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Factor analysis of the virtual reality Stroop task.

Justin Asbee1,2, Kimberly Kelly3,4, Timothy McMahan5

  • 1Adaptive Neural Systems Group, Institute for Integrative and Innovative Research, University of Arkansas, Fayetteville, Arkansas, USA.

Journal of Clinical and Experimental Neuropsychology
|November 29, 2022
PubMed
Summary
This summary is machine-generated.

Virtual reality Stroop Task (VRST) and Automated Neuropsychological Assessment Metrics (ANAM) Stroop tasks show similar two-factor structures, measuring speed and accuracy. This supports the construct validity of VRST for neuropsychological assessments.

Keywords:
ANAMStroopVRSTfactor analysisvalidityvirtual reality

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Area of Science:

  • Neuropsychology
  • Cognitive Science
  • Human-Computer Interaction

Background:

  • Virtual reality (VR) offers advanced platforms for neuropsychological assessments, enhancing ecological validity.
  • The Virtual Reality Stroop Task (VRST) integrates cognitive and affective components within a 3D environment.
  • The factor structure of the VRST, a high-dimensional assessment tool, required exploration.

Purpose of the Study:

  • To examine the factor structure of the Virtual Reality Stroop Task (VRST).
  • To compare the factor structure of the VRST with a 2D computer-automated Stroop task (ANAM).
  • To provide further support for the construct validity of the VRST.

Main Methods:

  • Principal axis factoring (PAF) was used for analysis.
  • Data included correct response percentages and response times from 115 college-aged students.
  • Both VRST and ANAM Stroop tasks were administered.

Main Results:

  • Both VRST and ANAM Stroop tasks exhibited two-factor solutions.
  • Factor one consistently measured response times (speed).
  • Factor two consistently measured accuracy, with low within-assessment correlations but moderate across-modality correlations.

Conclusions:

  • The two-factor solutions suggest distinct participant response styles (speed vs. accuracy focus).
  • Similar factor structures across VRST and ANAM support the construct validity of the VRST.
  • Future research could incorporate throughput to gain deeper performance insights.