Associations among workload dimensions, performance, and situational characteristics: a meta-analytic review of the Task Load Index

Morten Hertzum

Behaviour and Information Technology, 2022, vol. 41, issue 16, 3506-3518

Abstract: Workload is an important explanatory variable in human–computer interaction and commonly measured with the Task Load Index (TLX). Thus, it is important to understand the qualities of TLX and its relations to other variables. By reviewing 384 papers that apply TLX, this study analyzes how differences in TLX and its six subscales are associated with one another and with differences in performance, user experience, and situational characteristics. Six findings stand out. First, the TLX subscales measure associated, but somewhat independent, dimensions of workload. Second, people compensate for demanding conditions by putting in more effort and, as a result, sometimes avoid a drop in performance. Third, differences in workload are associated with differences in error rate, task completion time, and user experience but the strength of association is merely slight to fair. Fourth, differences in opposite directions between workload and either error rate, task completion time, or user experience are few but occur for all TLX subscales. Fifth, differences in workload dimensions are more often associated with differences in tasks and contexts than users and systems. Sixth, the TLX subscales – not just the composite TLX score – are widely used for testing cross-system differences in workload.

Date: 2022
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DOI: 10.1080/0144929X.2021.2000642

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