Evidence map›Paper›PMID 40365630›Full record

ArticleFrontiers in psychology2025

Trust in machines: how personality trait shapes static and dynamic trust across different human-machine interaction modalities.

Yi Zhu, Guiqi Hua, Xinning Liu, Chang Wang, Mingwei Tang

Abstract read
In one paragraph

Article in Frontiers in psychology, 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

5 authors.

Yi ZhuSchool of Computer Science, Nanjing Audit University, Nanjing, Jiangsu, China.
Guiqi HuaSchool of Computer Science, Nanjing Audit University, Nanjing, Jiangsu, China.
Xinning LiuInternational School, Nanjing Audit University, Nanjing, Jiangsu, China.
Chang WangCollege of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan, China.
Mingwei TangSchool of Engineering Audit, Nanjing Audit University, Nanjing, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rapid advancement of Artificial Intelligence (AI), intelligent machines are increasingly displaying "human-like personality," shifting Human-Machine Interaction (HMI) from one-way guidance to interactive, multi-level dynamics. Trust plays a pivotal role in the development and maintenance of these evolving interactions. While personality traits have been recognized as key factors in shaping and enhancing interpersonal trust, their role in the development of static and dynamic trust in HMI remains underexplored. This study investigates how personality traits influence trust in HMI across two interaction modalities: Personal Computer (PC) and Virtual Reality (VR). By simulating real-world interaction scenarios, we examined the impact of personality traits on both static and dynamic trust, and explored the relationship between them. The results showed that in the PC modality, personality traits significantly affected both static and dynamic trust, with static trust serving as a strong predictor of dynamic trust. In the VR modality, personality traits significantly influenced static trust, and static trust again played a key role in shaping dynamic trust. These findings underscore the foundational importance of static trust in the evolution of trust in HMI, and highlight the need to consider individual personality differences and interaction modalities in the design of AI-driven interfaces to foster trust and promote long-term engagement.

Indexed as

artificial intelligencedynamic trusthuman–machine interactioninteraction modalitiespersonality trait

Identifiers

PMID40365630
PMCPMC12069323

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LicenceCC BY
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Registered trials

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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.