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Related Experiment Video

Updated: Oct 22, 2025

The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool

The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool

Published on: June 30, 2014

Nonmemory Composite Embedded Performance Validity Formulas in Patients with Multiple Sclerosis.

John W Lace¹, Zachary C Merz², Rachel Galioto^1,3

¹Section of Neuropsychology, P57, Cleveland Clinic, Cleveland, OH, USA.

Archives of Clinical Neuropsychology : the Official Journal of the National Academy of Neuropsychologists

|September 1, 2021

Summary

This summary is machine-generated.

This study explored performance validity tests (PVTs) for multiple sclerosis (MS) patients, finding that combining embedded PVTs can help identify noncredible performance. This approach aids in accurate neuropsychological assessments for individuals with MS.

Keywords:

Effort Embedded PVTs Multiple sclerosis Neuropsychological assessment Performance validity

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Published on: October 13, 2016

Area of Science:

Neuropsychology
Clinical Psychology
Neurology

Background:

Limited research exists on performance validity tests (PVTs) for multiple sclerosis (MS) patients.
Current neuropsychological evaluation batteries for MS do not typically recommend PVTs.
Previous studies suggest embedded PVTs are useful in other patient populations.

Purpose of the Study:

To determine if a logistic regression-derived PVT formula can be identified from nonmemory-based embedded variables in MS patients.
To assess the clinical utility of embedded PVTs in distinguishing credible from noncredible performance in MS.
To develop a more efficient method for assessing performance validity in MS evaluations.

Main Methods:

184 patients with MS underwent neuropsychological assessment.
Patients were classified as "credible" (n=146) or "noncredible" (n=38) based on standalone PVT performance.
Logistic regression was used to create predictive equations from embedded PVT variables.

Main Results:

Individual embedded PVTs showed poor psychometric properties (AUCs = .48-.64).
Multivariate logistic regression equations with 3, 5, or 6 predictors demonstrated acceptable discriminability (AUC = .71-.74).
These models achieved good specificity (≥.90) but modest sensitivity (.34-.39).

Conclusions:

Multivariate combinations of embedded PVTs may offer clinical utility for assessing performance validity in MS patients.
Integrating multiple embedded PVTs can minimize test burden while improving detection of noncredible performance.
Routine inclusion of several PVTs and comprehensive clinical judgment are recommended for accurate assessment in MS.