gimenez_espert_2026_aco

2,298 responses from 193 respondents to 12 items.

One of 3 tables from the same source; this one measures Attitudes Towards Communication, reduced (ACO-R). The others are listed under Related tables.

About this table

DescriptionAttitudes Towards Communication, reduced version (ACO-R), 12 items, 1-5, 193 direct-care nurses from four public hospitals in the Valencian Community, Spain; no covariates.
ReferenceGiménez-Espert, M. d. C., Sanchis-Giménez, L., Prado-Gascó, V. J., & Ibrahim, M. I. (2026). Words on fire: Nurses' communication attitudes in the burnout equation. PLOS ONE, 21(9), e0358785.
DOI10.1371/journal.pone.0358785
LicenceCC BY 4.0
Source datahttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0358785

Notes

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Size and shape

Responses2,298
Respondents193
Items12
Response categories5
Responses per respondent11.907
Responses per item191.500
Density0.992
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleWorkplace
construct typeOpinion/attitude
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)spa
construct nameAttitudes Towards Communication, reduced (ACO-R)

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, gimenez_espert_2026_nurses.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).codigo
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("gimenez_espert_2026_aco")
# Python
pip install irw

import irw
df = irw.fetch("gimenez_espert_2026_aco")

How to cite

@article{Gim_nez_Espert_2026, title={Words on fire: Nurses’ communication attitudes in the burnout equation}, volume={21}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0358785}, DOI={10.1371/journal.pone.0358785}, number={9}, journal={PLOS One}, publisher={Public Library of Science (PLoS)}, author={Giménez-Espert, María del Carmen and Sanchis-Giménez, Lucía and Prado-Gascó, Vicente Javier}, editor={Ibrahim, Mohd Ismail}, year={2026}, month=Sept, pages={e0358785} }

Version and provenance

IRW versionv584
Redivis datasetitem_response_warehouse_5 v8.5
Redivis dataset DOI10.57761/41xy-5k56
Manifest pin for this IRW versionv8.5
Metadata sourceirw_meta v44.0