leon_rubio_2025_cdpe_coping

7,108 responses from 648 respondents to 11 items.

One of 5 tables from the same source; this one measures Cuestionario de Desgaste Profesional de Enfermería (CDPE) - coping. The others are listed under Related tables.

About this table

DescriptionNursing Burnout Questionnaire (CDPE), coping block: social support seeking, direct coping, avoidance; 11 items, 1-4 (strongly disagree-strongly agree), 648 Spanish nurses; itemcov_subscale; covariates cov_sex, cov_age, cov_relationship, cov_n_children, cov_education, cov_nursing_specialty, cov_which_specialty, cov_other_training, cov_years_experience, cov_job_category, cov_years_in_category, cov_employment_status, cov_service, cov_shift, cov_patients_per_day, cov_hours_per_week, cov_pct_time_with_patients (codes as in the deposit codebook).
ReferenceLeon-Rubio, J. M., & Leon-Perez, J. M. (2025). Professional burnout in nursing: Organizational background, dispositional and mediating factors, and consequences [Data set]. Zenodo. https://doi.org/10.5281/zenodo.17899509
LicenceCC BY-NC 4.0
Source datahttps://zenodo.org/records/17899509

Size and shape

Responses7,108
Respondents648
Items11
Response categories4
Responses per respondent10.969
Responses per item646.182
Density0.997
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleWorkplace
construct typeBehavioral
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)spa
construct nameCuestionario de Desgaste Profesional de Enfermería (CDPE) - coping

Item text

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

InstrumentCuestionario de Desgaste Profesional de Enfermería (CDPE)
Mean words per item11.455
Mean characters per item59.818
Mean characters per response17
Flesch-Kincaid grade level6.671

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, leon_rubio_2025_cdpe.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 edad
cov_educationCovariate estudios
cov_employment_statusCovariate situació
cov_hours_per_weekCovariate horas
cov_job_categoryCovariate categori
cov_n_childrenCovariate hijos
cov_nursing_specialtyCovariate especial
cov_other_trainingCovariate otraform
cov_patients_per_dayCovariate pacientes
cov_pct_time_with_patientsCovariate porcenta
cov_relationshipCovariate relación
cov_serviceCovariate servicio
cov_sexCovariate sexo
cov_shiftCovariate horario
cov_which_specialtyCovariate cual
cov_years_experienceCovariate exprofes
cov_years_in_categoryCovariate expcateg
Other columns
itemcov_subscaleNot documented Covariates invariant to measurement probes (item-level attributes).made in the build script

What item codes and covariate values stand for is in the source’s codebook, content.

Get the data

Licence: CC BY-NC 4.0 — non-commercial use only.

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("leon_rubio_2025_cdpe_coping")
# Python
pip install irw

import irw
df = irw.fetch("leon_rubio_2025_cdpe_coping")

How to cite

@misc{https://doi.org/10.5281/zenodo.17899509,
  doi = {10.5281/ZENODO.17899509},
  url = {https://zenodo.org/doi/10.5281/zenodo.17899509},
  author = {Leon-Rubio, Jose Maria and Leon-Perez, Jose Maria},
  keywords = {Burnout, Professional, Nursing, FOS: Health sciences, Occupational Stress, Psychosocial Factors, Hardiness, Coping Skills, Emotional Exhaustion, Professional Well-being, Healthcare Workers, Occupational Health},
  language = {es},
  title = {Professional burnout in nursing: Organizational background, dispositional and mediating factors, and consequences},
  publisher = {Zenodo},
  year = {2025},
  copyright = {Creative Commons Attribution Non Commercial 4.0 International}
}

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