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 |
cov_agecov_femalecov_racecov_rolecov_years_expiditemresptreatwave
Or load it directly in R or Python:
# 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")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse v53.0 |
| Redivis dataset DOI | 10.57761/4g08-xt41 |
| Manifest pin for this IRW version | v53.0 |
| Metadata source | irw_meta v23.0 |