Derivation of embedded symptom validity indicators for the Brief Symptom Inventory-18.

IF 2.7 3区心理学 Q2 CLINICAL NEUROLOGY

Clinical Neuropsychologist Pub Date : 2025-09-03 DOI:10.1080/13854046.2025.2555587

Jeremy J Davis, Scott R Millis

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引用次数: 0

Abstract

Objective: Symptom validity assessment is an important component of the evaluation of psychological sequelae of traumatic brain injury (TBI). Many personality inventories have embedded symptom validity scales (SVTs). A growing body of research reports derivation of embedded SVTs in brief symptom and self-report measures. We sought to develop embedded SVT indicators based on the Brief Symptom Inventory-18 (BSI-18).

Method: This project involved secondary analysis of TRACK-TBI data obtained from the Federal Interagency Traumatic Brain Injury Research Informatics System repository. Participants (N = 1,694) sustained TBI (n = 1,515) and or non-head orthopedic injury (n = 179). Independent SVTs were used to identify TBI cases with questionable validity (QV). Two novel SVTs were examined: BSI-V, which was developed using Bayesian model averaging (BMA) to determine a subset of BSI-18 items that predict QV, and BSI GSI, which is a total score cutoff based on the BSI-18 Global Severity Index. Receiver operating characteristic (ROC) analysis was used to compare classification accuracy of BSI-V and BSI GSI.

Results: Four BSI-18 items were determined to be optimal predictors of QV. The BSI-V and BSI GSI both showed outstanding discrimination with area under the ROC curve (AUC) of .95. BSI-V (≥5) and BSI GSI (≥64 T) cutoffs showed 83% sensitivity and 90% specificity.

Conclusions: Findings provide preliminary evidence of novel embedded SVTs in the BSI-18 with comparable support for BSI-V and BSI GSI. These findings warrant independent cross-validation to provide additional evidence of classification accuracy and refine cutoffs prior to implementation in practice.

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简要症状清单中嵌入症状效度指标的推导-18。

目的：症状效度评价是创伤性脑损伤（TBI）心理后遗症评价的重要组成部分。许多人格量表都嵌入了症状效度量表（SVTs）。越来越多的研究报告了在简短的症状和自我报告测量中嵌入svt的推导。我们试图根据简要症状清单-18 （BSI-18）开发嵌入式SVT指标。方法：本项目涉及对来自联邦跨部门创伤性脑损伤研究信息系统存储库的TRACK-TBI数据进行二次分析。参与者（N = 1,694）持续TBI （N = 1,515）和/或非头部骨科损伤（N = 179）。独立svt用于识别有效性可疑的TBI病例。我们研究了两种新的svt: BSI- v，它是使用贝叶斯模型平均（BMA）开发的，用于确定预测QV的BSI-18项目子集；BSI GSI，它是基于BSI-18全球严重性指数的总分截止值。采用受试者工作特征（ROC）分析比较BSI- v和BSI- GSI的分类准确率。结果：4个BSI-18项目被确定为QV的最佳预测因子。BSI- v和BSI- GSI均具有显著的判别性，ROC曲线下面积（AUC）均为0.95。BSI- v（≥5）和BSI- GSI（≥64 T）的截止值敏感性为83%，特异性为90%。结论：研究结果提供了BSI-18中新型嵌入svt的初步证据，对BSI- v和BSI- GSI具有相当的支持。这些发现需要独立的交叉验证，以提供分类准确性的额外证据，并在实践中实施之前完善截止点。

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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来源期刊

Clinical Neuropsychologist 医学-临床神经学

CiteScore

8.40

自引率

12.80%

发文量

审稿时长

6-12 weeks

期刊介绍： The Clinical Neuropsychologist (TCN) serves as the premier forum for (1) state-of-the-art clinically-relevant scientific research, (2) in-depth professional discussions of matters germane to evidence-based practice, and (3) clinical case studies in neuropsychology. Of particular interest are papers that can make definitive statements about a given topic (thereby having implications for the standards of clinical practice) and those with the potential to expand today’s clinical frontiers. Research on all age groups, and on both clinical and normal populations, is considered.