Evidence map›Paper›PMID 33986337›Full record

ArticleScientific reports2021

Comparing physiological responses during cognitive tests in virtual environments vs. in identical real-world environments.

Saleh Kalantari, James D Rounds, Julia Kan, Vidushi Tripathi, Jesus G Cruz-Garza

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Designing for Wayfinding in VR: Linking Navigation Interfaces to Spatial Learning and Cognitive Mapping.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2026
    Article
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  6. Low Vision Assessment in Virtual Reality (LVAVR): Spatial Computing in Virtual Reality and Real-World.2026 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops · 2026
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  17. Health risk assessment of PMScientific reports · 2021
    Observational
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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.

Saleh KalantariDepartment of Design and Environmental Analysis, College of Human Ecology, Cornell University, Ithaca, USA. sk3268@cornell.edu.ORCID 0000-0002-0472-5493
James D RoundsDepartment of Design and Environmental Analysis, College of Human Ecology, Cornell University, Ithaca, USA.ORCID 0000-0003-2142-1544
Julia KanDepartment of Design and Environmental Analysis, College of Human Ecology, Cornell University, Ithaca, USA.ORCID 0000-0002-3836-1675
Vidushi TripathiDepartment of Design and Environmental Analysis, College of Human Ecology, Cornell University, Ithaca, USA.ORCID 0000-0002-2777-8053
Jesus G Cruz-GarzaDepartment of Design and Environmental Analysis, College of Human Ecology, Cornell University, Ithaca, USA. jgc243@cornell.edu.ORCID 0000-0002-8440-6416

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immersive virtual environments (VEs) are increasingly used to evaluate human responses to design variables. VEs provide a tremendous capacity to isolate and readily adjust specific features of an architectural or product design. They also allow researchers to safely and effectively measure performance factors and physiological responses. However, the success of this form of design-testing depends on the generalizability of response measurements between VEs and real-world contexts. At the current time, there is very limited research evaluating the consistency of human response data across identical real and virtual environments. Rendering tools were used to precisely replicate a real-world classroom in virtual space. Participants were recruited and asked to complete a series of cognitive tests in the real classroom and in the virtual classroom. Physiological data were collected during these tests, including electroencephalography (EEG), electrocardiography (ECG), electrooculography (EOG), galvanic skin response (GSR), and head acceleration. Participants' accuracy on the cognitive tests did not significantly differ between the real classroom and the identical VE. However, the participants answered the tests more rapidly in the VE. No significant differences were found in eye blink rate and heart rate between the real and VR settings. Head acceleration and GSR variance were lower in the VE setting. Overall, EEG frequency band-power was not significantly altered between the real-world classroom and the VE. Analysis of EEG event-related potentials likewise indicated strong similarity between the real-world classroom and the VE, with a single exception related to executive functioning in a color-mismatch task.

Indexed as

Virtual RealityAcademic PerformanceAdolescentAdultCognitionElectroencephalographyElectrooculographyEnvironmentEvoked PotentialsFemaleGalvanic Skin ResponseHumansMaleMiddle AgedNeuropsychological TestsUser-Computer Interface

Identifiers

PMID33986337
PMCPMC8119471

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.