habibi_2026_burnout

15,915 responses from 1,065 respondents to 15 items.

One of 6 tables from the same source; this one measures Teacher burnout (MBI-ES adaptation). The others are listed under Related tables.

About this table

DescriptionTeacher burnout, 15 items adapted from the MBI-Educators Survey (emotional exhaustion 5, depersonalisation 3, reduced personal accomplishment 7, negatively worded), 1-5; N = 1,065; same covariates.
ReferenceHabibi, A. (2026). Determinants affecting teacher burnout and performance: Asian context. figshare. https://doi.org/10.6084/m9.figshare.31672783
LicenceCC BY 4.0
Source datahttps://figshare.com/articles/dataset/_b_Determinants_affecting_teacher_burnout_and_performance_Asian_context_b_/31672783

Size and shape

Responses15,915
Respondents1,065
Items15
Response categories5
Responses per respondent14.944
Responses per item1,061
Density0.996
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleEducational, Workplace
construct typeAffective/mental health
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)ind
construct nameTeacher burnout (MBI-ES adaptation)

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, habibi_2026_teacher_burnout.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).made in the build script
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
Respondent covariates
cov_experienceCovariate made in the build script
cov_genderCovariate made in the build script
cov_school_areaCovariate 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("habibi_2026_burnout")
# Python
pip install irw

import irw
df = irw.fetch("habibi_2026_burnout")

How to cite

@misc{https://doi.org/10.6084/m9.figshare.31672783,
  doi = {10.6084/M9.FIGSHARE.31672783},
  url = {https://figshare.com/articles/dataset/_b_Determinants_affecting_teacher_burnout_and_performance_Asian_context_b_/31672783},
  author = {Habibi, Akhmad},
  keywords = {Educational psychology},
  title = {<b>Determinants affecting teacher burnout and performance: Asian context</b>},
  publisher = {figshare},
  year = {2026},
  copyright = {Creative Commons Attribution 4.0 International}
}

Version and provenance

IRW versionv584
Redivis datasetitem_response_warehouse_7 v1.1
Redivis dataset DOI10.57761/7pd3-sh31
Manifest pin for this IRW versionv1.0
Metadata sourceirw_meta v44.0