Evidence map›Paper›PMID 42786376›Full record

ArticleBehavior research methods2026

Measuring the dynamics of attentional capture in hand and eye movements with virtual reality.

Max D Gurr, Jeff Moher, Matthew D Egbert, Christopher D Erb

Abstract read
In one paragraph

Article in Behavior research methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

4 authors.

Max D GurrSchool of Psychology, University of Auckland, 23 Symonds Street, Building 302, Auckland, 1010, New Zealand.
Jeff MoherDepartment of Psychology, Connecticut College, 270 Mohegan Avenue, New London, CT, 06320, USA.
Matthew D EgbertSchool of Computer Science, University of Auckland, 38 Princes Street, Building 303, Auckland, 1010, New Zealand.
Christopher D ErbSchool of Psychology, University of Auckland, 23 Symonds Street, Building 302, Auckland, 1010, New Zealand. christopher.erb@auckland.ac.nz.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Laboratory investigations of attentional capture typically use two-dimensional displays and button-press responses, which may limit their generalizability to everyday experiences. The current study used a virtual reality (VR) system to measure the dynamics of attentional capture by simultaneously recording participants' (N = 54) hand and eye movements as they completed a modified additional singleton task. In both a sparsely detailed and richly detailed virtual environment, participants reached to select a uniquely shaped target that was accompanied by a uniquely colored distractor on 50% of trials. We observed robust attentional capture costs across our measures of hand and eye movements, with greater latencies in initiation and movement times, larger reach curvatures, more overall eye movement, and delayed first target fixations on distractor-present trials. Three-dimensional target attraction and distractor attraction scores provided sensitive measures of the time course of attentional capture and allowed for more direct interpretations of performance than reach curvature. Although initiation times, response times, gaze distances, and target fixation proportions were elevated in the richly detailed environment relative to the sparsely detailed environment, we failed to observe a significant interaction between environmental detail and attentional capture costs in any of our measures. Taken together, our results demonstrate the feasibility of using VR to examine the dynamics of attentional capture in immersive virtual environments with richer, more continuous behavioral measures.

Indexed as

AttentionEye MovementsHandPsychomotor PerformanceVirtual RealityAdultFemaleHumansMaleReaction TimeYoung AdultAdditional singleton taskAttentional captureEye trackingHand trackingVirtual reality

Identifiers

PMID42786376
PMCPMC13612694

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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.