15,040 rated or chosen profiles from 1,504 respondents, in up to 5 tasks of 2 profiles varying on 6 attributes.
| Description | 1,504 UK adults (Dynata online sample, May 2020) each chose between 5 pairs of hypothetical COVID-19 contact-tracing apps varying in data storage, storage duration, contacts and location uploaded, purpose and contact definition; half saw a data-breach prime first. |
|---|---|
| Reference | Horvath, L., Banducci, S., & James, O. (2022). Citizens' attitudes to contact tracing apps. Journal of Experimental Political Science, 9(1), 118-130. |
| DOI | 10.1017/XPS.2020.30 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/KVKGUB |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 1,504 |
|---|---|
| Rows (one per respondent, task and profile) | 15,040 |
| Tasks per respondent (most) | 5 |
| Profiles per task | 2 |
| Attributes | 6 |
| Tasks with no profile chosen | 0 |
| Topic | technology ai privacy, health covid |
|---|---|
| A profile represents | product service |
| Country | GB |
| Language shown | en |
| Language of stored levels | en |
| Randomization restrictions | observed in the data (not documented by the source): storage = 'Decentralised, locally at device' always with stored until = 'Not stored', purpose = 'Notify users directly of exposure to virus', contacts uploaded = 'None', location uploaded = 'None'; 'Not stored' and 'Notify users directly' never occur with a central database |
| Task order | recorded in the deposit |
| Profile position | recorded in the deposit |
Because the attribute levels were not randomized independently, an estimator has to account for the restriction; a plain difference in means across levels can mislead.
Outcomes:
| choice | Here, we are presenting two hypothetical versions of a contact tracing app. Please choose the app which you would be more likely to install on your phone. Which app would you be more likely to install on your phone? [choice, forced] |
|---|
attr_contact_definitionattr_contacts_uploadedattr_location_uploadedattr_purposeattr_storageattr_stored_untilattrpos_contact_definitionattrpos_contacts_uploadedattrpos_location_uploadedattrpos_purposeattrpos_storageattrpos_stored_untilchoicecov_birth_yearcov_educationcov_gendercov_gov_handlingcov_regioncov_trust_nhsidprofiletasktrial_breach_prime
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("horvath_2022_contact_tracing_apps", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("horvath_2022_contact_tracing_apps", source="conj")
@article{Horvath_2020, title={Citizens’ Attitudes to Contact Tracing Apps}, volume={9}, ISSN={2052-2649}, url={http://dx.doi.org/10.1017/XPS.2020.30}, DOI={10.1017/xps.2020.30}, number={1}, journal={Journal of Experimental Political Science}, publisher={Cambridge University Press (CUP)}, author={Horvath, Laszlo and Banducci, Susan and James, Oliver}, year={2020}, month=Sept, pages={118–130} }
| 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 |