1,608 responses from 134 respondents to 12 items.
| Description | Self-Concept Clarity Scale (12 items, 1–5 Likert), Chinese university students, N=134 |
|---|---|
| Reference | Qi, Y., Zou, F., Chau, X. Y., Zhou, M., Wang, F., & Sui, J. (2025). A Comprehensive Dataset for Investigating the Structure of Self-Bias. Scientific Data, 12, 1755. https://doi.org/10.1038/s41597-025-06035-z |
| DOI | 10.1038/s41597-025-06035-z |
| Licence | CC BY 4.0 |
| Source data | https://doi.org/10.17605/OSF.IO/3H95F |
| Responses | 1,608 |
|---|---|
| Respondents | 134 |
| Items | 12 |
| Response categories | 5 |
| Responses per respondent | 12 |
| Responses per item | 134 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Educational |
| construct type | Personality |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | chi |
| construct name | Self-Concept Clarity Scale (SCCS) |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Self-Concept Clarity Scale |
|---|---|
| Mean words per item | 15.500 |
| Mean characters per item | 78 |
| Mean characters per response | 7.400 |
| Flesch-Kincaid grade level | 6.950 |
cov_agecov_genderiditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("qi_2025_self_concept_clarity")
# Python
pip install irw
import irw
df = irw.fetch("qi_2025_self_concept_clarity")
| 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 |