Department of Neuroscience, University of Padova, 35121, Padova, Italy.
Padova Neuroscience Center, University of Padova, Padova, Italy.
Behav Res Methods. 2024 Feb;56(2):934-951. doi: 10.3758/s13428-023-02091-8. Epub 2023 Mar 9.
The spatial Stroop task measures the ability to resolve interference between relevant and irrelevant spatial information. We recently proposed a four-choice spatial Stroop task that ensures methodological advantages over the original color-word verbal Stroop task, requiring participants to indicate the direction of an arrow while ignoring its position in one of the screen corners. However, its peripheral spatial arrangement might represent a methodological weakness and could introduce experimental confounds. Thus, aiming at improving our "Peripheral" spatial Stroop, we designed and made available five novel spatial Stroop tasks (Perifoveal, Navon, Figure-Ground, Flanker, and Saliency), wherein the stimuli appeared at the center of the screen. In a within-subjects online study, we compared the six versions to identify which task produced the largest but also the most reliable and robust Stroop effect. Indeed, although internal reliability is frequently overlooked, its estimate is fundamental, also in light of the recently proposed reliability paradox. Data analyses were performed using both the classical general linear model analytical approach and two multilevel modelling approaches (linear mixed models and random coefficient analysis), which specifically served for more accurately estimating the Stroop effect by explaining intra-subject, trial-by-trial variability. We then assessed our results based on their robustness to such analytic flexibility. Overall, our results indicate that the Perifoveal spatial Stroop is the best alternative task for its statistical properties and methodological advantages. Interestingly, our results also indicate that the Peripheral and Perifoveal Stroop effects were not only the largest, but also those with highest and most robust internal reliability.
空间斯特鲁普任务测量了在相关和不相关的空间信息之间进行干扰的能力。我们最近提出了一个四选一的空间斯特鲁普任务，与原始的颜色-单词言语斯特鲁普任务相比，该任务具有方法学上的优势，要求参与者在忽略箭头位置的情况下，指示箭头的方向。然而，其外围的空间排列可能代表了一种方法学上的弱点，并可能引入实验混淆。因此，为了改进我们的“周边”空间斯特鲁普任务，我们设计并提供了五个新的空间斯特鲁普任务（周边、纳冯、图形-背景、侧翼和显著性），其中刺激出现在屏幕中央。在一项在线的被试内研究中，我们比较了这六种版本，以确定哪种任务产生的斯特鲁普效应最大，但也最可靠和稳健。事实上，尽管内部可靠性经常被忽视，但它的估计是至关重要的，特别是考虑到最近提出的可靠性悖论。数据分析使用了经典的一般线性模型分析方法和两种多层次建模方法（线性混合模型和随机系数分析），这些方法专门用于通过解释被试内、试验间的变异性，更准确地估计斯特鲁普效应。然后，我们根据其对这种分析灵活性的稳健性来评估我们的结果。总的来说，我们的结果表明，周边空间斯特鲁普任务是一种具有统计学性质和方法学优势的最佳替代任务。有趣的是，我们的结果还表明，周边和周边空间斯特鲁普效应不仅是最大的，而且是具有最高和最稳健的内部可靠性的效应。
