15,396 responses from 733 respondents to 22 items.
| Description | Maslach Burnout Inventory (22 items, 0-6 frequency scale) administered to 733 medical students at the Chinese University of Hong Kong, 2017. |
|---|---|
| Reference | Lee KP, Yeung N, Wong C, Yip B, Luk LHF, Wong S (2020). Prevalence of medical students' burnout and its associated demographics and lifestyle factors in Hong Kong. PLOS ONE 15(7): e0235154. https://doi.org/10.1371/journal.pone.0235154 |
| DOI | 10.1371/journal.pone.0235154 |
| Licence | CC BY 4.0 |
| Source data | https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0235154 |
| Responses | 15,396 |
|---|---|
| Respondents | 733 |
| Items | 22 |
| Response categories | 7 |
| Responses per respondent | 21.004 |
| Responses per item | 699.818 |
| Density | 0.955 |
| Longitudinal | FALSE |
| age range | Mixed |
|---|---|
| child age (for child-focused studies) | Adolescent (12-18y) |
| sample | Educational |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | chi |
cov_agecov_clinical_stagecov_first_degreecov_gendercov_marital_statuscov_place_of_livingcov_scholarshipcov_smokecov_study_yeariditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("lee_2020_burnout")
# Python
pip install irw
import irw
df = irw.fetch("lee_2020_burnout")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_4 v7.0 |
| Redivis dataset DOI | 10.57761/cpj5-vm97 |
| Manifest pin for this IRW version | v7.0 |
| Metadata source | irw_meta v23.0 |