hendrikx_2022_autonomy

916 responses from 229 respondents to 4 items.

One of 4 tables from the same source; this one measures Job autonomy (4 items). The others are listed under Related tables.

About this table

Description4 job-autonomy items (1-5); N = 229 Dutch employees; cov_gender, cov_age, cov_sector, cov_contract_hours, cov_education, cov_telework, cov_hours_outside_worktime.
ReferenceHendrikx, K. (2022). Availability norms and burnout symptoms: The role of autonomy and telepressure [data]. DANS Data Station SSH. https://doi.org/10.17026/dans-z9b-7fej
LicenceCC BY 4.0
Source datahttps://doi.org/10.17026/dans-z9b-7fej

Size and shape

Responses916
Respondents229
Items4
Response categories5
Responses per respondent4
Responses per item229
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleWorkplace
construct typeOpinion/attitude
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)dut
construct nameJob autonomy (4 items)

Codebook

This codebook is reconstructed by the IRW from the IRW data standard. 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).not traced
itemIRW standard Item identifier.not traced
respIRW standard Response value.not traced
Respondent covariates
cov_ageCovariate not traced
cov_contract_hoursCovariate not traced
cov_educationCovariate not traced
cov_genderCovariate not traced
cov_hours_outside_worktimeCovariate not traced
cov_sectorCovariate not traced
cov_teleworkCovariate not traced

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("hendrikx_2022_autonomy")
# Python
pip install irw

import irw
df = irw.fetch("hendrikx_2022_autonomy")

How to cite

@misc{https://doi.org/10.17026/dans-z9b-7fej,
  doi = {10.17026/DANS-Z9B-7FEJ},
  url = {https://ssh.datastations.nl/citation?persistentId=doi:10.17026/DANS-Z9B-7FEJ},
  author = {{K Hendrikx}},
  keywords = {Social Sciences, Social norms, Availability norms, ICT use, Job autonomy, Telepressure, Burnout Symptoms},
  language = {nl},
  title = {Availability norms and burnout symptoms: The role of autonomy and telepressure},
  publisher = {DANS Data Station Social Sciences and Humanities},
  year = {2020}
}

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