Adaptive Neural Systems Group, Institute for Integrative and Innovative Research, University of Arkansas, Fayetteville, Arkansas, USA.
Computational Neuropsychology and Simulation (CNS) Lab, Arizona State University, Tempe, Arizona, USA.
J Clin Exp Neuropsychol. 2022 Oct;44(8):604-617. doi: 10.1080/13803395.2022.2150749. Epub 2022 Nov 29.
Virtual reality (VR) offers neuropsychologists high dimensional (3D) platforms for administering cognitive tasks that balance experimental control with simulations of naturalistic activities. A virtual reality version of the Stroop task, the Virtual Reality Stroop Task (VRST), was developed that leverages technological advances to enhance the ecological validity of neuropsychological assessments. The high mobility multipurpose wheeled vehicle (HMMWV) version of the VRST includes high arousal (ambush) and low arousal (safe) zones was employed in this study. This version of the VRST contains both cognitive (Stroop) and affective (arousal) components. While the VRST has been shown to have good construct validity, the factor structure has yet to be explored. This study aimed to examine the factor structure of the VRST and compare the results with a lower dimensional (2D) computer-automated Stroop task (i.e., the Automated Neuropsychological Assessment Metrics - ANAM).
Data was drawn from college-aged students who completed the VRST and ANAM Stroop tasks (N = 115). Factor analyses utilized principal axis factoring (PAF), and output variables included percent of correct responses and response times the VRST and ANAM Stroop tasks.
Results indicated that both Stroop tasks had two-factor solutions. Factor one measured response times and factor two measured accuracy. While factors respective of speed and accuracy factors were correlated across assessment modalities, within assessment factor correlations were low.
The factors possibly indicated participants response styles in that they either focus on responding accurately or responding quickly to stimuli. Therefore, including throughput in future research examining either the ANAM Stroop task or VRST may provide useful insight into participant performance. Finally, because similar factor structures were observed for both the VRST and ANAM Stroop task this study provided additional support for the construct validity of a higher dimensional Stroop task, the VRST.
虚拟现实(VR)为神经心理学家提供了高维(3D)平台,用于管理认知任务,在实验控制与自然活动模拟之间取得平衡。本研究开发了一种虚拟现实版的 Stroop 任务,即虚拟现实 Stroop 任务(VRST),该任务利用技术进步提高了神经心理学评估的生态有效性。高机动性多用途轮式车辆(HMMWV)版的 VRST 包括高唤醒(伏击)和低唤醒(安全)区域。该版本的 VRST 包含认知(Stroop)和情感(唤醒)成分。虽然 VRST 已被证明具有良好的结构效度,但尚未探讨其因子结构。本研究旨在检验 VRST 的因子结构,并将结果与低维(2D)计算机自动化 Stroop 任务(即自动神经心理评估指标 - ANAM)进行比较。
从完成 VRST 和 ANAM Stroop 任务的大学生中抽取数据(N=115)。因子分析采用主成分因子分析(PAF),输出变量包括 VRST 和 ANAM Stroop 任务的正确反应百分比和反应时间。
结果表明,两个 Stroop 任务都有两个因子解。第一个因子测量反应时间,第二个因子测量准确性。虽然评估模式之间的速度和准确性因子相关,但评估内因子相关性较低。
这些因素可能表明参与者的反应方式,即他们要么专注于准确反应,要么快速反应刺激。因此,在未来研究中,包括吞吐量可以为评估参与者表现提供有用的见解。最后,由于 VRST 和 ANAM Stroop 任务都观察到了相似的因子结构,本研究为更高维 Stroop 任务,即 VRST 的结构效度提供了额外的支持。