University of Windsor, Canada.
University of Utah, USA.
Hum Factors. 2024 Dec;66(12):2561-2568. doi: 10.1177/00187208241228049. Epub 2024 Jan 21.
This article tackles the issue of correct data interpretation when using stimulus detection tasks for determining the operator's workload.
Stimulus detection tasks are a relative simple and inexpensive means of measuring the operator's state. While stimulus detection tasks may be better geared to measure conditions of high workload, adopting this approach for the assessment of low workload may be more problematic.
This mini-review details the use of common stimulus detection tasks and their contributions to the Human Factors practice. It also borrows from the conceptual framework of the inverted-U shape model to discuss the issue of data interpretation.
The evidence being discussed here highlights a clear limitation of stimulus detection task paradigms.
There is an inherent risk in using a unidimensional tool like stimulus detection tasks as the primary source of information for determining the operator's psychophysiological state.
Two recommendations are put forward to Human Factors researchers and practitioners dealing with the interpretation conundrum of dealing with stimulus detection tasks.
本文探讨了在使用刺激检测任务来确定操作人员的工作量时正确解读数据的问题。
刺激检测任务是一种相对简单且经济的测量操作人员状态的方法。虽然刺激检测任务可能更适合测量高工作量的情况,但将这种方法用于评估低工作量可能会更成问题。
本迷你综述详细介绍了常见刺激检测任务的使用及其对人因实践的贡献。它还借鉴了倒 U 形模型的概念框架来讨论数据解释问题。
这里讨论的证据突出了刺激检测任务范式的明显局限性。
使用像刺激检测任务这样的单一维度工具作为确定操作人员心理生理状态的主要信息源存在固有风险。
向处理刺激检测任务解释难题的人因研究人员和从业者提出了两项建议。