threat_isler_2024_exp3_cog_panas

39,094 responses from 1,777 respondents to 22 items.

About this table

DescriptionA large-scale validation study comparing health threat and relaxation manipulations to a control condition (N=1777)
ReferenceIsler, O., Yilmaz, O., Maule, A. J., & Gächter, S. (2024). How to activate threat perceptions in behavior research: A simple technique for inducing health and resource scarcity threats. Behavior Research Methods, 56(8), 8379-8395.
DOI10.3758/s13428-024-02481-6
LicenceCC BY 4.0
Source datahttps://osf.io/grafm/

Size and shape

Responses39,094
Respondents1,777
Items22
Response categories5
Responses per respondent22
Responses per item1,777
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleInternet-based
construct typeAffective/mental health
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng
construct namePositive and Negative Afect Schedule (PANAS)

Item text

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

InstrumentA large-scale validation study comparing health threat and relaxation manipulations to a control condition (N=1777)
Mean words per item1
Mean characters per item7.500
Mean characters per response14
Flesch-Kincaid grade level56.274

Columns

iditemresptreat

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("threat_isler_2024_exp3_cog_panas")
# Python
pip install irw

import irw
df = irw.fetch("threat_isler_2024_exp3_cog_panas")

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