Coll-Martín Tao, Román-Caballero Rafael, Martínez-Caballero María Del Rocío, Martín-Sánchez Paulina Del Carmen, Trujillo Laura, Cásedas Luis, Castellanos M Concepción, Hemmerich Klara, Manini Greta, Aguirre María Julieta, Botta Fabiano, Marotta Andrea, Martín-Arévalo Elisa, Luna Fernando G, Lupiáñez Juan
Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, 18071 Granada, Spain.
Department of Research Methods in Behavioral Sciences, University of Granada, 18071 Granada, Spain.
J Intell. 2023 Sep 8;11(9):181. doi: 10.3390/jintelligence11090181.
The Attentional Networks Test for Interactions and Vigilance-executive and arousal components (ANTI-Vea) is a computerized task of 32 min duration in the standard format. The task simultaneously assesses the main effects and interactions of the three attentional networks (i.e., phasic alertness, orienting, and executive control) and two dissociated components of vigilance with reasonable reliability (executive and arousal vigilance). We present this free and publicly accessible resource (ANTI-Vea-UGR; https://anti-vea.ugr.es/) developed to easily run, collect, and analyze data with the ANTI-Vea (or its subtasks measuring some attentional and/or vigilance components embedded in the ANTI-Vea). Available in six different languages, the platform allows for the adaptation of stimulus timing and procedure to facilitate data collection from different populations (e.g., clinical patients, children). Collected data can be freely downloaded and easily analyzed with the provided scripts and tools, including a Shiny app. We discuss previous evidence supporting that attention and vigilance components can be assessed in typical lab conditions as well as online and outside the laboratory. We hope this tutorial will help researchers interested in measuring attention and vigilance with a tool useful to collect data from large sample sizes and easy to use in applied contexts.
用于交互以及警觉-执行和唤醒成分的注意网络测试(ANTI-Vea)是一个标准格式的、时长为32分钟的计算机化任务。该任务同时评估三个注意网络(即相位警觉、定向和执行控制)的主效应和交互作用,以及两个具有合理可靠性的警觉分离成分(执行和唤醒警觉)。我们展示了这个免费且公开可用的资源(ANTI-Vea-UGR;https://anti-vea.ugr.es/),它旨在便于使用ANTI-Vea(或其测量ANTI-Vea中嵌入的一些注意和/或警觉成分的子任务)运行、收集和分析数据。该平台有六种不同语言版本,允许调整刺激时间和程序,以方便从不同人群(如临床患者、儿童)收集数据。收集到的数据可以免费下载,并使用提供的脚本和工具(包括一个Shiny应用程序)轻松进行分析。我们讨论了先前的证据,这些证据支持在典型的实验室条件下以及在线和实验室外评估注意和警觉成分。我们希望本教程能帮助那些有兴趣使用一种有助于从大样本中收集数据且易于在应用环境中使用的工具来测量注意和警觉的研究人员。
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