alsyouf_2024_effort_expectancy

2,360 responses from 472 respondents to 5 items.

One of 12 tables from the same source; this one measures Effort expectancy (UTAUT). The others are listed under Related tables.

About this table

DescriptionEffort expectancy of EHR systems (5 items, UTAUT-based), 1-5 Likert, N=472 nurses (Jordan/Saudi Arabia EHR continuance-intention study).
ReferenceAlsyouf A, Alsubahi N, Alali H, Lutfi A, Al-Mugheed KA, Alrawad M, Almaiah MA, Anshasi RJ, Alhazmi FN, Sawhney D (2024). Nurses' continuance intention to use electronic health record systems: The antecedent role of personality and organisation support. PLOS ONE 19(10):e0300657.
DOI10.1371/journal.pone.0300657
LicenceCC BY 4.0
Source datahttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0300657

Size and shape

Responses2,360
Respondents472
Items5
Response categories5
Responses per respondent5
Responses per item472
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleTargeted/specific
construct typeOpinion/attitude
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)ara
construct nameEffort expectancy (UTAUT)

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, alsyouf_2024_ehr.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).ID
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
Respondent covariates
cov_ageCovariate age
cov_departmentCovariate dep.Name
cov_educationCovariate edu
cov_genderCovariate gender
cov_hospitalCovariate hos.Name
cov_professional_experienceCovariate prof.exp

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("alsyouf_2024_effort_expectancy")
# Python
pip install irw

import irw
df = irw.fetch("alsyouf_2024_effort_expectancy")

How to cite

@article{Alsyouf_2024, title={Nurses’ continuance intention to use electronic health record systems: The antecedent role of personality and organisation support}, volume={19}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0300657}, DOI={10.1371/journal.pone.0300657}, number={10}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Alsyouf, Adi and Alsubahi, Nizar and Alali, Haitham and Lutfi, Abdalwali and Al-Mugheed, Khalid Anwer and Alrawad, Mahmaod and Almaiah, Mohammed Amin and Anshasi, Rami J. and Alhazmi, Fahad N. and Sawhney, Disha}, editor={De Rosis, Sabina}, year={2024}, month=Oct, pages={e0300657} }

Version and provenance

IRW versionv557
Redivis datasetitem_response_warehouse_3 v13.0
Redivis dataset DOI10.57761/gpg7-sg87
Manifest pin for this IRW versionv13.0
Metadata sourceirw_meta v40.0