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Objective Research regarding performance validity tests (PVTs) in patients with multiple sclerosis (MS) is scant, with recommended batteries for neuropsychological evaluations in this population lacking suggestions to include PVTs. Moreover, limited work has examined embedded PVTs in this population. As previous investigations indicated that nonmemory-based embedded PVTs provide clinical utility in other populations, this study sought to determine if a logistic regression-derived PVT formula can be identified from selected nonmemory variables in a sample of patients with MS. Method A total of 184 patients (M age = 48.45; 76.6% female) with MS were referred for neuropsychological assessment at a large, Midwestern academic medical center. Patients were placed into “credible” (n = 146) or “noncredible” (n = 38) groups according to performance on standalone PVT. Missing data were imputed with HOTDECK. Results Classification statistics for a variety of embedded PVTs were examined, with none appearing psychometrically appropriate in isolation (areas under the curve [AUCs] = .48–.64). Four exponentiated equations were created via logistic regression. Six, five, and three predictor equations yielded acceptable discriminability (AUC = .71–.74) with modest sensitivity (.34–.39) while maintaining good specificity (≥.90). The two predictor equation appeared unacceptable (AUC = .67). Conclusions Results suggest that multivariate combinations of embedded PVTs may provide some clinical utility while minimizing test burden in determining performance validity in patients with MS. Nonetheless, the authors recommend routine inclusion of several PVTs and utilization of comprehensive clinical judgment to maximize signal detection of noncredible performance and avoid incorrect conclusions. Clinical implications, limitations, and avenues for future research are discussed.
Objective Research regarding performance validity tests (PVTs) in patients with multiple sclerosis (MS) is scant, with recommended batteries for neuropsychological evaluations in this population lacking suggestions to include PVTs. Moreover, limited work has examined embedded PVTs in this population. As previous investigations indicated that nonmemory-based embedded PVTs provide clinical utility in other populations, this study sought to determine if a logistic regression-derived PVT formula can be identified from selected nonmemory variables in a sample of patients with MS. Method A total of 184 patients (M age = 48.45; 76.6% female) with MS were referred for neuropsychological assessment at a large, Midwestern academic medical center. Patients were placed into “credible” (n = 146) or “noncredible” (n = 38) groups according to performance on standalone PVT. Missing data were imputed with HOTDECK. Results Classification statistics for a variety of embedded PVTs were examined, with none appearing psychometrically appropriate in isolation (areas under the curve [AUCs] = .48–.64). Four exponentiated equations were created via logistic regression. Six, five, and three predictor equations yielded acceptable discriminability (AUC = .71–.74) with modest sensitivity (.34–.39) while maintaining good specificity (≥.90). The two predictor equation appeared unacceptable (AUC = .67). Conclusions Results suggest that multivariate combinations of embedded PVTs may provide some clinical utility while minimizing test burden in determining performance validity in patients with MS. Nonetheless, the authors recommend routine inclusion of several PVTs and utilization of comprehensive clinical judgment to maximize signal detection of noncredible performance and avoid incorrect conclusions. Clinical implications, limitations, and avenues for future research are discussed.
Objective It is essential to interpret performance validity tests (PVTs) that are well-established and have strong psychometrics. This study evaluated the Child and Adolescent Memory Profile (ChAMP) Validity Indicator (VI) using a pediatric sample with traumatic brain injury (TBI). Method A cross-sectional sample of N = 110 youth (mean age = 15.1 years, standard deviation [SD] = 2.4 range = 8–18) on average 32.7 weeks (SD = 40.9) post TBI (71.8% mild/concussion; 3.6% complicated mild; 24.6% moderate-to-severe) were administered the ChAMP and two stand-alone PVTs. Criterion for valid performance was scores above cutoffs on both PVTs; criterion for invalid performance was scores below cutoffs on both PVTs. Classification statistics were used to evaluate the existing ChAMP VI and establish a new VI cutoff score if needed. Results There were no significant differences in demographics or time since injury between those deemed valid (n = 96) or invalid (n = 14), but all ChAMP scores were significantly lower in those deemed invalid. The original ChAMP VI cutoff score was highly specific (no false positives) but also highly insensitive (sensitivity [SN] = .07, specificity [SP] = 1.0). Based on area under the curve (AUC) analysis (0.94), a new cutoff score was established using the sum of scaled scores (VI-SS). A ChAMP VI-SS score of 32 or lower achieved strong SN (86%) and SP (92%). Using a 15% base rate, positive predictive value was 64% and negative predictive value was 97%. Conclusions The originally proposed ChAMP VI has insufficient SN in pediatric TBI. However, this study yields a promising new ChAMP VI-SS, with classification metrics that exceed any other current embedded PVT in pediatrics.
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