1,514 responses from 303 respondents to 5 items.
One of 3 tables from the same source; this one is the who5 table. The others are listed under Related tables.
| Description | WHO-5 Well-Being Index (5 items), Chinese college students |
|---|---|
| Reference | Hui Z, Wang X, Teng Z, Zou W, Wang J, Ji P, Wang M (2024). The Chinese version of the general benefit finding scale (GBFS): Psychometric properties in a sample of college students. PLOS ONE, 19(5), e0300064. https://doi.org/10.1371/journal.pone.0300064 |
| DOI | 10.1371/journal.pone.0300064 |
| Licence | CC BY 4.0 |
| Source data | https://doi.org/10.1371/journal.pone.0300064.s002 |
| Responses | 1,514 |
|---|---|
| Respondents | 303 |
| Items | 5 |
| Response categories | 6 |
| Responses per respondent | 4.997 |
| Responses per item | 302.800 |
| Density | 0.999 |
| Longitudinal | FALSE |
| sample | Educational |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | chi |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, hui_2024_gbfs_battery.py. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.
| Column | What it is | Source column |
|---|---|---|
| IRW standard columns | ||
id | IRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task). | No |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
What item codes and covariate values stand for is in the codebook released with the source data.
Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("hui_2024_who5")
# Python
pip install irw
import irw
df = irw.fetch("hui_2024_who5")
@article{Hui_2024, title={The Chinese version of the general benefit finding scale (GBFS): Psychometric properties in a sample of college students}, volume={19}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0300064}, DOI={10.1371/journal.pone.0300064}, number={5}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Hui, Zhaozhao and Wang, Xuan and Teng, Ziyi and Zou, Wenfeng and Wang, Jing and Ji, Pengcheng and Wang, Mingxu}, editor={Sudzina, Frantisek}, year={2024}, month=May, pages={e0300064} }
| IRW version | v549 |
|---|---|
| Redivis dataset | item_response_warehouse_3 v13.0 |
| Redivis dataset DOI | 10.57761/gpg7-sg87 |
| Manifest pin for this IRW version | v13.0 |
| Metadata source | irw_meta v39.0 |