Detecting memory performance validity with DETECTS: A computerized performance validity test

Multivariable utility of the Memory Integrated Language and Making Change Test

Recent reports indicate that the Memory Integrated Language Test (MIL) and Making Change Test Abbreviated Index (MCT-AI), two web-based performance validity tests (PVTs), have good sensitivity and specificity when used independently. This study investigated whether using these PVTs together could improve the detection of invalid performance in a mixed neuropsychiatric sample. Participants were 129 adult outpatients who underwent a neuropsychological evaluation and were classified into valid (n = 104) or invalid (n = 25) performance groups based on several commonly used PVTs. Using cut scores of ≤41 on the MIL and ≥1.05 on the MCT-AI together enhanced classification accuracy, yielding an area under the curve of .84 (95% CI: .75, .93). As compared to using the MIL and MCT-AI independently, the combined use increased the sensitivity from .10-.31 to.70 while maintaining ≥.90 specificity. Findings also indicated that failing either the MIL or MCT-AI was associated with somewhat lower cognitive test scores, but failing both was associated with markedly lower scores. Overall, using the MIL and MCT-AI together may be an effective way to identify invalid test performance during a neuropsychological evaluation. Furthermore, pairing these tests is consistent with current practice guidelines to include multiple PVTs in a neuropsychological test battery.

Development and Initial Validation of the Perceptual Assessment of Memory (PASSOM): A Simulator Study

OBJECTIVE

Performance validity tests (PVTs) are an integral component of neuropsychological assessment. There is a need for the development of more PVTs, especially those employing covert determinations. The aim of the present study was to provide initial validation of a new computerized PVT, the Perceptual Assessment of Memory (PASSOM).

METHOD

Participants were 58 undergraduate students randomly assigned to a simulator (SIM) or control (CON) group. All participants were provided written instructions for their role prior to testing and were administered the PASSOM as part of a brief battery of neurocognitive tests. Indices of interest included response accuracy for Trials 1 and 2, and total errors across Trials, as well as response time (RT) for Trials 1 and 2, and total RT for both Trials.

RESULTS

The SIM group produced significantly more errors than the CON group for Trials 1 and 2, and committed more total errors across trials. Significantly longer response latencies were found for the SIM group compared to the CON group for all RT indices examined. Linear regression modeling indicated excellent group classification for all indices studied, with areas under the curve ranging from 0.92 to 0.95. Sensitivity and specificity rates were good for several cut scores across all of the accuracy and RT indices, and sensitivity improved greatly by combining RT cut scores with the more traditional accuracy cut scores.

CONCLUSION

Findings demonstrate the ability of the PASSOM to distinguish individuals instructed to feign cognitive impairment from those told to perform to the best of their ability.