用神经心理评估电池检测不可信表现,筛选模块:模拟研究

J. Lace, A. Grant, P. Ruppert, D. Kaufman, Carson L. Teague, Kimberly T. Lowell, J. Gfeller
{"title":"用神经心理评估电池检测不可信表现,筛选模块:模拟研究","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":"{\"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}","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

摘要

摘要目的神经心理评估单元筛选模块(S-NAB)是一种常用的认知筛选方法,但目前尚未描述复合嵌入效能效度测试(PVT)公式。本研究试图使用模拟模拟范式在S-NAB中经验推导PVT公式。方法将72名年龄为18.92岁的大学生随机分为无症状(AS)组和模拟轻度创伤性脑损伤(S-mTBI)组,进行包括S-NAB和独立、嵌入式pvt在内的神经心理测试。AS组接受最佳表现指导,S-mTBI组接受症状和测试指导,以帮助模拟mtbi相关损伤。在整个测试过程中,两组人都收到了关于pvt存在的警告。结果各组S-NAB结构域评分和pvt均有显著性差异(p < 0.001)。在S-NAB中,注意力域(S-ATT)和执行功能域(S-EXE)的效应量最大(Cohen’s ds分别为2.02和1.79)。S-ATT和S-EXE子测试的七个原始分数作为直接逻辑回归(LR)的预测变量输入。该模型对90.3%的病例进行了准确分类。描述了两个PVT公式:(1)LR结果的指数方程和(2)使用四个独立有意义变量的算术公式。与其他pvt相比,这两个公式在组间表现出显著的区别性(auc = 0.96 - 0.97),并产生了良好的分类统计。本研究首次在S-NAB中描述了复合、嵌入的PVT配方。讨论了该研究的意义、局限性和未来适当的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detecting noncredible performance with the neuropsychological assessment battery, screening module: A simulation study
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信