kraft_todd_2017_competence

6,357 responses from 1,371 respondents to 5 items.

About this table

DescriptionCompetence ratings (5 items) of physicians in a nonverbal-empathy manipulation experiment, pooled across 4 sub-studies
ReferenceKraft-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
DOI10.1371/journal.pone.0177758
LicenceCC BY 4.0
Source datahttps://doi.org/10.1371/journal.pone.0177758.s003

Size and shape

Responses6,357
Respondents1,371
Items5
Response categories5
Responses per respondent4.637
Responses per item1271.400
Density0.927
LongitudinalFALSE

Classification

sampleInternet-based
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng

Item text

This table has item text in the IRW: the wording administered to respondents, not just the response codes.

InstrumentWarmth/competence scale (competence items), adapted from Fiske et al. 2002
Mean words per item1
Mean characters per item10.200
Mean characters per response6
Flesch-Kincaid grade level27.280

Columns

cov_condition_coatcov_condition_empathycov_sexcov_studyiditemresp

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

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_competence")
# Python
pip install irw

import irw
df = irw.fetch("kraft_todd_2017_competence")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse_3 v7.0
Redivis dataset DOI10.57761/pqqn-pm43
Manifest pin for this IRW versionv7.0
Metadata sourceirw_meta v23.0