1,340 responses from 335 respondents to 4 items.
| Description | 4-item scale on confidence in AI-assisted cognitive tasks (decisions, memory recall, math), 4-point Likert, from a general-population AI-trust survey |
|---|---|
| Reference | Alasmari AA, Alruwaili RF, Alotaibi RF, Youssef IK, Asklany SA (2025) Demographic influences on trust in artificial intelligence across cognitive domains: A statistical perspective. PLoS ONE 20(11): e0331003. |
| DOI | 10.1371/journal.pone.0331003 |
| Licence | CC BY 4.0 |
| Source data | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0331003.s001&type=supplementary |
| Responses | 1,340 |
|---|---|
| Respondents | 335 |
| Items | 4 |
| Response categories | 4 |
| Responses per respondent | 4 |
| Responses per item | 335 |
| Density | 1 |
| Longitudinal | FALSE |
| sample | Educational |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | ara |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | AI Trust and Confidence Survey (Part 3: Perception of AI in Cognitive Tasks) |
|---|---|
| Mean words per item | 17.250 |
| Mean characters per item | 123.750 |
| Mean characters per response | 13 |
| Flesch-Kincaid grade level | 15.004 |
cov_agecov_ai_familiaritycov_ai_use_frequencycov_genderiditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("alasmari_2025_ai_trust_confidence")
# Python
pip install irw
import irw
df = irw.fetch("alasmari_2025_ai_trust_confidence")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_4 v7.0 |
| Redivis dataset DOI | 10.57761/cpj5-vm97 |
| Manifest pin for this IRW version | v7.0 |
| Metadata source | irw_meta v23.0 |