Evidence map›Paper›PMID 41920807›Full record

ArticlePloS one2026

Social cognitive impacts of digital art in metaverse environments: A cross-sectional study of user perception and behavioral patterns.

Lin Yang

Abstract read
In one paragraph

Article in PloS one, 2026. 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

1 author.

Lin YangCommunication University of China Nanjing, Nanjing, Jiangsu, China.ORCID https://orcid.org/0009-0005-4150-7910

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This cross-sectional study investigated the social cognitive correlates of digital art in metaverse environments through analysis of user perception and behavioral patterns. The research examined how exposure to digital art within immersive virtual spaces is associated with user cognition and identified demographic factors moderating these associations. Secondary analysis was conducted on multiple datasets including VREED (VR emotion dataset with physiological measures, n = 34), VR eye-tracking data (n = 152), virtual museum navigation records (~7 million), ArtEmis emotion attributions (455K annotations), and WikiArt metadata (80K artworks). Results revealed that digital art exposure showed significant positive associations with aesthetic perception and social value attribution, with moderate effect sizes. Three behavioral exploration patterns emerged: systematic explorers (31.6%), selective browsers (42.1%), and random wanderers (26.3%). Behavioral patterns partially mediated relationships between perception and social cognitive outcomes through emotional resonance, cognitive elaboration, and social mediation pathways. Significant moderation effects were identified for age (U-shaped pattern with strongest associations for 18-25 and 46 + groups), technology proficiency, and cultural background (differential patterns for collectivist versus individualist cultures). The findings demonstrate that digital art experiences in virtual environments are associated with meaningful differences in user perception and social cognition, though associations are moderate and heavily moderated by individual differences. This challenges assumptions about universal effects of metaverse technologies and highlights the need for adaptive, culturally-sensitive approaches to digital art presentation in virtual spaces.

Indexed as

ArtCognitionSocial CognitionAdolescentAdultCross-Sectional StudiesDigital MediaEmotionsFemaleHumansMaleMiddle AgedPerceptionYoung Adult

Identifiers

PMID41920807
PMCPMC13042640

What OpenQuestion holds

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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.