2,880 responses from 160 respondents to 18 items.
| Description | Beliefs about Medicines Questionnaire (BMQ), 18 items on a 1-5 scale, Malaysian hypertensive outpatients. 2,880 responses from 160 respondents on 18 items. |
|---|---|
| Reference | Aziz F, Malek S, Mhd Ali A, Wong MS, Mosleh M, Milow P (2020). Determining hypertensive patients' beliefs towards medication and associations with medication adherence using machine learning methods. PeerJ, 8, e8286. https://doi.org/10.7717/peerj.8286 |
| DOI | 10.7717/peerj.8286 |
| Licence | CC BY 4.0 |
| Source data | https://europepmc.org/article/PMC/PMC7075362 |
| Responses | 2,880 |
|---|---|
| Respondents | 160 |
| Items | 18 |
| Response categories | 5 |
| Responses per respondent | 18 |
| Responses per item | 160 |
| Density | 1 |
| Longitudinal | FALSE |
| sample | Clinical |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | may |
cov_agecov_educationcov_ethnicitycov_gendercov_marital_statuscov_monthly_incomeiditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("aziz_2020_bmq")
# Python
pip install irw
import irw
df = irw.fetch("aziz_2020_bmq")
@article{Aziz_2020, title={Determining hypertensive patients’ beliefs towards medication and associations with medication adherence using machine learning methods}, volume={8}, ISSN={2167-8359}, url={http://dx.doi.org/10.7717/peerj.8286}, DOI={10.7717/peerj.8286}, journal={PeerJ}, publisher={PeerJ}, author={Aziz, Firdaus and Malek, Sorayya and Mhd Ali, Adliah and Wong, Mee Sieng and Mosleh, Mogeeb and Milow, Pozi}, year={2020}, month=Mar, pages={e8286} }
| IRW version | v407 |
|---|---|
| Redivis dataset | item_response_warehouse_6 v3.2 |
| Redivis dataset DOI | 10.57761/yvkw-nj32 |
| Manifest pin for this IRW version | v3.2 |
| Metadata source | irw_meta v24.0 |