Evidence map›Paper›PMID 37794208›Full record

ArticleBehavior research methods2024

Immersive VR for investigating threat avoidance: The VRthreat toolkit for Unity.

Jack Brookes, Samson Hall, Sascha Frühholz, Dominik R Bach

Abstract read
In one paragraph

Article in Behavior research methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

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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

4 authors.

Jack BrookesMax Planck UCL Centre for Computational Psychiatry and Ageing Research and Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK.
Samson HallMax Planck UCL Centre for Computational Psychiatry and Ageing Research and Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK.
Sascha FrühholzCognitive and Affective Neuroscience Unit, University of Zurich, Zürich, Switzerland.
Dominik R BachMax Planck UCL Centre for Computational Psychiatry and Ageing Research and Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK. d.bach@uni-bonn.de.ORCID http://orcid.org/0000-0003-3717-2036

Funding

H2020 European Research Council ERC-2018 CoG-816564Wellcome TrustWellcome Trust 203147/Z/16/Z
6 · The paper itself

Abstract

All animals have to respond to immediate threats in order to survive. In non-human animals, a diversity of sophisticated behaviours has been observed, but research in humans is hampered by ethical considerations. Here, we present a novel immersive VR toolkit for the Unity engine that allows assessing threat-related behaviour in single, semi-interactive, and semi-realistic threat encounters. The toolkit contains a suite of fully modelled naturalistic environments, interactive objects, animated threats, and scripted systems. These are arranged together by the researcher as a means of creating an experimental manipulation, to form a series of independent "episodes" in immersive VR. Several specifically designed tools aid the design of these episodes, including a system to allow for pre-sequencing the movement plans of animal threats. Episodes can be built with the assets included in the toolkit, but also easily extended with custom scripts, threats, and environments if required. During the experiments, the software stores behavioural, movement, and eye tracking data. With this software, we aim to facilitate the use of immersive VR in human threat avoidance research and thus to close a gap in the understanding of human behaviour under threat.

Indexed as

Avoidance LearningVirtual RealityAnimalsFearHumansSoftwareUser-Computer InterfaceDecision-makingDefensive behaviourMotor controlResearch softwareThreat avoidanceVR

Identifiers

PMID37794208
PMCPMC11289213

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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.