22,776 responses from 949 respondents to 24 items.
One of 9 tables from the same source; this one measures Psychological Uses of Artificial Intelligence scale (MPU-AI). The others are listed under Related tables.
| Description | Psychological uses of AI (MPU-AI; emotional, relational, academic and substitution uses), 24 items, 1-5, 949 adolescents in Spain (Basque and Spanish forms) and Greece; cov_form_language, cov_age, cov_gender, cov_grade. |
|---|---|
| Reference | Galindo Dominguez, H. (2026). Database from the manuscript entitled "Psychological Uses of Artificial Intelligence in Adolescence: Scale Development, Cross-Cultural Invariance, and Links to Loneliness and Emotional Intelligence" [Data set]. Harvard Dataverse. https://doi.org/10.7910/DVN/ZA15RI |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/ZA15RI |
| Responses | 22,776 |
|---|---|
| Respondents | 949 |
| Items | 24 |
| Response categories | 5 |
| Responses per respondent | 24 |
| Responses per item | 949 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Mixed |
|---|---|
| child age (for child-focused studies) | Adolescent (12-18y) |
| sample | Educational |
| construct type | Behavioral |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | baq, spa, gre |
| construct name | Psychological Uses of Artificial Intelligence scale (MPU-AI) |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, galindo_2026_ai_uses.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_form_language | Covariate | made in the build script |
cov_gender | Covariate | made in the build script |
cov_grade | Covariate | made in the build script |
What item codes and covariate values stand for is in the source’s codebook, 13914854.
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("galindo_2026_mpu_ai")
# Python
pip install irw
import irw
df = irw.fetch("galindo_2026_mpu_ai")
@misc{https://doi.org/10.7910/dvn/za15ri,
doi = {10.7910/DVN/ZA15RI},
url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/ZA15RI},
author = {GALINDO DOMINGUEZ, HECTOR},
keywords = {Social Sciences},
title = {Database from the manuscript entitled "Psychological Uses of Artificial Intelligence in Adolescence: Scale Development, Cross-Cultural Invariance, and Links to Loneliness and Emotional Intelligence"},
publisher = {Harvard Dataverse},
year = {2026}
}
| IRW version | v584 |
|---|---|
| Redivis dataset | item_response_warehouse_5 v8.5 |
| Redivis dataset DOI | 10.57761/41xy-5k56 |
| Manifest pin for this IRW version | v8.5 |
| Metadata source | irw_meta v44.0 |