3,107 rated or chosen profiles from 3,107 respondents, in up to 1 tasks of 1 profile varying on 5 attributes.
| Description | US adults (NORC AmeriSpeak, June 2019, n = 3,107) each read one news story about a recovering opioid user whose race, gender, residential location, pathway to addiction and insurance were randomized, then rated federal spending on treatment and on law enforcement and whether addicts are to blame (5-point scales). |
|---|---|
| Reference | de Benedictis-Kessner, J., & Hankinson, M. (2024). How the identity of substance users shapes public opinion on opioid policy. Political Behavior, 46(1), 609-629. |
| DOI | 10.1007/s11109-022-09845-8 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/QMVU0Z |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 3,107 |
|---|---|
| Rows (one per respondent, task and profile) | 3,107 |
| Tasks per respondent (most) | 1 |
| Profiles per task | 1 |
| Attributes | 5 |
| Topic | health covid |
|---|---|
| A profile represents | person |
| Country | US |
| Language shown | en |
| Language of stored levels | en |
| Task order | inferred from row order |
| Profile position | inferred from row order |
Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.
Outcomes:
| rating_blame | Would you agree or disagree that individuals addicted to opioids are to blame for their own addiction? [rating, 1 (Strongly agree) to 5 (Strongly disagree)] |
|---|---|
| rating_enforcement | If you were making up the budget for the federal government this year, would you increase, decrease, or keep spending the same for law enforcement to arrest and prosecute those addicted to opioids? [rating, 1 (Increase a lot) to 5 (Decrease a lot)] |
| rating_treatment | If you were making up the budget for the federal government this year, would you increase, decrease, or keep spending the same for treatment for those addicted to opioids? [rating, 1 (Increase a lot) to 5 (Decrease a lot)] |
attr_genderattr_insuranceattr_locationattr_pathwayattr_racecov_agecov_attendancecov_devicecov_educationcov_employmentcov_gendercov_housingcov_ideologycov_incomecov_know_addict_1cov_know_addict_2cov_know_addict_3cov_know_addict_4cov_know_addict_5cov_maritalcov_metrocov_party_id7cov_race_ethnicitycov_region4cov_religioncov_statecov_survey_weightcov_urbanicityidprofilerating_blamerating_enforcementrating_treatmenttasktrial_name_quartiletrial_question_order
The layout (one row per respondent, task and profile; choice/rating outcomes; attr_ columns holding each attribute level as displayed) is defined in the IRW conjoint standard. What the outcomes asked is under Design above.
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("debenedictiskessner_2022_opioid_identity", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("debenedictiskessner_2022_opioid_identity", source="conj")
@article{de_Benedictis_Kessner_2022, title={How the Identity of Substance Users Shapes Public Opinion on Opioid Policy}, volume={46}, ISSN={1573-6687}, url={http://dx.doi.org/10.1007/s11109-022-09845-8}, DOI={10.1007/s11109-022-09845-8}, number={1}, journal={Political Behavior}, publisher={Springer Science and Business Media LLC}, author={de Benedictis-Kessner, Justin and Hankinson, Michael}, year={2022}, month=Dec, pages={609–629} }
| IRW version | v584 |
|---|---|
| Redivis dataset | irw_conjoint v4.2 |
| Redivis dataset DOI | 10.57761/qkye-q530 |
| Manifest pin for this IRW version | v4.2 |
| Metadata source | irw_meta v44.0 |