, Andrew R.Bhandari, PratikBircan, TubaReyna, CeciliadatasetpsychologyCOVID-19https://purl.org/becyt/ford/5.1https://purl.org/becyt/ford/5This 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.Fil: Yamada, Yuki. Kyushu University; JapónFil: Ćepulić, Dominik Borna. Catholic University of Croatia; CroaciaFil: Coll Martín, Tao. Universidad de Granada; EspañaFil: Debove, Stéphane. Independent Researcher; FranciaFil: Gautreau, Guillaume. Universite Paris Saclay; FranciaFil: Han, Hyemin. University of Alabama at Birmingahm; Estados UnidosFil: Rasmussen, Jesper. University Aarhus; DinamarcaFil: Tran, Thao P.. State University of Colorado - Fort Collins; Estados UnidosFil: Travaglino, Giovanni A.. University Of Kent; Reino UnidoFil: Blackburn, Angélique M.. Texas A&M University; Estados UnidosFil: Boullu, Loïs. Independent Researcher; FranciaFil: Bujić, Mila. Universidad de Tampere; FinlandiaFil: Byrne, Grace. Vrije Universiteit Amsterdam; Países BajosFil: Caniëls, Marjolein C. J.. Open University of The Netherlands; Países BajosFil: Flis, Ivan. Catholic University of Croatia; CroaciaFil: Kowal, Marta. University of Wroclaw; PoloniaFil: Rachev, Nikolay R.. Sofia University St. Kliment Ohridski; BulgariaFil: Reynoso Alcántara, Vicenta. Universidad Nacional Autónoma de México; MéxicoFil: Zerhouni, Oulmann. Université Paris Nanterre; FranciaFil: Ahmed, Oli. University of Chittagong; BangladeshFil: Amin, Rizwana. Bahria University; PakistánFil: Aquino, Sibele. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Areias, João Carlos. Universidad de Porto; PortugalFil: Aruta, John Jamir Benzon R.. de la Salle University; FilipinasFil: Bamwesigye, Dastan. Mendel University in Brno; República ChecaFil: Bavolar, Jozef. Pavol Jozef Safarik University; EslovaquiaFil: Bender, Andrew R.. Michigan State University; Estados UnidosFil: Bhandari, Pratik. Universitat Saarland; AlemaniaFil: Bircan, Tuba. Vrije Unviversiteit Brussel; BélgicaFil: Reyna, Cecilia. Universidad Nacional de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaNature2021-01-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/135516Yamada, Yuki; Ćepulić, Dominik Borna; Coll Martín, Tao; Debove, Stéphane; Gautreau, Guillaume; et al.; COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak; Nature; Scientific Data; 8; 1; 4-1-2021; 1-232052-4463CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1038/s41597-020-00784-9info:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41597-020-00784-9info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:04:03Zoai:ri.conicet.gov.ar:11336/135516instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:04:03.736CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
| dc.title.none.fl_str_mv |
COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak |
| title |
COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak |
| spellingShingle |
COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak Yamada, Yuki dataset psychology COVID-19 |
| title_short |
COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak |
| title_full |
COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak |
| title_fullStr |
COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak |
| title_full_unstemmed |
COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak |
| title_sort |
COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak |
| dc.creator.none.fl_str_mv |
Yamada, Yuki Ćepulić, Dominik Borna Coll Martín, Tao Debove, Stéphane Gautreau, Guillaume Han, Hyemin Rasmussen, Jesper Tran, Thao P. Travaglino, Giovanni A. Blackburn, Angélique M. Boullu, Loïs Bujić, Mila Byrne, Grace Caniëls, Marjolein C. J. Flis, Ivan Kowal, Marta Rachev, Nikolay R. Reynoso Alcántara, Vicenta Zerhouni, Oulmann Ahmed, Oli Amin, Rizwana Aquino, Sibele Areias, João Carlos Aruta, John Jamir Benzon R. Bamwesigye, Dastan Bavolar, Jozef Bender, Andrew R. Bhandari, Pratik Bircan, Tuba Reyna, Cecilia |
| author |
Yamada, Yuki |
| author_facet |
Yamada, Yuki Ćepulić, Dominik Borna Coll Martín, Tao Debove, Stéphane Gautreau, Guillaume Han, Hyemin Rasmussen, Jesper Tran, Thao P. Travaglino, Giovanni A. Blackburn, Angélique M. Boullu, Loïs Bujić, Mila Byrne, Grace Caniëls, Marjolein C. J. Flis, Ivan Kowal, Marta Rachev, Nikolay R. Reynoso Alcántara, Vicenta Zerhouni, Oulmann Ahmed, Oli Amin, Rizwana Aquino, Sibele Areias, João Carlos Aruta, John Jamir Benzon R. Bamwesigye, Dastan Bavolar, Jozef Bender, Andrew R. Bhandari, Pratik Bircan, Tuba Reyna, Cecilia |
| author_role |
author |
| author2 |
Ćepulić, Dominik Borna Coll Martín, Tao Debove, Stéphane Gautreau, Guillaume Han, Hyemin Rasmussen, Jesper Tran, Thao P. Travaglino, Giovanni A. Blackburn, Angélique M. Boullu, Loïs Bujić, Mila Byrne, Grace Caniëls, Marjolein C. J. Flis, Ivan Kowal, Marta Rachev, Nikolay R. Reynoso Alcántara, Vicenta Zerhouni, Oulmann Ahmed, Oli Amin, Rizwana Aquino, Sibele Areias, João Carlos Aruta, John Jamir Benzon R. Bamwesigye, Dastan Bavolar, Jozef Bender, Andrew R. Bhandari, Pratik Bircan, Tuba Reyna, Cecilia |
| author2_role |
author author author author author author author author author author author author author author author author author author author author author author author author author author author author author |
| dc.subject.none.fl_str_mv |
dataset psychology COVID-19 |
| topic |
dataset psychology COVID-19 |
| purl_subject.fl_str_mv |
https://purl.org/becyt/ford/5.1 https://purl.org/becyt/ford/5 |
| dc.description.none.fl_txt_mv |
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. Fil: Yamada, Yuki. Kyushu University; Japón Fil: Ćepulić, Dominik Borna. Catholic University of Croatia; Croacia Fil: Coll Martín, Tao. Universidad de Granada; España Fil: Debove, Stéphane. Independent Researcher; Francia Fil: Gautreau, Guillaume. Universite Paris Saclay; Francia Fil: Han, Hyemin. University of Alabama at Birmingahm; Estados Unidos Fil: Rasmussen, Jesper. University Aarhus; Dinamarca Fil: Tran, Thao P.. State University of Colorado - Fort Collins; Estados Unidos Fil: Travaglino, Giovanni A.. University Of Kent; Reino Unido Fil: Blackburn, Angélique M.. Texas A&M University; Estados Unidos Fil: Boullu, Loïs. Independent Researcher; Francia Fil: Bujić, Mila. Universidad de Tampere; Finlandia Fil: Byrne, Grace. Vrije Universiteit Amsterdam; Países Bajos Fil: Caniëls, Marjolein C. J.. Open University of The Netherlands; Países Bajos Fil: Flis, Ivan. Catholic University of Croatia; Croacia Fil: Kowal, Marta. University of Wroclaw; Polonia Fil: Rachev, Nikolay R.. Sofia University St. Kliment Ohridski; Bulgaria Fil: Reynoso Alcántara, Vicenta. Universidad Nacional Autónoma de México; México Fil: Zerhouni, Oulmann. Université Paris Nanterre; Francia Fil: Ahmed, Oli. University of Chittagong; Bangladesh Fil: Amin, Rizwana. Bahria University; Pakistán Fil: Aquino, Sibele. Pontifícia Universidade Católica do Rio de Janeiro; Brasil Fil: Areias, João Carlos. Universidad de Porto; Portugal Fil: Aruta, John Jamir Benzon R.. de la Salle University; Filipinas Fil: Bamwesigye, Dastan. Mendel University in Brno; República Checa Fil: Bavolar, Jozef. Pavol Jozef Safarik University; Eslovaquia Fil: Bender, Andrew R.. Michigan State University; Estados Unidos Fil: Bhandari, Pratik. Universitat Saarland; Alemania Fil: Bircan, Tuba. Vrije Unviversiteit Brussel; Bélgica Fil: Reyna, Cecilia. Universidad Nacional de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina |
| description |
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. |
| publishDate |
2021 |
| dc.date.none.fl_str_mv |
2021-01-04 |
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info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
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publishedVersion |
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http://hdl.handle.net/11336/135516 Yamada, Yuki; Ćepulić, Dominik Borna; Coll Martín, Tao; Debove, Stéphane; Gautreau, Guillaume; et al.; COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak; Nature; Scientific Data; 8; 1; 4-1-2021; 1-23 2052-4463 CONICET Digital CONICET |
| url |
http://hdl.handle.net/11336/135516 |
| identifier_str_mv |
Yamada, Yuki; Ćepulić, Dominik Borna; Coll Martín, Tao; Debove, Stéphane; Gautreau, Guillaume; et al.; COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak; Nature; Scientific Data; 8; 1; 4-1-2021; 1-23 2052-4463 CONICET Digital CONICET |
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eng |
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eng |
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info:eu-repo/semantics/altIdentifier/doi/10.1038/s41597-020-00784-9 info:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41597-020-00784-9 |
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Nature |
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Nature |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
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dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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