25,636 responses from 249 respondents to 37 items.
| Description | Burnout and depression in an RCT |
|---|---|
| Reference | Bateman, M. E., Hammer, R., Byrne, A., Ravindran, N., Chiurco, J., Lasky, S., ... & Denson, J. L. (2020). Death Cafés for prevention of burnout in intensive care unit employees: study protocol for a randomized controlled trial (STOPTHEBURN). Trials, 21, 1-9. Bateman, Marjorie, 2023, "STOPTHEBURN Randomized Controlled Trial Data", https://doi.org/10.7910/DVN/DIU6BU, Harvard Dataverse, V1 |
| Licence | CC0 1.0 |
| Source data | https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/DIU6BU |
| Responses | 25,636 |
|---|---|
| Respondents | 249 |
| Items | 37 |
| Response categories | 7 |
| Responses per respondent | 102.956 |
| Responses per item | 692.865 |
| Density | 2.783 |
| Longitudinal | TRUE |
| age range | Adult (18+) |
|---|---|
| sample | Clinical, Targeted/specific |
| construct type | Affective/mental health |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | Maslach Burnout Inventory (MBI) Score |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Maslach Burnout Inventory -- Human Services Survey (MBI-HSS; Maslach & Jackson 1981) |
|---|---|
| Mean words per item | 3.280 |
| Mean characters per item | 16.505 |
| Mean characters per response | 18.636 |
| Flesch-Kincaid grade level | 3.505 |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, il_hte_45.R. 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.
| Column | What it is | Source column |
|---|---|---|
| IRW standard columns | ||
id | IRW 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 |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | not traced |
treat | IRW standard Treatment group assignment in experimental studies. | made in the build script |
wave | IRW standard Longitudinal wave indicator. | not traced |
| Respondent covariates | ||
cov_age | Covariate | what_is_your_age |
cov_female | Covariate | what_is_your_self_identified_gender |
cov_race | Covariate | what_is_your_race |
cov_role | Covariate | what_is_your_role_on_the_healthcare_team |
cov_years_exp | Covariate | how_many_years_of_experience_do_you_have |
What item codes and covariate values stand for is in the codebook released with the source data.
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("gilbert_meta_45")
# Python
pip install irw
import irw
df = irw.fetch("gilbert_meta_45")
@misc{https://doi.org/10.7910/dvn/diu6bu,
doi = {10.7910/DVN/DIU6BU},
url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/DIU6BU},
author = {Bateman, Marjorie},
keywords = {Medicine, Health and Life Sciences, Burnout, Critical Care, Healthcare workers},
title = {STOPTHEBURN Randomized Controlled Trial Data},
publisher = {Harvard Dataverse},
year = {2023}
}
| IRW version | v557 |
|---|---|
| Redivis dataset | item_response_warehouse v70.0 |
| Redivis dataset DOI | 10.57761/4qxs-pq87 |
| Manifest pin for this IRW version | v70.0 |
| Metadata source | irw_meta v40.0 |