ghanbari_2016_helma_appraise

2,910 responses from 582 respondents to 5 items.

About this table

DescriptionHELMA appraisal subscale (5 items 1-5 Likert) N=582 Iranian adolescents
ReferenceGhanbari S et al. 2016 PLOS ONE
DOI10.1371/journal.pone.0149202
LicenceCC BY 4.0
Source datahttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0149202

Size and shape

Responses2,910
Respondents582
Items5
Response categories5
Responses per respondent5
Responses per item582
Density1
LongitudinalFALSE

Classification

age rangeMixed
child age (for child-focused studies)Adolescent (12-18y)
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.

InstrumentHealth Literacy Measure for Adolescents (HELMA), appraisal subscale
Mean words per item11.200
Mean characters per item70.200
Mean characters per response7.400
Flesch-Kincaid grade level9.217

Columns

cov_agecov_classcov_father_educationcov_father_jobcov_fieldcov_first_health_info_sourcecov_health_statuscov_interest_in_healthcov_internet_holidaycov_internet_schooldaycov_magazine_usecov_mother_educationcov_mother_jobcov_radio_usecov_regioncov_sexcov_tv_holidaycov_tv_schooldayiditemresp

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("ghanbari_2016_helma_appraise")
# Python
pip install irw

import irw
df = irw.fetch("ghanbari_2016_helma_appraise")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse_3 v7.0
Redivis dataset DOI10.57761/pqqn-pm43
Manifest pin for this IRW versionv7.0
Metadata sourceirw_meta v23.0