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 - Lentoor, Antonio G.
N1 - 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
JO - Scientific data
JF - Scientific data
IS - 1
M1 - 3
ER -