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Updated: Mar 15, 2026
Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity
Published on: March 18, 2019
Assessment of Performance Validity Using Embedded Saccadic and Manual Indices on a Continuous Performance Test
David M Barry1, Mark L Ettenhofer1
1Department of Medical and Clinical Psychology, F. Edward Hebert School of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA.
Objective:
In addition to manual (i.e., "button press") metrics, oculomotor metrics demonstrate considerable promise as tools for detecting invalid responding in neurocognitive assessment. This study was conducted to evaluate saccadic and manual metrics from a computerized continuous performance test as embedded indices of performance validity.
Method:
Receiver operating characteristic analyses, logistic regressions, and ANOVAs were performed to evaluate saccadic and manual metrics in classification of healthy adults instructed to feign deficits ("Fake Bad" group; n = 24), healthy adults instructed to perform their best ("Best Effort" group; n = 26), and adults with a history of mild traumatic brain injury (TBI) who passed a series of validity indices ("mTBI-Pass" group; n = 19).
Results:
Several saccadic and manual metrics achieved outstanding classification accuracy between Fake Bad versus Best Effort and mTBI-Pass groups, including variability (consistency) of saccadic and manual response time (RT), saccadic commission errors, and manual omission errors. Very large effect sizes were obtained between Fake Bad and Best Effort groups (Cohen's d range: 1.89-2.90; r range: .75-.78) as well as between Fake Bad and mTBI-Pass groups (Cohen's d range: 1.32-2.21; r range: .69-.71). The Fake Bad group consistently had higher saccadic and manual RT variability, more saccadic commission errors, and more manual omission errors than the Best Effort and mTBI-Pass groups.
Conclusions:
These findings are the first to demonstrate that eye movements can be used to detect invalid responding in neurocognitive assessment. These results also provide compelling evidence that concurrently measured saccadic and manual metrics can detect invalid responding with high levels of sensitivity and specificity.
