Differentiating poor validity from probable impairment on the medical symptom validity test: a cross-validation study

Area of Science:

• Neuropsychology
• Cognitive Psychology
• Forensic Psychology

Background:

• Distinguishing poor effort or malingering from genuine cognitive impairment is crucial in neuropsychological evaluations.
• The Medical Symptom Validity Test (MSVT) is used to assess performance validity.
• Dunham and Denney developed an algorithm to interpret MSVT results.

Purpose of the Study:

• To evaluate the effectiveness of Dunham and Denney's algorithm in differentiating poor performance validity from genuine cognitive impairment.
• To assess the concordance of MSVT failure rates with other performance validity tests.

Main Methods:

• Two independent datasets from outpatient neuropsychological evaluations were analyzed (n=153 and n=641).
• Dunham and Denney's algorithm was tested using four different cutoff scores for MSVT failure.
• Concordance was assessed with the Test of Memory Malingering (TOMM) and a forced-choice measure of the California Verbal Learning Test (CVLT-FC).

Main Results:

• None of the tested MSVT cutoff scores (70%, 75%, 80%, 85%) successfully identified a poor validity group with aligned failure rates on other performance validity measures.
• Cognitive performance did not differ between participants classified as having probable impairment versus poor validity.

Conclusions:

• The tested algorithm by Dunham and Denney was not effective in distinguishing poor effort from genuine cognitive impairment.
• The advanced interpretation (AI) of the MSVT is recommended as the current gold standard for evaluating performance validity when clinical data is limited.
• Further research is needed to improve measures of effort in neuropsychological assessments.