10,864 responses from 388 respondents to 28 items.
| Description | Brief COPE (28 items), Indonesian resident physicians, N=388 |
|---|---|
| Reference | Menaldi SL, Raharjanti NW, Wahid M, Ramadianto AS, Nugrahadi NR, Adhiguna GMYP, Kusumoningrum DA (2023). Burnout and coping strategies among resident physicians at an Indonesian tertiary referral hospital during COVID-19 pandemic. PLOS ONE, 18(1), e0280313. https://doi.org/10.1371/journal.pone.0280313 |
| DOI | 10.1371/journal.pone.0280313 |
| Licence | CC BY 4.0 |
| Source data | https://doi.org/10.1371/journal.pone.0280313.s001 |
| Responses | 10,864 |
|---|---|
| Respondents | 388 |
| Items | 28 |
| Response categories | 4 |
| Responses per respondent | 28 |
| Responses per item | 388 |
| Density | 1 |
| Longitudinal | FALSE |
| sample | Workplace |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | ind |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Brief COPE (Indonesian administration) |
|---|---|
| Mean words per item | 10.071 |
| Mean characters per item | 56.679 |
| Mean characters per response | 12.500 |
| Flesch-Kincaid grade level | 5.661 |
iditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("menaldi_2023_brief_cope")
# Python
pip install irw
import irw
df = irw.fetch("menaldi_2023_brief_cope")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_3 v7.0 |
| Redivis dataset DOI | 10.57761/pqqn-pm43 |
| Manifest pin for this IRW version | v7.0 |
| Metadata source | irw_meta v23.0 |