909 responses from 305 respondents to 3 items.
| Description | 3-item collective anger scale, 1-7. 305 respondents x 3 items = 909 responses. |
|---|---|
| Reference | Eldor, D., Lindholm, K., Chavez, M., Vassanyi, S., Badiane, M., Yaldizli, K., Froysa, P., Haugestad, C., & Kunst, J. (2022). Resilience against radicalization and extremism in schools: Development of a psychometric scale. Frontiers in Psychology, 13, 980180. https://doi.org/10.3389/fpsyg.2022.980180 |
| DOI | 10.3389/fpsyg.2022.980180 |
| Licence | CC BY 4.0 |
| Source data | https://frontiersin.figshare.com/articles/dataset/_/21531195 |
| Responses | 909 |
|---|---|
| Respondents | 305 |
| Items | 3 |
| Response categories | 7 |
| Responses per respondent | 2.980 |
| Responses per item | 303 |
| Density | 0.993 |
| Longitudinal | FALSE |
| sample | Educational, Program-based |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | nor |
cov_completion_time_scov_ethnicitycov_gendercov_schooliditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("eldor_2022_collective_anger")
# Python
pip install irw
import irw
df = irw.fetch("eldor_2022_collective_anger")
| 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 |