2,016 responses from 504 respondents to 4 items.
One of 3 tables from the same source; this one measures job performance. The others are listed under Related tables.
| Description | HPWT (Happy-Productive Worker Thesis), contains supervisor-rated assessments of employee performance using a 4-item standardized scale. |
|---|---|
| Reference | Bayona, J. A., Durán, W. F., Perdomo-Ortiz, J., Castañeda, D. I., Valencia, C. A., Fatien Diochon, P., & Alvarado, D. F. (2025). Happy-Productive worker thesis: The role of work characteristics, gender, and age. PloS one, 20(3), e0316656. |
| DOI | 10.1371/journal.pone.0316656 |
| Licence | CC BY 4.0 |
| Source data | https://figshare.com/articles/dataset/S1_Dataset_sav/25833070?file=46358782 |
| Responses | 2,016 |
|---|---|
| Respondents | 504 |
| Items | 4 |
| Response categories | 5 |
| Responses per respondent | 4 |
| Responses per item | 504 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Educational, General/non-specific |
| construct type | Behavioral |
| measurement tool | Observational rating |
| item format | Likert Scale/selected response |
| primary language(s) | spa |
| construct name | job performance |
These are classifications the IRW records, not the study’s own words. Some were annotated by hand and some written by an automated tagger whose output is published only where it clears a measured accuracy bar; which values came from which is not recorded per table. Coverage and accuracy per column, and what is held back, are on Tag quality.
This table is in 1 collection. Each membership records how it was decided:
rater_mediated — by ruleMembership is the IRW’s judgment and is worth checking before you use a collection as a sample. A hand-curated list is a snapshot: it is not re-checked when tables are added, so a table that would qualify may be missing. See Collections.
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, hpwt_bayona_2025.R. 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 |
rater | IRW standard Observer identifier in scenarios where items are rated by an external observer rather than self-reported. | made in the build script |
resp | IRW standard Response value. | made in the build script |
| Respondent covariates | ||
cov_age | Covariate | made in the build script |
cov_education | Covariate | made in the build script |
cov_gender | Covariate | made in the build script |
What item codes and covariate values stand for is in the codebook released with the source data.
Respondent uniqueness. 8% of this table’s respondents are alone in their combination of the 3 covariates above — no one else in the table shares it. That is a necessary condition for re-identification and not re-identification itself, and on a sample this size it is largely arithmetic. The IRW republishes the demographics its sources published and never at finer granularity: see the data standard.
Or load it directly in R (no account needed with irw 1.4.0 or later) or Python (needs a free Redivis account; the first call opens a browser to sign in):
# R
install.packages("irw")
library(irw)
df <- irw_fetch("hpwt_bayona_2025_jobperformance")
# Python
pip install irw
import irw
df = irw.fetch("hpwt_bayona_2025_jobperformance")
Or in Stata, which reads the same no-account CSV as the button above:
* Stata
net install irw, from("https://raw.githubusercontent.com/itemresponsewarehouse/Stata-pkg/main/")
irw_fetch hpwt_bayona_2025_jobperformance, clear
@article{Bayona_2025, title={Happy-Productive worker thesis: The role of work characteristics, gender, and age}, volume={20}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0316656}, DOI={10.1371/journal.pone.0316656}, number={3}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Bayona, Jaime A. and Durán, William F. and Perdomo-Ortiz, Jesús and Castañeda, Delio I. and Valencia, Carlos A. and Fatien Diochon, Pauline and Alvarado, Diego F.}, editor={Mahmoud, Ali B.}, year={2025}, month=mar, pages={e0316656} }
| IRW version | v674 |
|---|---|
| Redivis dataset | item_response_warehouse v78.0 |
| Redivis dataset DOI | 10.57761/yzj1-v654 |
| Manifest pin for this IRW version | v78.0 |
| Metadata source | irw_meta v59.0 |