pezzuti_2025_coolpeople_main_trendy_USA

3,376 responses from 844 respondents to 4 items.

About this table

DescriptionCoolness ratings of fashionableness and alignment with current style trends
ReferencePezzuti T, Warren C, Chen J. Cool people. J Exp Psychol Gen. 2025 Sep;154(9):2410-2431. doi: 10.1037/xge0001799. Epub 2025 Jun 30. PMID: 40587319.
DOI10.1037/xge0001799
LicenceCC BY 4.0
Source datahttps://osf.io/m7gps/overview?view_only=d3fec7aa6c994b0f873403b2dcde15a0

Size and shape

Responses3,376
Respondents844
Items4
Response categories7
Responses per respondent4
Responses per item844
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleGeneral/non-specific, Internet-based
construct typeOpinion/attitude
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng
construct nameTrendy

Item text

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

InstrumentCoolness ratings of fashionableness and alignment with current style trends
Mean words per item5.250
Mean characters per item30.750
Mean characters per response5.857
Flesch-Kincaid grade level2.557

Columns

cov_agecov_countrycov_gendercov_hdicov_individualismcov_powerdistancecov_yeariditemresp

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("pezzuti_2025_coolpeople_main_trendy_USA")
# Python
pip install irw

import irw
df = irw.fetch("pezzuti_2025_coolpeople_main_trendy_USA")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse_2 v19.0
Redivis dataset DOI10.57761/qtx5-4m80
Manifest pin for this IRW versionv19.0
Metadata sourceirw_meta v23.0