shu_2025_translation_pcd

16,864 responses from 1,054 respondents to 16 items.

About this table

DescriptionProfessional commitment and devotion ratings
ReferenceShu X, Feng C, Ip C-L, Zhang X, Yang N, Li S, et al. (2025) Translation and cultural adaption of MacLeod Clark professional identity scale among Chinese therapy students. PLoS ONE 20(1): e0318101. https://doi.org/10.1371/journal.pone.0318101
DOI10.1371/journal.pone.0318101
LicenceCC BY 4.0
Source datahttps://figshare.com/articles/dataset/Datasets_for_the_project_of_Translation_and_cultural_adaption_of_MacLeod_Clark_Professional_Identity_Scale_among_Chinese_therapy_students_/28136309/1

Size and shape

Responses16,864
Respondents1,054
Items16
Response categories9
Responses per respondent16
Responses per item1,054
Density1
LongitudinalFALSE

Classification

age rangeMixed
sampleEducational, Targeted/specific
construct typeAffective/mental health, Opinion/attitude
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng, chi
construct nameProfessional Commitment and Devotion

Item text

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

InstrumentProfessional commitment and devotion ratings
Mean words per item13.812
Mean characters per item78.125
Mean characters per response17.556
Flesch-Kincaid grade level7.474

Columns

cov_agecov_genderiditemresp

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("shu_2025_translation_pcd")
# Python
pip install irw

import irw
df = irw.fetch("shu_2025_translation_pcd")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse v53.0
Redivis dataset DOI10.57761/4g08-xt41
Manifest pin for this IRW versionv53.0
Metadata sourceirw_meta v23.0