ReviewJournal of Intelligence2025
A Systematic Review of User Attitudes Toward GenAI: Influencing Factors and Industry Perspectives.
Review in Journal of Intelligence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Utility judgments, risk concerns, and generative AI use intention among first-year university students.Frontiers in psychology · 2026Article
- Physician perceptions of artificial intelligence in Northern Italy healthcare: a survey of fears and expectations.Frontiers in artificial intelligence · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
In the era of GenAI, user attitude-shaped by cognition, emotion, and behavior-plays a critical role in the sustainable development of human-AI interaction. Human creativity and intelligence, as core drivers of social progress, are important factors influencing user attitudes. This paper systematically reviews 243 peer-reviewed studies on GenAI user attitudes published since 2019, identifying major research methods and theoretical perspectives, including the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the AI Device Use Acceptance (AIDUA) model. Drawing on contemporary creativity theories-such as Sternberg's Theory of Successful Intelligence, the 4C Model by Kaufman and Beghetto, and the Dynamic Creativity Framework-we analyze how creativity and intelligence are conceptualized in current studies and how they affect user responses to GenAI. Through cross-cultural analysis and multimodal comparison, this review offers a comprehensive understanding of the interplay between GenAI and human creativity, aiming to support more inclusive and sustainable human-AI collaboration.
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.