blaszyk_2023_tbm

2,988 responses from 273 respondents to 11 items.

One of 8 tables from the same source; this one measures Trusting Beliefs Measure (McKnight et al., 2002). The others are listed under Related tables.

About this table

DescriptionTrusting Beliefs Measure (McKnight et al. 2002, Polish; physicians rating themselves), 11 items, 1-7 agreement, 307 Polish physicians from 51 specialties (online, N per table 254-288 after missing codes); cov_age, cov_specialty.
ReferenceBlaszyk, M. A., & Kroemeke, A. (2023). Polish adaptation of Physician's Trust in the Patient Scale (PTPS) - psychometric properties and validation [Data set]. Mendeley Data, V1. https://doi.org/10.17632/x2rxtpzg4v.1
LicenceCC BY 4.0
Source datahttps://data.mendeley.com/datasets/x2rxtpzg4v/1

Size and shape

Responses2,988
Respondents273
Items11
Response categories7
Responses per respondent10.945
Responses per item271.636
Density0.995
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleTargeted/specific, Workplace
construct typeOpinion/attitude
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)pol
construct nameTrusting Beliefs Measure (McKnight et al., 2002)

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, blaszyk_2023_ptps.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.

ColumnWhat it isSource column
IRW standard columns
idIRW 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
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
Respondent covariates
cov_ageCovariate made in the build script
cov_specialtyCovariate made in the build script

What item codes and covariate values stand for is in the source’s codebook, file_downloaded.

Get the data

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

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("blaszyk_2023_tbm")
# Python
pip install irw

import irw
df = irw.fetch("blaszyk_2023_tbm")

How to cite

@misc{https://doi.org/10.17632/x2rxtpzg4v.1,
  doi = {10.17632/X2RXTPZG4V.1},
  url = {https://data.mendeley.com/datasets/x2rxtpzg4v/1},
  author = {{Marta Adrianna Blaszyk}},
  title = {Polish adaptation of Physician’s Trust in the Patient Scale (PTPS) – psychometric properties and validation},
  publisher = {Mendeley},
  year = {2023},
  copyright = {Creative Commons Attribution 4.0 International}
}

Version and provenance

IRW versionv584
Redivis datasetitem_response_warehouse_5 v8.5
Redivis dataset DOI10.57761/41xy-5k56
Manifest pin for this IRW versionv8.5
Metadata sourceirw_meta v44.0