ajlan_2025_stemcell_knowledge

3,030 responses from 101 respondents to 30 items.

About this table

Description	Knowledge/attitude survey (30 items) on stem cell therapies among dental school faculty in Saudi Arabia. N=101.
Reference	Ajlan S, Ashri N (2025). Knowledge and attitude of dental school faculties towards stem cell therapies and their applications. PeerJ 13:e19127.
DOI	10.7717/peerj.19127
Licence	CC BY 4.0
Source data	https://europepmc.org/article/PMC/PMC11967409

Size and shape

Responses	3,030
Respondents	101
Items	30
Response categories	4
Responses per respondent	30
Responses per item	101
Density	1
Longitudinal	FALSE

Classification

sample	Workplace
measurement tool	Survey/questionnaire
item format	Likert 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.

Instrument	Knowledge and Attitude of Dental School Faculties in King Saud University Towards Stem Cell Therapies and Their Applications
Mean words per item	5.167
Mean characters per item	34.598
Mean characters per response	7.471
Flesch-Kincaid grade level	10.607

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, ajlan_2025_stemcell_knowledge.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.

Column	What it is	Source column
IRW standard columns
`id`	IRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task).	`Fsno`
`item`	IRW standard Item identifier.	made in the build script
`resp`	IRW standard Response value.	made in the build script
Respondent covariates
`cov_age_bracket`	Covariate	`Q1_Age`
`cov_gender`	Covariate	`Q2_Gender`
`cov_nationality`	Covariate	`Q3_Nationality`
`cov_speciality`	Covariate	`Q4_Speciality`

What item codes and covariate values stand for is in the source’s questionnaire, peerj-13-19127-s002.docx, which shows the item wording.

Get the data

Download CSVno account needed Browse on Redivisexplore and query Croissant 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("ajlan_2025_stemcell_knowledge")

# Python
pip install irw

import irw
df = irw.fetch("ajlan_2025_stemcell_knowledge")

How to cite

@article{Ajlan_2025, title={Knowledge and attitude of dental school faculties towards stem cell therapies and their applications}, volume={13}, ISSN={2167-8359}, url={http://dx.doi.org/10.7717/peerj.19127}, DOI={10.7717/peerj.19127}, journal={PeerJ}, publisher={PeerJ}, author={Ajlan, Sumaiah and Ashri, Nahid}, year={2025}, month=Mar, pages={e19127} }

Version and provenance

IRW version	v566
Redivis dataset	item_response_warehouse_4 v13.0
Redivis dataset DOI	10.57761/w8zx-td92
Manifest pin for this IRW version	v13.0
Metadata source	irw_meta v43.0