2,800 responses from 400 respondents to 7 items.
| Description | Priority ratings (4-pt ordinal) of 7 clinical teaching-skill domains from 400 clinical educators across 6 Jordanian universities/hospitals, informing preceptor development program design. |
|---|---|
| Reference | Albeitawi et al. (2025). Assessment of clinical medical education needs inform design of a preceptor development program in Jordan. PLOS ONE. |
| DOI | 10.1371/journal.pone.0337101 |
| Licence | CC BY 4.0 |
| Source data | https://doi.org/10.1371/journal.pone.0337101 |
| Responses | 2,800 |
|---|---|
| Respondents | 400 |
| Items | 7 |
| Response categories | 4 |
| Responses per respondent | 7 |
| Responses per item | 400 |
| Density | 1 |
| Longitudinal | FALSE |
| sample | Workplace |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | ara |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Training Need Assessment for Clinical Preceptors |
|---|---|
| Mean words per item | 3.571 |
| Mean characters per item | 26.429 |
| Mean characters per response | 13.500 |
| Flesch-Kincaid grade level | 9.875 |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, albeitawi_2025_preceptor_needs.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). | made in the build script |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
| Respondent covariates | ||
cov_gender | Covariate | Kindly indicate your gender\n |
cov_health_sector | Covariate | Kindly indicate the health sector you currently work at\n |
cov_specialty_category | Covariate | Kindly indicate your specialty according to core board certification\n |
cov_university | Covariate | University |
cov_years_experience | Covariate | Kindly indicate your years of expertise as a clinical educator \n |
What item codes and covariate values stand for is in the source’s documentation, S1_File.docx.
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("albeitawi_2025_preceptor_needs")
# Python
pip install irw
import irw
df = irw.fetch("albeitawi_2025_preceptor_needs")
@article{Albeitawi_2025, title={Assessment of clinical medical education needs inform design of a preceptor development program in Jordan: A multi method study}, volume={20}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0337101}, DOI={10.1371/journal.pone.0337101}, number={11}, journal={PLOS One}, publisher={Public Library of Science (PLoS)}, author={Albeitawi, Soha and Al-zubi, Mohammad Talal and Aljaiuossi, Anas and Shatnawi, Murad and Al-Kharabsheh, Ahlam and Sawaqed, Fadi and Aborajooh, Emad and Wadi, Walid I. and Mahasneh, Randa and Colton, Benjamin Rowland and AlQudah, Mohammad and Kufoof, Tamara and Asali, Fida and Sheyyab, Ahmed and Gharaibeh, Monther A. and Al-latayfeh, Motasem and Al-Zayadneh, Enas and Badran, Eman and Rayyan, Yaser M. and Al Balbissi, Kais and Al-Taher, Raed and Basha, Asma and Saqan, Rola and Oweis, Ashraf Omar and Taher, Wafa and Hamouri, Shadi}, editor={Christmals, Christmal Dela}, year={2025}, month=Nov, pages={e0337101} }
| IRW version | v557 |
|---|---|
| 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 v40.0 |