Abstract Objectives: The Automated Neuropsychological Assessment Metrics 4 TBI-MIL (ANAM4) is a computerized cognitive test often used in post-concussion assessments with U.S. service members (SMs). However, existing evidence remains mixed… Click to show full abstract
Abstract Objectives: The Automated Neuropsychological Assessment Metrics 4 TBI-MIL (ANAM4) is a computerized cognitive test often used in post-concussion assessments with U.S. service members (SMs). However, existing evidence remains mixed regarding ANAM4’s ability to identify cognitive issues following mild traumatic brain injury (mTBI). Studies typically examine ANAM4 using standardized scores and/ or comparisons to a baseline. A more fine-grained approach involves examining inconsistency within an individual’s performance (i.e., intraindividual variability). Methods: Data from 237 healthy control SMs and 105 SMs within seven days of mTBI who took the ANAM4 were included in analyses. Using each individual’s raw scores on a simple reaction time (RT) subtest (SRT1) that is repeated at the end of the battery (SRT2), we calculated mean raw RT and the intraindividual standard deviation (ISD) of trial-by-trial RT. Analyses investigated differences between groups in mean RT, RT variability (i.e., ISD), and change in ISD from SRT1 and SRT2. Results: Using regression residuals to control for demographic variables, analysis of variance, and pairwise comparisons revealed the control group had faster mean RT and smaller ISD compared to the mTBI group. Furthermore, the mTBI group had a significant increase in ISD from SRT1 to SRT2, with effect sizes exceeding the minimum practical effect for comparisons of ISD in SRT2 and change in ISD from SRT1 to SRT2. Conclusions: While inconsistencies in performance are often viewed as test error, the results suggest intraindividual cognitive variability may be more sensitive than traditional metrics in detecting changes in cognitive function after mTBI. Additionally, the findings highlight the utility of the ANAM4’s repeating a RT subtest at two points in the same session for exploring within-subject differences in performance variability. (JINS, 2018, 24, 156–162)
               
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