Evidence map›Paper›PMID 41022973›Full record

ArticleScientific reports2025

Survey on Chinese users' acceptance of AI assistants: expanding technology acceptance model.

Wei Wang, Yifan Lu

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

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

2 authors.

Wei WangDepartment of Design, School of Architecture and Art, Central South University, Changsha, China.
Yifan LuDepartment of Design, School of Architecture and Art, Central South University, Changsha, China. 2676025463@qq.com.

Funding

2024 Hunan Provincial Key Project for Educational Science Planning XJK24ATW0012025 Central South University Program for Degree and Postgraduate Education Reform 2025JGB0742025 Hunan Provincial Teaching Reform Research Program for Regular Undergraduate Universities 202502000115
6 · The paper itself

Abstract

With the rapid development of artificial intelligence technology, AI assistants are gradually penetrating daily life and work. However, the internal mechanism of their user acceptance still needs to be further explored. Therefore, this study is based on the Technology Acceptance Model (TAM), introducing three external variables, Aesthetic Pleasure (AP), Information Quality (IQ), and AI Skills (AIS), to construct an extended model to explore the acceptance of AI assistants by Chinese users and its influencing factors. The results showed that aesthetic pleasure, information quality, and AI skills significantly affect perceived usefulness and ease of use by analyzing questionnaire survey data from 363 Chinese users and using structural equation modeling (CB-SEM) to validate hypotheses. AI skills, perceived usefulness, and perceived ease of use significantly affect behavioral intention. Notably, aesthetic pleasure and information quality do not affect behavioral intention. This study provides theoretical support for the design of AI assistants, helping designers and developers understand users' needs and preferences to better design AI assistants.

Indexed as

Artificial IntelligenceAdultChinaEast Asian PeopleFemaleHumansMaleMiddle AgedSurveys and QuestionnairesYoung AdultAesthetic pleasureAI assistantAI skillsInformation qualityTechnology acceptance model

Identifiers

PMID41022973
PMCPMC12480648

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.