Measuring Subjective Workload: When Is One Scale Better Than Many?
通过四项独立研究的数据，比较了单变量量表与多变量量表在评估整体工作负荷时的效果，发现单变量评分对任务需求变化的敏感度至少不亚于多变量推导值。
The idea that mental workload should be treated as a multidimensional problem is well recognized. Yet the NASA Task Load Index and Subjective Workload Assessment Technique scales incorporate procedures for combining multidimensional judgments into scalar estimates of overall workload. In view of comparable or superior performance claimed for univariate scales, it is reasonable to ask whether the scaled values are good estimates of overall processing demands and whether workload values derived from multidimensional scales provide better estimates than do judgments made on a univariate scale. This paper examines these issues using data from four independent studies. The results support two conclusions. First, if a measure of the overall demand on human information-processing is required, then a univariate rating is expected to provide a measure that is at least as sensitive to manipulations of task demand as a derived estimate from multivariate data. Second, if a univariate workload rating is not available, a simple unweighted additive model provides an adequate method for combining factor ratings into an estimate of overall workload.