ArticleFrontiers in psychology2026
Factors shaping willingness to adopt generative artificial intelligence tools among university students: a TAM-based investigation.
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.
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.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the rapid advancement of generative artificial intelligence (GAI) technology, college students represent a crucial demographic in the adoption of emerging technologies. Their willingness to use such tools plays a significant role in shaping the integration and dissemination of GAI platforms. Extending the Technology Acceptance Model (TAM), this study proposes and tests a sequential mediation chain: perceived ease of use → perceived usefulness → satisfaction → user trust → behavioral intention. and develops a corresponding structural equation model (SEM) to systematically explore the factors influencing college students' willingness to use GAI platforms. The study employed a questionnaire survey method and collected a total of 334 valid responses. Results confirm that perceived ease of use and perceived usefulness exert significant direct positive effects on satisfaction. Satisfaction, in turn, further enhances users' trust in GAI platforms, and user trust is the key factor driving behavioral intention. This study enriches the theoretical application of the TAM in the context of GAI platforms, identifies key pathways influencing university students' behavioral intentions, and has valuable practical implications for the design optimization, trust mechanism development, and formulation of promotion strategies for GAI platforms.
Indexed as
Identifiers
What OpenQuestion holds
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.