fadhliah_2022_disaster_media_trust

600 responses from 75 respondents to 8 items.

About this table

DescriptionRatings of 8 named disaster-information channels (TV/Internet/WA-SMS/Radio/Mosque-Church/Surau/community leader/word of mouth), N=75
ReferenceFadhliah, et al. (2022). Comparison of disaster information from various media in strengthening ecological communication during & after natural disasters. PLOS ONE.
DOI10.1371/journal.pone.0264089
LicenceCC BY 4.0
Source datahttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0264089

Size and shape

Responses600
Respondents75
Items8
Response categories4
Responses per respondent8
Responses per item75
Density1
LongitudinalFALSE

Classification

sampleProgram-based
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)ind

Columns

iditemresp

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("fadhliah_2022_disaster_media_trust")
# Python
pip install irw

import irw
df = irw.fetch("fadhliah_2022_disaster_media_trust")

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