6,672 responses from 556 respondents to 12 items.
One of 4 tables from the same source; this one is the beliefs_about_empathy table. The others are listed under Related tables.
| Description | 12-item Beliefs about Empathy Scale- combined across 2 studies (confirmed identical administration; ids offset per study) |
|---|---|
| Reference | Herrera F, Bailenson J, Weisz E, Ogle E, Zaki J (2018). Building long-term empathy: A large-scale comparison of traditional and virtual reality perspective-taking. PLOS ONE, 13(10), e0204494. https://doi.org/10.1371/journal.pone.0204494 |
| DOI | 10.1371/journal.pone.0204494 |
| Licence | CC BY 4.0 |
| Source data | https://doi.org/10.1371/journal.pone.0204494.s004 |
| Responses | 6,672 |
|---|---|
| Respondents | 556 |
| Items | 12 |
| Response categories | 7 |
| Responses per respondent | 12 |
| Responses per item | 556 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Mixed |
|---|---|
| child age (for child-focused studies) | Adolescent (12-18y) |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, herrera_2018_vr_empathy.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). | made in the build script |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
| Respondent covariates | ||
cov_age | Covariate | made in the build script |
cov_condition | Covariate | made in the build script |
cov_gender | Covariate | made in the build script |
cov_study | Covariate | made in the build script |
What item codes and covariate values stand for is in the source’s questionnaire, S2_Appendix.docx, which shows the item wording.
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("herrera_2018_beliefs_about_empathy")
# Python
pip install irw
import irw
df = irw.fetch("herrera_2018_beliefs_about_empathy")
@article{Herrera_2018, title={Building long-term empathy: A large-scale comparison of traditional and virtual reality perspective-taking}, volume={13}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0204494}, DOI={10.1371/journal.pone.0204494}, number={10}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Herrera, Fernanda and Bailenson, Jeremy and Weisz, Erika and Ogle, Elise and Zaki, Jamil}, editor={Bastian, Brock}, year={2018}, month=Oct, pages={e0204494} }
| IRW version | v566 |
|---|---|
| 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 v43.0 |