265 responses from 29 respondents to 5 items.
| Description | 5-item feedback-perceptions survey, first-year medical residents, pre/post intervention (wave=1/2), 1-5 Likert, N=29 |
|---|---|
| Reference | Cox, R., & Arthur, J. (2024). Feedback perceptions of first year medical residents: An intervention-based survey study. PLOS ONE. |
| DOI | 10.1371/journal.pone.0300205 |
| Licence | CC BY 4.0 |
| Source data | https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0300205 |
| Responses | 265 |
|---|---|
| Respondents | 29 |
| Items | 5 |
| Response categories | 3 |
| Responses per respondent | 9.138 |
| Responses per item | 53 |
| Density | 1.828 |
| Longitudinal | TRUE |
| sample | Workplace |
|---|---|
| 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 | Feedback perceptions questionnaire |
|---|---|
| Mean words per item | 11.800 |
| Mean characters per item | 75.800 |
| Mean characters per response | 9 |
| Flesch-Kincaid grade level | 10.412 |
iditemrespwave
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("cox_2024_feedback_perceptions")
# Python
pip install irw
import irw
df = irw.fetch("cox_2024_feedback_perceptions")
| 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 |