curiosity_stone_2022_var

3,146 responses from 481 respondents to 8 items.

One of 3 tables from the same source; this one is the var table. The others are listed under Related tables.

About this table

DescriptionCurious to eat insects? Curiosity as a Key Predictor of Willingness to try novel food
ReferenceStone, H. J., FitzGibbon, L., Millan, E., & Murayama, K. (2021, April 28). Curious to Eat Insects? Curiosity as a Key Predictor of Willingness to Try Novel Food. https://doi.org/10.17605/OSF.IO/5F9SP
DOI10.1016/j.appet.2021.105790
LicenceCC BY 4.0
Source datahttps://osf.io/5f9sp/overview

Size and shape

Responses3,146
Respondents481
Items8
Response categories5
Responses per respondent6.541
Responses per item393.250
Density0.818
LongitudinalTRUE

Classification

age rangeAdult (18+)
sampleInternet-based
construct typePersonality
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng
construct nameVariety Seeking

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, curiosity_stone_2022.py. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.

ColumnWhat it isSource column
IRW standard columns
idIRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task).subject
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
waveIRW standard Longitudinal wave indicator.made in the build script
Respondent covariates
cov_ageCovariate age
cov_educationCovariate education
cov_ethnicityCovariate ethnicity
cov_nationalityCovariate nationality
cov_residencyCovariate residency
cov_sexCovariate sex

What item codes and covariate values stand for is in the codebook released with the source data.

Get the data

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

Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("curiosity_stone_2022_var")
# Python
pip install irw

import irw
df = irw.fetch("curiosity_stone_2022_var")

How to cite

@article{Stone_2022, title={Curious to eat insects? Curiosity as a Key Predictor of Willingness to try novel food}, volume={168}, ISSN={0195-6663}, url={http://dx.doi.org/10.1016/j.appet.2021.105790}, DOI={10.1016/j.appet.2021.105790}, journal={Appetite}, publisher={Elsevier BV}, author={Stone, Hannah and FitzGibbon, Lily and Millan, Elena and Murayama, Kou}, year={2022}, month=jan, pages={105790} }

Version and provenance

IRW versionv566
Redivis datasetitem_response_warehouse_2 v33.0
Redivis dataset DOI10.57761/6m04-m698
Manifest pin for this IRW versionv33.0
Metadata sourceirw_meta v43.0