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Open AccessJournal ArticleDOI

Psychometric Properties of NASA-TLX and Index of Cognitive Activity as Measures of Cognitive Workload in Older Adults.

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TLDR
It is concluded that ICA and NASA-TLX are reliable measures of cognitive workload in older adults, and the convergent validity of these measures against event-related potentials (ERPs) was investigated.
Abstract
Cognitive workload is increasingly recognized as an important determinant of performance in cognitive tests and daily life activities. Cognitive workload is a measure of physical and mental effort allocation to a task, which can be determined through self-report or physiological measures. However, the reliability and validity of these measures have not been established in older adults with a wide range of cognitive ability. The aim of this study was to establish the test-retest reliability of the National Aeronautics and Space Administration Task Load Index (NASA-TLX) and Index of Cognitive Activity (ICA), extracted from pupillary size. The convergent validity of these measures against event-related potentials (ERPs) was also investigated. A total of 38 individuals with scores on the Montreal Cognitive Assessment ranging between 17 and 30 completed a working memory test (n-back) with three levels of difficulty at baseline and at a two-week follow-up. The intraclass correlation coefficients (ICC) values of the NASA-TLX ranged between 0.71 and 0.81, demonstrating good to excellent reliability. The mean ICA scores showed fair to good reliability, with ICCs ranging between 0.56 and 0.73. The mean ICA and NASA-TLX scores showed significant and moderate correlations (Pearson's r ranging between 0.30 and 0.33) with the third positive peak of the ERP at the midline channels. We conclude that ICA and NASA-TLX are reliable measures of cognitive workload in older adults. Further research is needed in dissecting the subjective and objective constructs of cognitive workload.

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EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis.

TL;DR: EELAB as mentioned in this paper is a toolbox and graphic user interface for processing collections of single-trial and/or averaged EEG data of any number of channels, including EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), Independent Component Analysis (ICA) and time/frequency decomposition including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling.
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The Montreal Cognitive Assessment, MoCA: A Brief Screening Tool For Mild Cognitive Impairment

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Book ChapterDOI

Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research

TL;DR: In this article, the results of a multi-year research program to identify the factors associated with variations in subjective workload within and between different types of tasks are reviewed, including task-, behavior-, and subject-related correlates of subjective workload experiences.
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