27,420 responses from 1,371 respondents to 20 items.
| Description | PANAS (20 items, positive+negative affect) administered in a physician nonverbal-empathy manipulation experiment, pooled across 4 sub-studies |
|---|---|
| Reference | Kraft-Todd GT, Reinero DA, Kelley JM, Heberlein AS, Baer L, Riess H (2017). Empathic nonverbal behavior increases ratings of both warmth and competence in a medical context. PLOS ONE, 12(5), e0177758. https://doi.org/10.1371/journal.pone.0177758 |
| DOI | 10.1371/journal.pone.0177758 |
| Licence | CC BY 4.0 |
| Source data | https://doi.org/10.1371/journal.pone.0177758.s003 |
| Responses | 27,420 |
|---|---|
| Respondents | 1,371 |
| Items | 20 |
| Response categories | 5 |
| Responses per respondent | 20 |
| Responses per item | 1,371 |
| Density | 1 |
| Longitudinal | FALSE |
| sample | Internet-based |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Positive and Negative Affect Schedule (PANAS) |
|---|---|
| Mean words per item | 1 |
| Mean characters per item | 7.400 |
| Mean characters per response | 13 |
| Flesch-Kincaid grade level | 13.710 |
cov_condition_coatcov_condition_empathycov_sexcov_studyiditemitemcov_valenceresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("kraft_todd_2017_panas")
# Python
pip install irw
import irw
df = irw.fetch("kraft_todd_2017_panas")
| 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 |