9,557 responses from 484 respondents to 20 items.
| Description | Perceived benefits of medical cannabis (20 yes/no items) among 485 adult medical-cannabis users in Thailand recruited by respondent-driven sampling |
|---|---|
| Reference | Assanangkornchai, S., Thaikla, K., Talek, M., & Saingam, D. (2022). Medical cannabis use in Thailand after its legalization: a respondent-driven sample survey. PeerJ, 10, e12809. |
| DOI | 10.7717/peerj.12809 |
| Licence | CC BY 4.0 |
| Source data | https://europepmc.org/article/PMC/PMC8759353 |
| Responses | 9,557 |
|---|---|
| Respondents | 484 |
| Items | 20 |
| Response categories | 2 |
| Responses per respondent | 19.746 |
| Responses per item | 477.850 |
| Density | 0.987 |
| Longitudinal | FALSE |
cov_agecov_cannabis_sourcecov_condition_for_usecov_condition_moph_classcov_educationcov_gendercov_network_sizecov_occupationcov_regioniditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("assanangkornchai_2022_cannabis_benefits")
# Python
pip install irw
import irw
df = irw.fetch("assanangkornchai_2022_cannabis_benefits")
@article{Assanangkornchai_2022, title={Medical cannabis use in Thailand after its legalization: a respondent-driven sample survey}, volume={10}, ISSN={2167-8359}, url={http://dx.doi.org/10.7717/peerj.12809}, DOI={10.7717/peerj.12809}, journal={PeerJ}, publisher={PeerJ}, author={Assanangkornchai, Sawitri and Thaikla, Kanittha and Talek, Muhammadfahmee and Saingam, Darika}, year={2022}, month=Jan, pages={e12809} }
| IRW version | v439 |
|---|---|
| Redivis dataset | item_response_warehouse_6 v3.7 |
| Redivis dataset DOI | 10.57761/k0pn-7r67 |
| Manifest pin for this IRW version | v3.6 |
| Metadata source | irw_meta v27.0 |