assessment_time_fournier_2025_bscs

5,174 responses from 398 respondents to 13 items.

One of 5 tables from the same source; this one measures Assessment Time - Self-Control. The others are listed under Related tables.

About this table

DescriptionBrief Self-Control Scale
ReferenceFournier, L., Heeren, A., Baggio, S., Clark, L., Verdejo-Garcia, A., Perales, J., & Billieux, J. (2025, August 20). Data. https://doi.org/10.17605/OSF.IO/6V5QB
LicenceCC BY 4.0
Source datahttps://osf.io/6v5qb/files/osfstorage

Size and shape

Responses5,174
Respondents398
Items13
Response categories5
Responses per respondent13
Responses per item398
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleInternet-based
construct typeBehavioral, Cognitive/educational
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng
construct nameAssessment Time - Self-Control

Item text

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

InstrumentBrief Self-Control Scale
Mean words per item7.923
Mean characters per item43.385
Mean characters per response8.200
Flesch-Kincaid grade level4.065

Codebook

This codebook is reconstructed by the IRW from the IRW data standard. 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).not traced
itemIRW standard Item identifier.not traced
respIRW standard Response value.not traced
Respondent covariates
cov_ageCovariate not traced
cov_countryCovariate not traced
cov_genderCovariate not traced

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("assessment_time_fournier_2025_bscs")
# Python
pip install irw

import irw
df = irw.fetch("assessment_time_fournier_2025_bscs")

How to cite

@article{https://doi.org/10.17605/osf.io/6v5qb,
  doi = {10.17605/OSF.IO/6V5QB},
  url = {https://osf.io/6v5qb/},
  author = {Verdejo-Garcia, Antonio and Perales, José C. and Fournier, Loïs and Billieux, Joel and Heeren, Alexandre and Clark, Luke and Baggio, Stéphanie},
  keywords = {UPPS-P Impulsive Behavior Scale, UPPS-P-20-R, network modeling, psychometrics, structural equation modeling},
  title = {Data},
  publisher = {OSF},
  year = {2023},
  copyright = {Creative Commons Attribution 4.0 International}
}

Version and provenance

IRW versionv557
Redivis datasetitem_response_warehouse_2 v33.0
Redivis dataset DOI10.57761/6m04-m698
Manifest pin for this IRW versionv33.0
Metadata sourceirw_meta v40.0