Evidence map›Paper›PMID 41872313›Full record

ArticleScientific reports2026

Restorative benefits of nature-related wooden elements in virtual reality settings for visual (eye-tracking) attention, performance, and experience.

Shunyan Zhang, Jian Lv, Weijie Pan

Abstract read
In one paragraph

Article in Scientific reports, 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

3 authors.

Shunyan ZhangThe Key Laboratory of Advanced Manufacturing Technology of the Ministry of Education, Guizhou University, Guiyang, Guizhou, China.ORCID http://orcid.org/0009-0000-4971-4360
Jian LvThe Key Laboratory of Advanced Manufacturing Technology of the Ministry of Education, Guizhou University, Guiyang, Guizhou, China.ORCID http://orcid.org/0000-0003-4072-6925
Weijie PanThe Key Laboratory of Advanced Manufacturing Technology of the Ministry of Education, Guizhou University, Guiyang, Guizhou, China. gzdxpwj@163.com.

Funding

Science and Technology Projects in Guizhou Province [2023]274
6 · The paper itself

Abstract

Contemporary digital work is increasingly shaped by frequent multitasking, which places sustained demands on directed attention. Restorative design theories propose that nature-related cues can support attention recovery, yet it remains unclear whether and how such effects translate to immersive virtual environments. In response to this study, virtual environments with and without nature-related wooden elements were constructed, and 54 subjects were recruited to complete cognitive tasks, eye movement experiments, and questionnaires. The experimental results showed that: (1) the response time of the wood group in the Stroop test was shortened by 15.3%, and the correctness rate of the OSPAN test was increased by 11.3%; the wood elements in the virtual environment could optimize the cognitive processing process, significantly shorten the response time of the cognitive task, and increase the accuracy of working memory. (2) Eye-movement data showed that the wood elements could improve the stability of attention and thus enhance the ability of sustained concentration. The findings of this study provide a reference for the selection of materials based on the principle of psychological recovery for the future design of digital office space.

Indexed as

AttentionEye MovementsEye-Tracking TechnologyVirtual RealityWoodAdultCognitionFemaleHumansMemory, Short-TermReaction TimeYoung AdultCognitive abilityEye movement testVirtual realityWood element

Identifiers

PMID41872313
PMCPMC13168668

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.