Pak Richard, McLaughlin Anne Collins, Engle Randall
Department of Psychology, Clemson University, Clemson, SC, USA.
Hum Factors. 2024 May;66(5):1321-1332. doi: 10.1177/00187208231159727. Epub 2023 Feb 28.
Discuss the human factors relevance of attention control (AC), a domain-general ability to regulate information processing functions in the service of goal-directed behavior.
Working memory (WM) measures appear as predictors in various applied psychology studies. However, measures of WM reflect a mixture of memory storage and controlled attention making it difficult to interpret the meaning of significant WM-task relations for human factors. In light of new research, complex task performance may be better predicted or explained with new measures of attention control rather than WM.
We briefly review the topic of individual differences in abilities in Human Factors. Next, we focus on WM, how it is measured, and what can be inferred from significant WM-task relations.
The theoretical underpinnings of attention control as a high-level factor that affects complex thought and behavior make it useful in human factors, which often study performance in complex and dynamic task environments. To facilitate research on attention control in applied settings, we discuss a validated measure of attention control that predicts more variance in complex task performance than WM. In contrast to existing measures of WM or AC, our measures of attention control only require 3 minutes each (10 minutes total) and may be less culture-bound making them suitable for use in applied settings.
Explaining or predicting task performance relations with attention control rather than WM may have dramatically different implications for designing more specific, equitable task interfaces, or training.
A highly efficient ability predictor can help researchers and practitioners better understand task requirements for human factors interventions or performance prediction.
探讨注意力控制（AC）的人为因素相关性，AC是一种通用能力，用于调节信息处理功能以服务于目标导向行为。
工作记忆（WM）测量在各种应用心理学研究中表现为预测指标。然而，WM测量反映了记忆存储和控制性注意力的混合，这使得难以解释WM任务显著关系对人为因素的意义。鉴于新的研究，用注意力控制的新测量方法而非WM可能能更好地预测或解释复杂任务表现。
我们简要回顾人为因素中能力个体差异的主题。接下来，我们聚焦于WM，它如何被测量，以及从显著的WM任务关系中可以推断出什么。
注意力控制作为影响复杂思维和行为的高级因素的理论基础使其在人为因素中有用，人为因素经常研究复杂和动态任务环境中的表现。为便于在应用环境中研究注意力控制，我们讨论一种经过验证的注意力控制测量方法，它比WM能预测更多复杂任务表现的方差。与现有的WM或AC测量方法不同，我们的注意力控制测量方法每项仅需3分钟（总共10分钟），且可能受文化约束较小，使其适用于应用环境。
用注意力控制而非WM来解释或预测任务表现关系可能对设计更具体、公平的任务界面或培训有截然不同的意义。
一种高效的能力预测指标可帮助研究人员和从业者更好地理解人为因素干预或表现预测的任务要求。
