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斯坦福-比奈 5 项漏答非言语指数的编制及其在伪装智力迟钝中的应用检测。

Development and validation of the stanford binet-5 rarely missed items-nonverbal index for the detection of malingered mental retardation.

机构信息

Department of Psychology, Louisiana State University, Baton Rouge, 70803, USA.

出版信息

Arch Clin Neuropsychol. 2011 Dec;26(8):756-67. doi: 10.1093/arclin/acr078. Epub 2011 Oct 4.

DOI:10.1093/arclin/acr078
PMID:21971392
Abstract

Current research suggests that effort indices designed for the detection of malingered neurocognitive functioning do not have adequate sensitivity or specificity for use in cases where malingered mental retardation (MR) is the issue. Therefore, development and validation of reliable, objective measures for the detection of malingered MR have become imperative for both forensic and disability cases in recent years. The purpose of this study was to develop and validate an embedded malingering index for the Stanford Binet Intelligence Scales, Fifth Edition. Data from individuals in the SB5 standardization sample, who had intellectual deficits in the MR range, were used. Items that were rarely missed by the MR sample were pooled and validated using a sample of 54 college students asked to feign MR. Nonverbal items that were missed significantly more frequently by the malingering "analog MR sample" were retained and composed the Stanford Binet Rarely Missed Items-Nonverbal (SBRMI-NV) index. When only individuals who successfully malingered MR (FSIQ < 71) were included, sensitivity of 0.88 and specificity of 1.00 were obtained. Results indicate that although the SBRMI-NV needs further validation, it shows great promise in the detection of malingered MR.

摘要

目前的研究表明,旨在检测伪装神经认知功能的努力指数对于检测伪装智力迟钝(MR)的案例没有足够的敏感性或特异性。因此,近年来,为了法医和残疾案件,开发和验证可靠、客观的伪装 MR 检测方法已变得至关重要。本研究旨在为斯坦福-比奈智力量表第五版开发和验证一个嵌入式伪装指数。使用了在 MR 范围内存在智力缺陷的 SB5 标准化样本中的个体的数据。将很少被 MR 样本遗漏的项目汇集在一起,并使用要求伪装成 MR 的 54 名大学生样本进行验证。被伪装的“模拟 MR 样本”明显更频繁遗漏的非语言项目被保留下来,并组成斯坦福-比奈罕见遗漏项目-非语言(SBRMI-NV)指数。当只包括那些成功伪装 MR(FSIQ<71)的个体时,获得了 0.88 的敏感性和 1.00 的特异性。结果表明,尽管 SBRMI-NV 需要进一步验证,但它在检测伪装 MR 方面显示出很大的潜力。

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