4,120 responses from 515 respondents to 8 items.
One of 6 tables from the same source; this one measures Perception of program constraints. The others are listed under Related tables.
| Description | Perception of dengue-control program constraints, 8 items, 1-5 (strongly disagree-strongly agree); N = 515 adult residents of Denpasar, Indonesia (online survey). |
|---|---|
| Reference | Purnama, S. G., Susanna, D., Achmadi, U. F., & Eryando, T. (2023). Attitude towards dengue control efforts with the potential of digital technology during COVID-19: partial least squares-structural equation modeling. F1000Research, 11, 1283. https://doi.org/10.12688/f1000research.125318.2 |
| DOI | 10.12688/f1000research.125318.2 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.5061/dryad.jdfn2z3f0 |
| Responses | 4,120 |
|---|---|
| Respondents | 515 |
| Items | 8 |
| Response categories | 5 |
| Responses per respondent | 8 |
| Responses per item | 515 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Targeted/specific |
| construct type | Opinion/attitude |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | ind |
| construct name | Perception of program constraints |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Attitude towards dengue control efforts questionnaire (Purnama et al. 2023): Perception of program constraints |
|---|---|
| Mean words per item | 5.375 |
| Mean characters per item | 35.125 |
| Mean characters per response | 10.200 |
| Flesch-Kincaid grade level | 9.619 |
This codebook is reconstructed by the IRW from the IRW data standard. 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). | not traced |
item | IRW standard Item identifier. | not traced |
resp | IRW standard Response value. | not traced |
What item codes and covariate values stand for is in the source’s codebook, 2037150.
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("purnama_2023_constraints")
# Python
pip install irw
import irw
df = irw.fetch("purnama_2023_constraints")
@article{Purnama_2023, title={Attitude towards dengue control efforts with the potential of digital technology during COVID-19: partial least squares-structural equation modeling}, volume={11}, ISSN={2046-1402}, url={http://dx.doi.org/10.12688/f1000research.125318.2}, DOI={10.12688/f1000research.125318.2}, journal={F1000Research}, publisher={F1000 Research Ltd}, author={Purnama, Sang Gede and Susanna, Dewi and Achmadi, Umar Fahmi and Eryando, Tris}, year={2023}, month=June, pages={1283} }
| IRW version | v607 |
|---|---|
| Redivis dataset | item_response_warehouse_5 v10.0 |
| Redivis dataset DOI | 10.57761/45xf-md22 |
| Manifest pin for this IRW version | v9.0 |
| Metadata source | irw_meta v47.0 |