Straub Clinic and Hospital, 888 South King Street, Honolulu, HI 96813, USA.
Clin Neuropsychol. 2011 Nov;25(8):1403-14. doi: 10.1080/13854046.2011.613854. Epub 2011 Oct 17.
Five validity scales derived from the Minnesota Multiphasic Personality Inventory-2 (MMPI-2), the Infrequency Scale (F), Infrequency-Psychopathology Scale (F[p]), Symptom Validity Scale (FBS), Henry-Heilbronner Index (HHI), and Response Bias Scale (RBS) were evaluated in 118 litigation patients (LPs) and 163 clinical patients (CPs). Varied statistical methods, including hierarchical logistic regression analyses, Receiver Operating Characteristic (ROC) curve, Area Under the Curve (AUC) values, and sensitivity/specificity analyses, showed that RBS performed better than the other four scales in identifying LPs. The regression analyses found RBS to be the most significant predictor of LP and CP group membership (p < .001). The effectiveness of RBS in identifying LPs, all of whom reported neuropsychological symptoms, was attributed to its development based on cognitive effort test scores.
五种效度量表源自明尼苏达多项人格测验-2(MMPI-2),包括不寻常量表(F)、不寻常-精神病理学量表(F[p])、症状效度量表(FBS)、亨利-赫尔布伦纳指数(HHI)和反应偏差量表(RBS),对 118 名诉讼患者(LP)和 163 名临床患者(CP)进行了评估。多种统计方法,包括层次逻辑回归分析、接收者操作特征(ROC)曲线、曲线下面积(AUC)值和敏感性/特异性分析,表明 RBS 在识别 LP 方面优于其他四种量表。回归分析发现 RBS 是 LP 和 CP 组归属的最显著预测因子(p <.001)。RBS 能够有效识别所有报告神经心理症状的 LP,这归因于其基于认知努力测试分数的发展。