Evidence map›Paper›PMID 42602260›Full record

ArticleFrontiers in psychology2026

Extending the UTAUT model to explore the acceptance and use of generative AI: the roles of generative AI identity and trust.

Der-Fa Chen, Han-Piao Lin, Tzu-Hsin Chu

Abstract read
In one paragraph

Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Der-Fa ChenGraduate Institute of Technological and Vocational Education, National Changhua University of Education, Changhua City, Taiwan.
Han-Piao LinDepartment of Electrical and Mechanical Technology, National Changhua University of Education, Changhua, Taiwan.
Tzu-Hsin ChuDepartment and Graduate Institute of Information Management, Yu Da University of Science and Technology, Miaoli County, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Generative AI (GenAI) technology has been rapidly integrated into diverse domains, including education. It has fundamentally reshaped the global learning landscape, exerting a significantly positive influence on students' learning experience. However, the factors influencing adult learners' behavioral intention to use GenAI have not yet been fully understood. Therefore, this study aims to explore key factors influencing the behavioral intention to use GenAI among adult learners from central Taiwan. Based on the unified theory of acceptance and use of technology (UTAUT) model, this study integrated two constructs-GenAI identity and trust-to extend the model. Methods: A structured questionnaire survey was performed to collect data from 718 adult learners who were aged 50 or above and from central Taiwan. Partial least squares (PLS) and Partial least squares-Multi-group analyses (PLS-MGA) were employed for data analysis. Results: The following results were obtained: (1) social influence and facilitating conditions are significant antecedent factors influencing adult learners' behavioral intention to use GenAI-conversely, performance expectancy has a negative influence on such intention; (2) GenAI identity and trust are key predictive variables of performance expectancy and effort expectancy; (3) different gender groups exhibit significant differences in most structural paths of the research model. Discussion: These findings provide theoretical support for context-sensitive strategies in adult learning and the educational application of GenAI.

Indexed as

adult learninggenerative AI identitygenerative AI trustgenerative artificial intelligence (generative AI)multi-group analysis

Identifiers

PMID42602260
PMCPMC13473430

What OpenQuestion holds

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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.