University of Illinois at Chicago, USA.
California State University, Long Beach, USA.
Hum Factors. 2019 May;61(3):393-414. doi: 10.1177/0018720819830553. Epub 2019 Mar 1.
We aimed to provide an assessment of the impact of workload manipulations on various cardiac measurements. We further sought to determine the most effective measurement approaches of cognitive workload as well as quantify the conditions under which these measures are most effective for interpretation.
Cognitive workload affects human performance, particularly when load is relatively high (overload) or low (underload). Despite ongoing interest in assessing cognitive workload through cardiac measures, it is currently unclear which cardiac-based assessments best indicate cognitive workload. Although several quantitative studies and qualitative reviews have sought to provide guidance, no meta-analytic integration of cardiac assessment(s) of cognitive workload exists to date.
We used Morris and DeShon's meta-analytic procedures to quantify the changes in cardiac measures due to task load conditions.
Sample-weighted Cohen's d values suggest that several metrics of cardiac activity demonstrate sensitivity in response to cognitive workload manipulations. Heart rate variability measures show sensitivity to task load, conditions of event rate, and task duration. Authors of future work should seek to quantify the utility of leveraging multiple metrics to understand workload.
Results suggest that assessment of cognitive workload can be done using various cardiac activity indicators. Further, given the number of valid and reliable measures available, researchers and practitioners should base their selection of a psychophysiological measure on the experimental and practical concerns inherent to their task/protocol.
Findings bear implications for future assessment of cognitive workload within basic and applied settings. Future research should seek to validate conditions under which measurements are best interpreted, including but not limited to individual differences.
我们旨在评估工作量操作对各种心脏测量的影响。我们还试图确定认知工作量的最有效测量方法，并量化这些措施在哪些情况下最有效进行解释。
认知工作量会影响人类的表现，尤其是在负荷相对较高（过载）或较低（欠载）时。尽管人们一直有兴趣通过心脏测量来评估认知工作量，但目前尚不清楚哪些基于心脏的评估最能指示认知工作量。尽管已经有几项定量研究和定性综述试图提供指导，但迄今为止，还没有关于心脏评估认知工作量的元分析综合。
我们使用 Morris 和 DeShon 的元分析程序来量化由于任务负荷条件而导致的心脏测量变化。
样本加权 Cohen 的 d 值表明，几种心脏活动指标对认知工作量操作具有敏感性。心率变异性指标对任务负荷、事件率条件和任务持续时间敏感。未来的工作作者应寻求量化利用多种指标来理解工作量的效用。
结果表明，可以使用各种心脏活动指标来评估认知工作量。此外，鉴于有许多有效且可靠的测量方法可用，研究人员和从业人员应根据其任务/协议固有的实验和实际问题来选择心理生理测量方法。
研究结果对未来在基础和应用环境中评估认知工作量具有重要意义。未来的研究应该寻求验证测量结果最佳解释的条件，包括但不限于个体差异。
