967 responses from 323 respondents to 3 items.
One of 11 tables from the same source; this one measures Health Promoting Behaviour for Bloating (HPB-Bloat) scale - health awareness subscale. The others are listed under Related tables.
| Description | HPB-Bloat health promoting behaviour scale, health awareness subscale (3 items), abdominal bloating study |
|---|---|
| Reference | Abdullah et al. (2024). Structural equation models of health behaviour, psychological well-being, symptom severity and quality of life in abdominal bloating. PeerJ. |
| DOI | 10.7717/peerj.17265 |
| Licence | CC BY 4.0 |
| Source data | https://europepmc.org/article/PMC/PMC11067892 |
| Responses | 967 |
|---|---|
| Respondents | 323 |
| Items | 3 |
| Response categories | 5 |
| Responses per respondent | 2.994 |
| Responses per item | 322.333 |
| Density | 0.998 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Clinical |
| construct type | Behavioral |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | may |
| construct name | Health Promoting Behaviour for Bloating (HPB-Bloat) scale - health awareness subscale |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, abdullah_2024_bloating.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). | ID |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
| Respondent covariates | ||
cov_bmi | Covariate | BMI |
What item codes and covariate values stand for is in the codebook released with the source data.
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("abdullah_2024_hpbbloat_awareness")
# Python
pip install irw
import irw
df = irw.fetch("abdullah_2024_hpbbloat_awareness")
@article{Abdullah_2024, title={Structural equation models of health behaviour, psychological well-being, symptom severity and quality of life in abdominal bloating}, volume={12}, ISSN={2167-8359}, url={http://dx.doi.org/10.7717/peerj.17265}, DOI={10.7717/peerj.17265}, journal={PeerJ}, publisher={PeerJ}, author={Abdullah, Nurzulaikha and Kueh, Yee Cheng and Kuan, Garry and Wong, Mung Seong and Tee, Vincent and Tengku Alang, Tengku Ahmad Iskandar and Hamid, Nurhazwani and Lee, Yeong Yeh}, year={2024}, month=Apr, pages={e17265} }
| IRW version | v549 |
|---|---|
| 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 v39.0 |