Evidence map›Paper›PMID 34235291›Full record

ArticleComputers in human behavior reports

Initial validation of the general attitudes towards Artificial Intelligence Scale.

Astrid Schepman, Paul Rodway

3 registry-linked trialsAbstract read
In one paragraph

Article in Computers in human behavior reports. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 130 papers.

0numbers the graph read from it
0cells of the map it votes in
130citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT07308561 recruitingnot on this map

The Relationship Between Quality of Life, Anxiety Levels, and Attitudes Toward Artificial Intelligence Among Women Undergoing Infertility Treatment

TypeobservationalSponsorAcibadem UniversityRan2025 to 2026Enrolled191ConditionsInfertility, Female, Artificial Intelligence, Quality of Life, Anxiety
NCT07430358 narecruitingnot on this map

Obstetric Risk Assessment & Cesarean-delivery in Labor Estimation Using Artificial Intelligence Trial (ORACLE-AI)

TypeinterventionalSponsorHadassah Medical OrganizationRan2026 to 2027Enrolled400ConditionsLabor, Obstetric, Pregnancy, Cesarean Section RateArmsSoftware-based, real-time AI dashboard providing continuous risk estimates for unplanned cesarean delivery during labor.
NCT07631585 recruitingnot on this map

Longitudinal Pre-Post Patient AI Trust Dynamics in Orthopedic Outpatients: A Mixed-Methods Observational Study With Matched Physician-Patient Dyads

TypeobservationalSponsorUtku GürhanRan2026 to 2027Enrolled180ConditionsPatient Health Information Seeking Behavior, Trust, Health Literacy, Orthopedics
3 · Its place in the literature

Who cites it

130 citing papers in PubMed.

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  11. Modeling the cognitive processes of accepting clinical decision support.Quarterly journal of experimental psychology (2006) · 2026
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70 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Astrid SchepmanSchool of Psychology, University of Chester, United Kingdom.
Paul RodwaySchool of Psychology, University of Chester, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A new General Attitudes towards Artificial Intelligence Scale (GAAIS) was developed. The scale underwent initial statistical validation via Exploratory Factor Analysis, which identified positive and negative subscales. Both subscales captured emotions in line with their valence. In addition, the positive subscale reflected societal and personal utility, whereas the negative subscale reflected concerns. The scale showed good psychometric indices and convergent and discriminant validity against existing measures. To cross-validate general attitudes with attitudes towards specific instances of AI applications, summaries of tasks accomplished by specific applications of Artificial Intelligence were sourced from newspaper articles. These were rated for comfortableness and perceived capability. Comfortableness with specific applications was a strong predictor of general attitudes as measured by the GAAIS, but perceived capability was a weaker predictor. Participants viewed AI applications involving big data (e.g. astronomy, law, pharmacology) positively, but viewed applications for tasks involving human judgement, (e.g. medical treatment, psychological counselling) negatively. Applications with a strong ethical dimension led to stronger discomfort than their rated capabilities would predict. The survey data suggested that people held mixed views of AI. The initially validated two-factor GAAIS to measure General Attitudes towards Artificial Intelligence is included in the Appendix.

Indexed as

Artificial intelligenceAttitudesIndexPerceptionPsychometricsQuestionnaire

Identifiers

PMID34235291
PMCPMC7231759

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.