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内置于词语流畅性测试中的症状真实性指标。

Symptom validity indicators embedded in the Controlled Oral Word Association Test.

机构信息

Department of Psychology, University of British Columbia, Vancouver, BC, Canada.

出版信息

Clin Neuropsychol. 2012;26(7):1230-41. doi: 10.1080/13854046.2012.709886. Epub 2012 Aug 3.

Abstract

Embedded symptom validity measures facilitate the detection of below-capacity performance in neuropsychological assessment. A number of such indicators have been proposed for the Controlled Oral Word Association Test (COWAT), a widely used test of word generation. However, several of these embedded indicators have not been cross-validated and it is currently unclear which represent the optimal combination of predictors. This study used Bayesian Model Averaging (BMA) to determine the set of predictors that best differentiate between patients presenting with (n = 46) and without (n = 55) malingered neurocognitive dysfunction (MND). Mild traumatic brain injury was the most common diagnosis in the MND group (96%). BMA selected the COWAT total score and a measure of change in output over time. A logistic regression model combining these variables yielded good discriminability, with an AUC of. 774, (95% confidence interval = .679 to. 869), 78% of cases were classified correctly, with 67% sensitivity and 88% specificity. Two alternative models performed similarly, but the variables involved required slightly longer administration and/or calculation time, making them somewhat less desirable. These results support the use of a weighted combination of embedded symptom validity measures in the COWAT.

摘要

嵌入式症状有效性测量有助于在神经心理评估中发现能力不足的表现。已经为广泛使用的单词生成测试——连续词汇联想测验(COWAT)提出了许多这样的指标。然而,其中一些嵌入式指标尚未经过交叉验证,目前尚不清楚哪些指标是最佳的预测因子组合。本研究使用贝叶斯模型平均(BMA)来确定一组最佳预测因子,这些预测因子可区分表现出(n=46)和不表现出(n=55)伪装性神经认知功能障碍(MND)的患者。在 MND 组中,轻度创伤性脑损伤是最常见的诊断(96%)。BMA 选择了 COWAT 总分和随时间变化的输出测量。将这些变量结合起来的逻辑回归模型具有良好的判别能力,AUC 为 0.774(95%置信区间=0.679 至 0.869),78%的病例得到正确分类,敏感性为 67%,特异性为 88%。两种替代模型的性能相似,但涉及的变量需要稍长的管理和/或计算时间,因此不太理想。这些结果支持在 COWAT 中使用加权组合的嵌入式症状有效性测量。

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