ecps_sahm_2024_distrust

130,849 responses from 13,137 respondents to 13 items.

About this table

DescriptionCOVIDiSTRESS Global Survey Round II - Anti-expert sentiment, COVID-19 misperceptions and conspiratorial thinking
ReferenceBlackburn, A. M., Vestergren, S., et al. (2022). COVIDiSTRESS diverse dataset on psychological and behavioural outcomes one year into the COVID-19 pandemic. Scientific Data, 9, 331.
DOI10.1038/s41597-022-01383-6
LicenceCC BY 4.0
Source datahttps://osf.io/36tsd/

Size and shape

Responses130,849
Respondents13,137
Items13
Response categories7
Responses per respondent9.960
Responses per item10065.308
Density0.766
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleClinical, Targeted/specific
construct typeAffective/mental health, Cognitive/educational
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)ger
construct nameGerman Version of the Emotion Regulation Questionnaire-Short Form - Distrust Subscale

Item text

This table has item text in the IRW: the wording administered to respondents, not just the response codes.

InstrumentCOVIDiSTRESS Global Survey Round II: Anti-expert sentiment
Mean words per item11.846
Mean characters per item64.308
Mean characters per response11.714
Flesch-Kincaid grade level5.877

Columns

cov_agecov_covid_selfcov_educationcov_gendercov_live_alonecov_occupationcov_residing_countryiditemresp

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python:

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("ecps_sahm_2024_distrust")
# Python
pip install irw

import irw
df = irw.fetch("ecps_sahm_2024_distrust")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse v53.0
Redivis dataset DOI10.57761/4g08-xt41
Manifest pin for this IRW versionv53.0
Metadata sourceirw_meta v23.0