doherty_2023_burnout
6,846 responses from 432 respondents to 16 items.
About this table
| Description | 16-item burnout scale, 1-7, Irish consultant doctors. 432 respondents x 16 items = 6846 responses. |
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| Reference | Doherty, A. (2023). National burnout survey: BICDIS [Data set]. Mendeley Data. https://doi.org/10.17632/95cmh2ftwk |
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| Licence | CC BY 4.0 |
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| Source data | https://data.mendeley.com/datasets/95cmh2ftwk |
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Size and shape
| Responses | 6,846 |
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| Respondents | 432 |
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| Items | 16 |
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| Response categories | 7 |
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| Responses per respondent | 15.847 |
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| Responses per item | 427.875 |
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| Density | 0.990 |
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| Longitudinal | FALSE |
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Classification
| sample | Workplace |
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| measurement tool | Survey/questionnaire |
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| item format | Likert Scale/selected response |
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| primary language(s) | eng |
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Columns
cov_age_bandcov_alcohol_drug_treatmentcov_disciplinary_historycov_employer_typecov_exercisecov_face_to_face_sessionscov_gendercov_job_satisfactioncov_lawsuit_historycov_mental_health_problemcov_oncall_frequencycov_specialitycov_weekly_hoursiditemresp
Get the data
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("doherty_2023_burnout")
# Python
pip install irw
import irw
df = irw.fetch("doherty_2023_burnout")
Version and provenance
| IRW version | v393 |
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| Redivis dataset | item_response_warehouse_4 v7.0 |
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| Redivis dataset DOI | 10.57761/cpj5-vm97 |
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| Manifest pin for this IRW version | v7.0 |
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| Metadata source | irw_meta v23.0 |
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