J. Lace, A. Grant, P. Ruppert, D. Kaufman, Carson L. Teague, Kimberly T. Lowell, J. Gfeller
{"title":"Detecting noncredible performance with the neuropsychological assessment battery, screening module: A simulation study","authors":"J. Lace, A. Grant, P. Ruppert, D. Kaufman, Carson L. Teague, Kimberly T. Lowell, J. Gfeller","doi":"10.1080/13854046.2019.1694703","DOIUrl":null,"url":null,"abstract":"Abstract Objective While the Neuropsychological Assessment Battery, Screening Module (S-NAB) is a commonly used cognitive screening measure, no composite embedded performance validity test (PVT) formula has yet been described within it. This study sought to empirically derive PVT formulas within the S-NAB using an analog simulation paradigm. Method Seventy-two university students (M age = 18.92) were randomly assigned to either an Asymptomatic (AS) or simulated mild traumatic brain injury (S-mTBI) group and were administered a neuropsychological test battery that included the S-NAB and standalone and embedded PVTs. The AS group was instructed to perform optimally, and the S-mTBI group received symptom and test coaching to help simulate mTBI-related impairment. Both groups received warnings regarding the presence of PVTs throughout the test battery. Results Groups showed significant differences (all ps < .001) on all S-NAB domain scores and PVTs. In the S-NAB, the Attention (S-ATT) and Executive Function (S-EXE) domains showed the largest effect sizes (Cohen’s ds = 2.02 and 1.79, respectively). Seven raw scores from S-ATT and S-EXE subtests were entered as predictor variables in a direct logistic regression (LR). The model accurately classified 90.3% of cases. Two PVT formulas were described: (1) an exponentiated equation from LR results and (2) an arithmetic formula using four individually meaningful variables. Both formulas demonstrated outstanding discriminability between groups (AUCs = .96–.97) and yielded good classification statistics compared to other PVTs. Conclusions This study is the first to describe composite, embedded PVT formulas within the S-NAB. Implications, limitations, and appropriate future directions of inquiry are discussed.","PeriodicalId":197334,"journal":{"name":"The Clinical neuropsychologist","volume":"128 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Clinical neuropsychologist","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/13854046.2019.1694703","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
Abstract Objective While the Neuropsychological Assessment Battery, Screening Module (S-NAB) is a commonly used cognitive screening measure, no composite embedded performance validity test (PVT) formula has yet been described within it. This study sought to empirically derive PVT formulas within the S-NAB using an analog simulation paradigm. Method Seventy-two university students (M age = 18.92) were randomly assigned to either an Asymptomatic (AS) or simulated mild traumatic brain injury (S-mTBI) group and were administered a neuropsychological test battery that included the S-NAB and standalone and embedded PVTs. The AS group was instructed to perform optimally, and the S-mTBI group received symptom and test coaching to help simulate mTBI-related impairment. Both groups received warnings regarding the presence of PVTs throughout the test battery. Results Groups showed significant differences (all ps < .001) on all S-NAB domain scores and PVTs. In the S-NAB, the Attention (S-ATT) and Executive Function (S-EXE) domains showed the largest effect sizes (Cohen’s ds = 2.02 and 1.79, respectively). Seven raw scores from S-ATT and S-EXE subtests were entered as predictor variables in a direct logistic regression (LR). The model accurately classified 90.3% of cases. Two PVT formulas were described: (1) an exponentiated equation from LR results and (2) an arithmetic formula using four individually meaningful variables. Both formulas demonstrated outstanding discriminability between groups (AUCs = .96–.97) and yielded good classification statistics compared to other PVTs. Conclusions This study is the first to describe composite, embedded PVT formulas within the S-NAB. Implications, limitations, and appropriate future directions of inquiry are discussed.