Development of Embedded Performance Validity Indicators in the NIH Toolbox Cognitive Battery

To assess noncredible performance on the NIH Toolbox Cognitive Battery (NIHTB-CB), we developed embedded validity indicators (EVIs). Data were collected from 98 adults (54.1% female) as part of a prospective multicenter cross-sectional study at 4 mild traumatic brain injury (mTBI) specialty clinics. Traditional EVIs and novel item-based EVIs were developed for the NIHTB-CB using the Medical Symptom Validity Test (MSVT) as criterion. The signal detection profile of individual EVIs varied greatly. Multivariate models had superior classification accuracy. Failing >= 4 traditional EVIs at the liberal cutoff or >= 3 at the conservative cutoff produced a good combination of sensitivity (.57 to .61) and specificity (.92 to .94) to MSVT. Combining the traditional and item-based EVIs improved sensitivity (.65 to .70) at comparable specificity (.91 to .95). In conclusion, newly developed EVIs within the NIHTB-CB effectively discriminated between patients who passed versus failed the MSVT. Aggregating EVIs within the same category into validity composites improved signal detection over univariate cutoffs. Item-based EVIs improved classification accuracy over that of traditional EVIs. However, the marginal gains hardly justify the burden of extra calculations. The newly introduced EVIs require cross-validation before wide-spread research or clinical application. Public Significance Statement In this study, we developed the first embedded validity indices within the NIH Toolbox Cognitive Battery in a sample of people with a recent history of mild traumatic brain injury. Embedded validity indices provide information about performance validity, or the degree to which test scores reflect test-taker ability on cognitive tests.