buczel_2022_inoculation_belief

822 responses from 137 respondents to 6 items.

About this table

Description	6-item misinformation/retraction belief-rating scale (1-11), from an inoculation-technique experiment on the continued influence effect
Reference	Buczel KA, Szyszka PD, Siwiak A, Szpitalak M, Polczyk R (2022) Vaccination against misinformation: The inoculation technique reduces the continued influence effect. PLoS ONE 17(4): e0267463.
DOI	10.1371/journal.pone.0267463
Licence	CC BY 4.0
Source data	https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0267463.s001&type=supplementary

Size and shape

Responses	822
Respondents	137
Items	6
Response categories	11
Responses per respondent	6
Responses per item	137
Density	1
Longitudinal	FALSE

Classification

age range	Adult (18+)
sample	Educational, Internet-based
measurement tool	Survey/questionnaire
item format	Likert Scale/selected response
primary language(s)	pol

Item text

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

Instrument	Belief in misinformation and belief in retraction rating scales (continued influence effect scenarios)
Mean words per item	56
Mean characters per item	415.333
Mean characters per response	1.091
Flesch-Kincaid grade level	16.184

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, buczel_2022_inoculation_belief.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.

Column	What it is	Source column
IRW standard columns
`id`	IRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task).	`Subject`
`item`	IRW standard Item identifier.	made in the build script
`resp`	IRW standard Response value.	made in the build script
`treat`	IRW standard Treatment group assignment in experimental studies.	made in the build script
Respondent covariates
`cov_age`	Covariate	`Age`
`cov_education`	Covariate	`Education`
`cov_gender`	Covariate	`Gender`

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

Get the data

Download CSVno account needed Browse on Redivisexplore and query Croissant 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("buczel_2022_inoculation_belief")

# Python
pip install irw

import irw
df = irw.fetch("buczel_2022_inoculation_belief")

How to cite

@article{Buczel_2022, title={Vaccination against misinformation: The inoculation technique reduces the continued influence effect}, volume={17}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0267463}, DOI={10.1371/journal.pone.0267463}, number={4}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Buczel, Klara Austeja and Szyszka, Paulina D. and Siwiak, Adam and Szpitalak, Malwina and Polczyk, Romuald}, editor={Garrido, Margarida Vaz}, year={2022}, month=Apr, pages={e0267463} }

Version and provenance

IRW version	v566
Redivis dataset	item_response_warehouse_4 v13.0
Redivis dataset DOI	10.57761/w8zx-td92
Manifest pin for this IRW version	v13.0
Metadata source	irw_meta v43.0