Schoenberg Mike R, Lange Rael T, Saklofske Donald H
Department of Neurology, University Hospitals of Cleveland and Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA.
J Clin Exp Neuropsychol. 2007 Nov;29(8):867-78. doi: 10.1080/13803390601147678. Epub 2007 Feb 19.
Establishing a comparison standard in neuropsychological assessment is crucial to determining change in function. There is no available method to estimate premorbid intellectual functioning for the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). The WISC-IV provided normative data for both American and Canadian children aged 6 to 16 years old. This study developed regression algorithms as a proposed method to estimate full-scale intelligence quotient (FSIQ) for the Canadian WISC-IV. Participants were the Canadian WISC-IV standardization sample (n = 1,100). The sample was randomly divided into two groups (development and validation groups). The development group was used to generate regression algorithms; 1 algorithm only included demographics, and 11 combined demographic variables with WISC-IV subtest raw scores. The algorithms accounted for 18% to 70% of the variance in FSIQ (standard error of estimate, SEE = 8.6 to 14.2). Estimated FSIQ significantly correlated with actual FSIQ (r = .30 to .80), and the majority of individual FSIQ estimates were within +/-10 points of actual FSIQ. The demographic-only algorithm was less accurate than algorithms combining demographic variables with subtest raw scores. The current algorithms yielded accurate estimates of current FSIQ for Canadian individuals aged 6-16 years old. The potential application of the algorithms to estimate premorbid FSIQ is reviewed. While promising, clinical validation of the algorithms in a sample of children and/or adolescents with known neurological dysfunction is needed to establish these algorithms as a premorbid estimation procedure.
在神经心理学评估中建立比较标准对于确定功能变化至关重要。目前尚无可用方法来估计《韦氏儿童智力量表第四版》(WISC-IV)的病前智力功能。WISC-IV提供了6至16岁美国和加拿大儿童的常模数据。本研究开发了回归算法,作为一种估计加拿大WISC-IV全量表智商(FSIQ)的建议方法。参与者为加拿大WISC-IV标准化样本(n = 1100)。样本被随机分为两组(开发组和验证组)。开发组用于生成回归算法;1种算法仅包含人口统计学变量,11种算法将人口统计学变量与WISC-IV分测验原始分数相结合。这些算法解释了FSIQ中18%至70%的方差(估计标准误,SEE = 8.6至14.2)。估计的FSIQ与实际FSIQ显著相关(r = 0.30至0.80),并且大多数个体FSIQ估计值在实际FSIQ的±10分范围内。仅包含人口统计学变量的算法不如将人口统计学变量与分测验原始分数相结合的算法准确。当前算法对6至16岁加拿大个体的当前FSIQ给出了准确估计。本文回顾了这些算法在估计病前FSIQ方面的潜在应用。尽管前景乐观,但需要在已知神经功能障碍的儿童和/或青少年样本中对这些算法进行临床验证,以将其确立为一种病前估计程序。