480,000 responses from 10,000 respondents to 48 items.
One of 5 tables from the same source; this one measures Trait Requirement. The others are listed under Related tables.
| Description | Fears About Artificial Intelligence Across 20 Countries and Six Domains of Application |
|---|---|
| Reference | Dong, M. (2024, November 25). A Psychological Model of AI fears. https://doi.org/10.17605/OSF.IO/MB5NZ |
| DOI | 10.1037/amp0001454 |
| Licence | CC BY 4.0 |
| Source data | https://osf.io/mb5nz/overview |
| Responses | 480,000 |
|---|---|
| Respondents | 10,000 |
| Items | 48 |
| Response categories | 101 |
| Responses per respondent | 48 |
| Responses per item | 10,000 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | General/non-specific |
| construct type | Opinion/attitude |
| measurement tool | Survey/questionnaire |
| item format | Slider/continuous |
| primary language(s) | eng |
| construct name | Trait Requirement |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, ai_fear_dong_2026.py. 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). | made in the build script |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
| Respondent covariates | ||
cov_age | Covariate | made in the build script |
cov_age_group | Covariate | made in the build script |
cov_country | Covariate | made in the build script |
cov_education | Covariate | made in the build script |
cov_gender | Covariate | made in the build script |
cov_income | Covariate | made in the build script |
cov_social_class | Covariate | made in the build script |
What item codes and covariate values stand for is in the source’s codebook, codebook-pilot-study.xlsx, long_format_codebook.xlsx.
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("ai_fear_dong_2026_requirement")
# Python
pip install irw
import irw
df = irw.fetch("ai_fear_dong_2026_requirement")
@article{Dong_2026, title={Fears about artificial intelligence across 20 countries and six domains of application.}, volume={81}, ISSN={0003-066X}, url={http://dx.doi.org/10.1037/amp0001454}, DOI={10.1037/amp0001454}, number={1}, journal={American Psychologist}, publisher={American Psychological Association (APA)}, author={Dong, Mengchen and Conway, Jane Rebecca and Bonnefon, Jean-François and Shariff, Azim and Rahwan, Iyad}, year={2026}, month=jan, pages={53–67} }
| IRW version | v566 |
|---|---|
| Redivis dataset | item_response_warehouse_2 v33.0 |
| Redivis dataset DOI | 10.57761/6m04-m698 |
| Manifest pin for this IRW version | v33.0 |
| Metadata source | irw_meta v43.0 |