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Citation
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Whiteside DM, Gaasedelen OJ, Hahn-Ketter AE, Luu H, Miller ML, Persinger V, Rice L, Basso MR. Clin. Neuropsychol. 2015; 29(6): 788-803. |
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Affiliation
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g Department of Psychology , University of Tulsa , Tulsa , IL , USA. |
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Abstract
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OBJECTIVE: Performance validity assessment is increasingly considered standard practice in neuropsychological evaluations. The current study extended research on logistically derived performance validity tests (PVTs) by utilizing neuropsychological measures from multiple cognitive domains instead of from a single measure or a single cognitive domain.
METHOD: A logistic-derived PVT was calculated using several measures from multiple cognitive domains, including verbal memory (California Verbal Learning Test-II Trial 5, Total Hits, and False Positives), attention (Brief Test of Attention Total score), and language (Boston Naming Test T-score, and Animal Fluency T-score). Due to its cross-domain nature, the cross-domain logistic-derived embedded PVT was hypothesized to have excellent classification accuracy for non-credible performance. Participants included 224 patients who completed all measures and were moderate to severe traumatic brain injury (STBI) patients (N = 66), possible mild TBI (MTBI-FAIL) patients who failed at least 2 independent PVTs (N = 67), and possible mild TBI patients who passed all PVTs (MTBI-PASS; N = 91). Logistic regression and ROC analyses were conducted on the MTBI-FAIL group and the STBI group.
RESULTS: Multivariate analysis of variance indicated that the MTBI-FAIL group was significantly lower on all measures than the MTBI-PASS and the STBI groups. Using logistic regression, CVLT Total Hits, BTA, and the CVLT False Positives best differentiated between the MTBI-FAIL and STBI groups. The logistically derived PVT had excellent classification accuracy (area under the curve [AUC] = .84), with sensitivity at.54 when specificity was set at.90, higher than any individual variable.
CONCLUSIONS: Findings support the use of this logistical-derived variable as an embedded PVT and support further research with this type of methodology.
Language: en |