Evidence map›Paper›PMID 31366058›Full record

SynthesisInternational journal of environmental research and public health2019

A Systematic Review of Physiological Measures of Mental Workload.

Da Tao, Haibo Tan, Hailiang Wang, Xu Zhang, Xingda Qu, Tingru Zhang

Abstract readSystematic Review
In one paragraph

Synthesis in International journal of environmental research and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
69citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

69 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  6. Detecting Feigned Pain Using an Eye-Tracker Integrated Numerical Pain Rating Scale (NPRS).Pain practice : the official journal of World Institute of Pain · 2025
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9 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Da TaoState Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment, China Nuclear Power Engineering Co., Ltd., Shenzhen 518172, China.
Haibo TanState Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment, China Nuclear Power Engineering Co., Ltd., Shenzhen 518172, China.
Hailiang WangInstitute of Human Factors and Ergonomics, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China.
Xu ZhangInstitute of Human Factors and Ergonomics, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China.
Xingda QuState Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment, China Nuclear Power Engineering Co., Ltd., Shenzhen 518172, China.ORCID 0000-0003-1764-0357
Tingru ZhangState Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment, China Nuclear Power Engineering Co., Ltd., Shenzhen 518172, China. zhangtr@szu.edu.cn.ORCID 0000-0003-2395-1864

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mental workload (MWL) can affect human performance and is considered critical in the design and evaluation of complex human-machine systems. While numerous physiological measures are used to assess MWL, there appears no consensus on their validity as effective agents of MWL. This study was conducted to provide a comprehensive understanding of the use of physiological measures of MWL and to synthesize empirical evidence on the validity of the measures to discriminate changes in MWL. A systematical literature search was conducted with four electronic databases for empirical studies measuring MWL with physiological measures. Ninety-one studies were included for analysis. We identified 78 physiological measures, which were distributed in cardiovascular, eye movement, electroencephalogram (EEG), respiration, electromyogram (EMG) and skin categories. Cardiovascular, eye movement and EEG measures were the most widely used across varied research domains, with 76%, 66%, and 71% of times reported a significant association with MWL, respectively. While most physiological measures were found to be able to discriminate changes in MWL, they were not universally valid in all task scenarios. The use of physiological measures and their validity for MWL assessment also varied across different research domains. Our study offers insights into the understanding and selection of appropriate physiological measures for MWL assessment in varied human-machine systems.

Indexed as

RespirationTask Performance and AnalysisWorkloadHeart RateHumansMaleYoung Adulthuman-machine systemmental workloadphysiological measuresystematic review

Identifiers

PMID31366058
PMCPMC6696017

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.