2,727 responses from 539 respondents to 6 items.
| Description | Brief Resilience Scale (6 items), first-year medical students, N=539 |
|---|---|
| Reference | Jordan RK, Shah SS, Desai H, Tripi J, Mitchell A, Worth RG (2020). Variation of stress levels, burnout, and resilience throughout the academic year in first-year medical students. PLOS ONE, 15(10), e0240667. https://doi.org/10.1371/journal.pone.0240667 |
| DOI | 10.1371/journal.pone.0240667 |
| Licence | CC BY 4.0 |
| Source data | https://doi.org/10.1371/journal.pone.0240667.s001 |
| Responses | 2,727 |
|---|---|
| Respondents | 539 |
| Items | 6 |
| Response categories | 5 |
| Responses per respondent | 5.059 |
| Responses per item | 454.500 |
| Density | 0.843 |
| Longitudinal | FALSE |
| sample | Educational |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Brief Resilience Scale (BRS) |
|---|---|
| Mean words per item | 11 |
| Mean characters per item | 56.167 |
| Mean characters per response | 10.200 |
| Flesch-Kincaid grade level | 3.911 |
iditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("jordan_2020_resilience")
# Python
pip install irw
import irw
df = irw.fetch("jordan_2020_resilience")
| 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 |