doustmohammadian_2017_fnlit

21,634 responses from 373 respondents to 58 items.

About this table

Description58-item Food and Nutrition Literacy (FNLIT) scale for elementary school children in Iran, spanning 10 sub-domains
ReferenceDoustmohammadian A, Omidvar N, Keshavarz-Mohammadi N, Abdollahi M, Amini M, Eini-Zinab H (2017) Developing and validating a scale to measure Food and Nutrition Literacy (FNLIT) in elementary school children in Iran. PLoS ONE 12(6): e0179196.
DOI10.1371/journal.pone.0179196
LicenceCC BY 4.0
Source datahttps://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0179196.s007

Size and shape

Responses21,634
Respondents373
Items58
Response categories5
Responses per respondent58
Responses per item373
Density1
LongitudinalFALSE

Classification

sampleEducational
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)per

Item text

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

InstrumentFood and Nutrition Literacy (FNLIT) scale for elementary school children (58-item validation form)
Mean words per item10.345
Mean characters per item60.328
Mean characters per response5.762
Flesch-Kincaid grade level7.530

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, doustmohammadian_2017_fnlit.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).made in the build script
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script

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("doustmohammadian_2017_fnlit")
# Python
pip install irw

import irw
df = irw.fetch("doustmohammadian_2017_fnlit")

How to cite

@article{Doustmohammadian_2017, title={Developing and validating a scale to measure Food and Nutrition Literacy (FNLIT) in elementary school children in Iran}, volume={12}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0179196}, DOI={10.1371/journal.pone.0179196}, number={6}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Doustmohammadian, Aazam and Omidvar, Nasrin and Keshavarz-Mohammadi, Nastaran and Abdollahi, Morteza and Amini, Maryam and Eini-Zinab, Hassan}, editor={Cipresso, Pietro}, year={2017}, month=June, pages={e0179196} }

Version and provenance

IRW versionv549
Redivis datasetitem_response_warehouse_3 v13.0
Redivis dataset DOI10.57761/gpg7-sg87
Manifest pin for this IRW versionv13.0
Metadata sourceirw_meta v39.0