jo_2023_sno

1,035 responses from 345 respondents to 3 items.

One of 6 tables from the same source; this one is the sno table. The others are listed under Related tables.

About this table

Description3-item Subjective Norms scale (7-point Likert, 1-7), from a COVID-19 survey of N=345 Korean and Vietnamese university students.
ReferenceJo H, Baek E (2023) Impacts of social isolation and risk perception on social networking intensity among university students during covid-19. PLoS ONE.
DOI10.1371/journal.pone.0283997
LicenceCC BY 4.0
Source datahttps://doi.org/10.1371/journal.pone.0283997.s003

Size and shape

Responses1,035
Respondents345
Items3
Response categories7
Responses per respondent3
Responses per item345
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleEducational
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)kor, vie

Item text

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

InstrumentSubjective Norms (3-item scale adapted from Ajzen 1991, Theory of Planned Behavior)
Mean words per item17
Mean characters per item104
Mean characters per response2
Flesch-Kincaid grade level10.878

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_gender_maleCovariate not traced
cov_nationalityCovariate 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("jo_2023_sno")
# Python
pip install irw

import irw
df = irw.fetch("jo_2023_sno")

How to cite

@article{Jo_2023, title={Impacts of social isolation and risk perception on social networking intensity among university students during covid-19}, volume={18}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0283997}, DOI={10.1371/journal.pone.0283997}, number={4}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Jo, Hyeon and Baek, Eun-Mi}, editor={Al-Adwan, Ahmad Samed}, year={2023}, month=Apr, pages={e0283997} }

Version and provenance

IRW versionv557
Redivis datasetitem_response_warehouse_4 v13.0
Redivis dataset DOI10.57761/w8zx-td92
Manifest pin for this IRW versionv13.0
Metadata sourceirw_meta v40.0