hirwa_2024_antibiotic_attitudes

3,969 responses from 441 respondents to 9 items.

About this table

DescriptionAttitudes toward antibiotic use and antimicrobial resistance among cattle farmers in Rwanda; N=441, 9 items, 0-2 scale
ReferenceHirwa, E.; Mujawamariya, G.; Shimelash, N.; Shyaka, A. (2024). Evaluation of cattle farmers' knowledge, attitudes, and practices regarding antimicrobial use and antimicrobial resistance in Rwanda. PLOS ONE. DOI: 10.1371/journal.pone.0300742
DOI10.1371/journal.pone.0300742
LicenceCC BY 4.0
Source datahttps://plos.figshare.com/articles/dataset/Attitude_related_answers_/24448688

Size and shape

Responses3,969
Respondents441
Items9
Response categories3
Responses per respondent9
Responses per item441
Density1
LongitudinalFALSE

Classification

sampleWorkplace
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)kin

Item text

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

InstrumentAttitudes towards antimicrobial use and antimicrobial resistance (Hirwa et al. 2024 cattle-farmer KAP questionnaire, part five)
Mean words per item1
Mean characters per item2
Mean characters per response6.667
Flesch-Kincaid grade level-3.400

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, hirwa_2024_antibiotic_attitudes.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).SN
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("hirwa_2024_antibiotic_attitudes")
# Python
pip install irw

import irw
df = irw.fetch("hirwa_2024_antibiotic_attitudes")

How to cite

@article{Hirwa_2024, title={Evaluation of cattle farmers’ knowledge, attitudes, and practices regarding antimicrobial use and antimicrobial resistance in Rwanda}, volume={19}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0300742}, DOI={10.1371/journal.pone.0300742}, number={4}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Hirwa, Elise M. and Mujawamariya, Gisele and Shimelash, Natnael and Shyaka, Anselme}, editor={Alegría-Morán, Raúl Alejandro}, year={2024}, month=Apr, pages={e0300742} }

Version and provenance

IRW versionv549
Redivis datasetitem_response_warehouse_2 v33.0
Redivis dataset DOI10.57761/6m04-m698
Manifest pin for this IRW versionv33.0
Metadata sourceirw_meta v39.0