Within-Person Score Distribution Measures as Performance Validity Indicators in Service Members and Veterans with and without History of Mild Traumatic Brain Injury.

IF 2.1
Jeremy J Davis
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Abstract

Objective: This study examined within-person score distribution measures (WPSD) as a performance validity indicator using the overall test battery mean (OTBM), within-battery standard deviation (SD-B), coefficient of variation (CV), number of abnormal scores (ABN), and several other measures. The primary aim was comparison of classification accuracy of various WPSD measures.

Method: The study involved secondary analysis of de-identified data originally collected in the Chronic Effects of Neurotrauma Consortium Study 1. Participants (N = 1431) were categorized into valid and questionable performance validity groups using independent performance validity tests (PVTs). Seven WPSD measures were calculated from norm-referenced T scores on 24 cognitive tests: OTBM, CV, SD-B, kurtosis, skew, range, and ABN (scores ≤35 T). Area under the receiver operating characteristic curve (AUC) values were compared across WPSD measures.

Results: Significant group differences were observed in OTBM, CV, and ABN. AUC comparison showed excellent classification accuracy for OTBM (AUC = 0.83) and ABN (AUC = 0.84), and acceptable accuracy for CV (AUC = 0.74). Minimum specificity (≥90%) was shown with cutoffs on OTBM (≤42 T; sensitivity = 56%), CV (≥0.265; sensitivity = 30%), and ABN (≥6; sensitivity = 55%). Slight adjustments were required to maintain specificity in racially and ethnically diverse sample subsets.

Conclusions: OTBM and ABN demonstrated strong potential for use as embedded PVTs with excellent classification accuracy. CV displayed lower classification accuracy with group differences primarily due to changes in mean performance rather than increased dispersion. Further development and cross-validation of WPSD-based PVTs is warranted in civilian samples.

在有和没有轻度创伤性脑损伤史的服役人员和退伍军人中作为绩效效度指标的人内得分分布测量。
目的:本研究采用整体测试电池均值(OTBM)、电池内标准差(SD-B)、变异系数(CV)、异常得分数(ABN)等多项指标,对人内得分分布测度(WPSD)作为效能效度指标进行检验。主要目的是比较各种WPSD方法的分类精度。方法:该研究涉及对最初收集于神经创伤慢性效应联合研究1的去识别数据的二次分析。采用独立效度测试(pvt)将参与者(N = 1431)分为有效效度组和可疑效度组。根据24项认知测试的标准参照T评分计算7项WPSD指标:OTBM、CV、SD-B、峰度、偏度、范围和ABN(评分≤35 T)。比较不同WPSD测量的受试者工作特征曲线下面积(AUC)值。结果:OTBM、CV、ABN组间差异有统计学意义。AUC比较显示,OTBM (AUC = 0.83)和ABN (AUC = 0.84)的分类准确率良好,CV (AUC = 0.74)的分类准确率尚可。在OTBM(≤42 T,灵敏度= 56%)、CV(≥0.265,灵敏度= 30%)和ABN(≥6,灵敏度= 55%)的截止点上显示出最低特异性(≥90%)。需要稍微调整以保持种族和民族多样化样本子集的特异性。结论:OTBM和ABN具有很强的应用潜力,可作为嵌入式pvt,具有优异的分类精度。CV表现出较低的分类准确度,主要是由于平均表现的变化,而不是分散度的增加。需要在民用样品中进一步开发和交叉验证基于wpsd的pvt。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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