13,455 responses from 897 respondents to 15 items.
One of 5 tables from the same source; this one measures Social well-being (K-12 teachers; scale not named in the deposit). The others are listed under Related tables.
| Description | Social Well-Being scale (15 items) for K-12 teachers in China |
|---|---|
| Reference | Che X (2026). Data of How Social Support Predicts the Social Well-being of K-12 teachers. figshare. https://doi.org/10.6084/m9.figshare.32090683.v1 |
| Licence | CC BY 4.0 |
| Source data | https://figshare.com/articles/dataset/32090683 |
| Responses | 13,455 |
|---|---|
| Respondents | 897 |
| Items | 15 |
| Response categories | 5 |
| Responses per respondent | 15 |
| Responses per item | 897 |
| Density | 1 |
| Longitudinal | FALSE |
| sample | Workplace |
|---|---|
| measurement tool | Survey/questionnaire |
| primary language(s) | chi |
| construct name | Social well-being (K-12 teachers; scale not named in the deposit) |
These are classifications the IRW records, not the study’s own words. Some were annotated by hand and some written by an automated tagger whose output is published only where it clears a measured accuracy bar; which values came from which is not recorded per table. Coverage and accuracy per column, and what is held back, are on Tag quality.
This table is in 1 collection. Each membership records how it was decided:
wellbeing — by ruleMembership is the IRW’s judgment and is worth checking before you use a collection as a sample. A hand-curated list is a snapshot: it is not re-checked when tables are added, so a table that would qualify may be missing. See Collections.
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, che_2026_social_support.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). | Participants ID |
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 (no account needed with irw 1.4.0 or later) or Python (needs a free Redivis account; the first call opens a browser to sign in):
# R
install.packages("irw")
library(irw)
df <- irw_fetch("che_2026_social_wellbeing")
# Python
pip install irw
import irw
df = irw.fetch("che_2026_social_wellbeing")
Or in Stata, which reads the same no-account CSV as the button above:
* Stata
net install irw, from("https://raw.githubusercontent.com/itemresponsewarehouse/Stata-pkg/main/")
irw_fetch che_2026_social_wellbeing, clear
@misc{https://doi.org/10.6084/m9.figshare.32090683.v1,
doi = {10.6084/M9.FIGSHARE.32090683.V1},
url = {https://figshare.com/articles/dataset/Data_of_b_How_Social_Support_Predicts_the_Social_Well-being_of_K-12_teachers_The_Mediating_Role_of_Regulation_Emotional_Self-efficacy_and_the_Differential_Moderating_Effects_of_Upward_Social_Identity_and_Upward_Social_Comparison_b_/32090683/1},
author = {Che, Xiang},
keywords = {Social psychology},
title = {Data of <b>How Social Support Predicts the Social Well-being of K-12 teachers: The Mediating Role of Regulation Emotional Self-efficacy and the Differential Moderating Effects of Upward Social Identity and Upward Social Comparison</b>},
publisher = {figshare},
year = {2026},
copyright = {Creative Commons Attribution 4.0 International}
}
| IRW version | v707 |
|---|---|
| Redivis dataset | item_response_warehouse_2 v36.0 |
| Redivis dataset DOI | 10.57761/cqv8-kp65 |
| Manifest pin for this IRW version | v36.0 |
| Metadata source | irw_meta v66.0 |