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Reference values and subscale patterns for the task load index (TLX): a meta-analytic review.

Morten Hertzum¹

¹Department of Communication, University of Copenhagen, Copenhagen, Denmark.

|January 19, 2021

Summary

This study provides benchmark Task Load Index (TLX) values from 556 studies. These reference values help practitioners assess workload across different domains, technologies, and settings.

Keywords:

Mental workload NASA-TLX TLX task load index workload

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Area of Science:

Human Factors and Ergonomics
Psychology
Occupational Health

Background:

The Task Load Index (TLX) is a widely used self-report measure for assessing subjective workload.
Establishing normative data is crucial for interpreting TLX scores effectively.
Previous research has not synthesized TLX data across diverse contexts.

Purpose of the Study:

To provide reference values for the Task Load Index (TLX) and its subscales based on a large meta-analytic review.
To identify factors influencing TLX scores, including application domains, technologies, geographical regions, and study settings.
To enhance the diagnostic utility of the TLX instrument for practitioners.

Main Methods:

A meta-analytic review was conducted on 556 studies utilizing the Task Load Index (TLX).
TLX scores and subscale values were analyzed across various application domains, technologies, regions, and settings (real-life vs. lab).
Statistical analysis was performed to identify patterns and influencing factors on TLX scores.

Main Results:

Mean TLX scores varied significantly across domains, ranging from 35 (leisure) to 56 (manual labor).
Mental demand and effort subscales generally drove higher TLX scores, while physical demand and frustration contributed less.
Handheld devices were associated with lower TLX, and scores were higher in Asia compared to Europe and North America. TLX scores were also higher in real-life settings.

Conclusions:

The study provides valuable reference values for benchmarking TLX measurements in practice.
Understanding the patterns of TLX subscales across different contexts improves the diagnostic power of the instrument.
These findings offer a robust basis for interpreting workload assessments in diverse human-computer interaction and occupational settings.