9,525 responses from 1,361 respondents to 7 items.
| Description | 7-item Medical Students' Well-Being Index (MSWBI, dichotomous 0/1 items, originally Polish "Tak"/"Nie"), from a survey of N=1361 Polish medical students during the COVID-19 pandemic. |
|---|---|
| Reference | Forycka J, Pawłowicz-Szlarska E, Burczyńska A, Cegielska N, Harendarz K, Nowicki M (2022) Polish medical students facing the pandemic—Assessment of resilience, well-being and burnout in the COVID-19 era. PLoS ONE. |
| DOI | 10.1371/journal.pone.0261652 |
| Licence | CC BY 4.0 |
| Source data | https://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0261652.s002 |
| Responses | 9,525 |
|---|---|
| Respondents | 1,361 |
| Items | 7 |
| Response categories | 2 |
| Responses per respondent | 6.999 |
| Responses per item | 1360.714 |
| Density | 1.000 |
| Longitudinal | FALSE |
| sample | Internet-based |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | pol |
cov_agecov_gendercov_school_yeariditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("forycka_2022_mswbi")
# Python
pip install irw
import irw
df = irw.fetch("forycka_2022_mswbi")
| 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 |