Y Yamada
COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak
Yamada, Y; Ćepulić, D-B; Coll-Martín, T; Debove, S; Gautreau, G; Han, H; Rasmussen, J; Tran, TP; Travaglino, GA; Lieberoth, A; Blackburn, AM; Boullu, L; Bujić, M; Byrne, G; Caniëls, MCJ; Flis, I; Kowal, M; Rachev, NR; Reynoso-Alcántara, V; Zerhouni, O; Ahmed, O; Amin, R; Aquino, S; Areias, JC; Aruta, JJBR; Bamwesigye, D; Bavolar, J; Bender, AR; Bhandari, P; Bircan, T; Cakal, H; Capelos, T; Čeněk, J; Ch’ng, B; Chen, F-Y; Chrona, S; Contreras-Ibáñez, CC; Correa, PS; Cristofori, I; Cyrus-Lai, W; Delgado-Garcia, G; Deschrijver, E; Díaz, C; Dilekler, İ; Dranseika, V; Dubrov, D; Eichel, K; Ermagan-Caglar, E; Gelpí, R; González, RF; Griffin, A; Hakim, MA; Hanusz, K; Ho, YW; Hristova, D; Hubena, B; Ihaya, K; Ikizer, G; Islam, MN; Jeftic, A; Jha, S; Juárez, FP-G; Kacmar, P; Kalinova, K; Kavanagh, PS; Kosa, M; Koszałkowska, K; Kumaga, R; Lacko, D; Lee, Y; Lentoor, AG; De Leon, GA; Lin, S-Y; Lins, S; López, CRC; Lys, AE; Mahlungulu, S; Makaveeva, T; Mamede, S; Mari, S; Marot, TA; Martinez, L; Mes...
Authors
D-B Ćepulić
T Coll-Martín
S Debove
G Gautreau
H Han
J Rasmussen
TP Tran
GA Travaglino
A Lieberoth
AM Blackburn
L Boullu
M Bujić
G Byrne
MCJ Caniëls
I Flis
M Kowal
NR Rachev
V Reynoso-Alcántara
O Zerhouni
O Ahmed
R Amin
S Aquino
JC Areias
JJBR Aruta
D Bamwesigye
J Bavolar
AR Bender
P Bhandari
T Bircan
H Cakal
T Capelos
J Čeněk
B Ch’ng
F-Y Chen
S Chrona
CC Contreras-Ibáñez
PS Correa
I Cristofori
W Cyrus-Lai
G Delgado-Garcia
E Deschrijver
C Díaz
İ Dilekler
V Dranseika
D Dubrov
K Eichel
E Ermagan-Caglar
R Gelpí
RF González
A Griffin
MA Hakim
K Hanusz
YW Ho
D Hristova
B Hubena
K Ihaya
G Ikizer
MN Islam
A Jeftic
S Jha
FP-G Juárez
P Kacmar
K Kalinova
PS Kavanagh
M Kosa
K Koszałkowska
R Kumaga
D Lacko
Y Lee
AG Lentoor
GA De Leon
S-Y Lin
S Lins
CRC López
AE Lys
S Mahlungulu
T Makaveeva
S Mamede
S Mari
TA Marot
L Martinez
D Meshi
DJ Mola
S Morales-Izquierdo
A Musliu
PA Naidu
A Najmussaqib
JC Natividade
S Nebel
J Nezkusilova
I Nikolova
M Ninaus
V Noreika
MV Ortiz
DH Ozery
D Pankowski
T Pennato
M Pírko
L Pummerer
C Reyna
E Romano
H Sahin
AM Sanli
G Sayılan
A Scarpaci
C Sechi
M Shani
A Shata
P Sikka
N Sinha
S Stöckli
A Studzinska
E Sungailaite
Z Szebeni
B Tag
M Taranu
F Tisocco
J Tuominen
F Turk
MK Uddin
E Uzelac
SK Vestergren
R Vilar
AH-E Wang
JN West
CKS Wu
T Yaneva
Y-Y Yeh
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.
Citation
Yamada, Y., Ćepulić, D., Coll-Martín, T., Debove, S., Gautreau, G., Han, H., …Yeh, Y. (2021). COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak. Scientific Data, 8(1), 3. https://doi.org/10.1038/s41597-020-00784-9
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 2, 2020 |
Publication Date | Jan 4, 2021 |
Deposit Date | Jan 5, 2021 |
Publicly Available Date | Jan 5, 2021 |
Journal | Scientific Data |
Publisher | Nature Publishing Group |
Volume | 8 |
Issue | 1 |
Pages | 3 |
DOI | https://doi.org/10.1038/s41597-020-00784-9 |
Publisher URL | https://doi.org/10.1038/s41597-020-00784-9 |
Related Public URLs | http://www.nature.com/sdata/ |
Additional Information | Additional Information : ** From Springer Nature via Jisc Publications Router ** Licence for this article: http://creativecommons.org/licenses/by/4.0/ **Journal IDs: eissn 2052-4463 **Article IDs: publisher-id: s41597-020-00784-9; manuscript: 784 **History: collection 12-2021; published 04-01-2021; online 04-01-2021; registration 08-12-2020; accepted 02-10-2020; submitted 05-06-2020 Funders : MEXT | Japan Society for the Promotion of Science (JSPS);Consejo Nacional de Ciencia y Tecnología (CONCYT);Research Foundation Flanders (FWO) postdoctoral fellowship;The HSE University Basic Research Program;JSPS KAKENHI Projects : JP17H00875;JP18K12015;JP20H04581;unspecified Grant Number: JP17H00875 Grant Number: JP18K12015 Grant Number: JP20H04581 Grant Number: JP20K14222 |
Files
41597_2020_784_MOESM1_ESM.pdf
(60 Kb)
PDF
Licence
http://creativecommons.org/licenses/by/4.0/
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
41597_2020_Article_784.pdf
(1.3 Mb)
PDF
Licence
http://creativecommons.org/licenses/by/4.0/
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
Downloadable Citations
About USIR
Administrator e-mail: library-research@salford.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search