3,636 responses from 202 respondents to 18 items.
| Description | 18-item Japanese Healthy Work Environment Assessment Tool (HWE-AT-J, 1-5 Likert), main validation sample of critical-care nurses |
|---|---|
| Reference | Kitayama M, Unoki T, Matsuda Y, Matsuishi Y, Kawai Y, Iida Y (2022) Development and initial validation of the Japanese healthy work environment assessment tool for critical care settings. PLoS ONE. |
| DOI | 10.1371/journal.pone.0268124 |
| Licence | CC BY 4.0 |
| Source data | https://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0268124.s004 |
| Responses | 3,636 |
|---|---|
| Respondents | 202 |
| Items | 18 |
| Response categories | 5 |
| Responses per respondent | 18 |
| Responses per item | 202 |
| Density | 1 |
| Longitudinal | FALSE |
| sample | Workplace |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | jpn |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Japanese version of the Healthy Work Environment Assessment Tool (HWE-AT-J) |
|---|---|
| Mean words per item | 26.167 |
| Mean characters per item | 179.389 |
| Mean characters per response | 2 |
| Flesch-Kincaid grade level | 15.135 |
iditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("kitayama_2022_hweat")
# Python
pip install irw
import irw
df = irw.fetch("kitayama_2022_hweat")
| 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 |