IN 2003, AN UPDATED version of the Wechsler Intelligence Scale for Children, known as the Wechsler Intelligence Scale for Children Fourth Edition (WISC-IV), was published and put into clinical usage in English-speaking countries. The WISC-IV is a psychometric measure of intelligence for children aged 6–16 years. The WISC-IV differs from its previous version, the WISC-III, in significant ways. In essence, there is a move away from a verbal–performance dichotomy of intellectual abilities, and all four of the index scores are included in the calculation of full-scale IQ (FSIQ). The psychometric properties of the English WISC-IV are strong but revisions made to the WISC-III when developing the WISC-IV may have altered previously identified patterns of subtest and index score performance in clinical populations. For example, studies of children with traumatic brain injury have shown profile differences when comparing the WISC-IV to older versions of the WISC-III.
Western studies on the data obtained from WISC-III of specific clinical groups have reported some distinct and reliable subtest and index profiles in childhood neurodevelopmental disorders, such as autism[5, 6] and attention-deficit/hyperactivity disorder (ADHD). A commonly reported Wechsler profile among school-aged children with ADHD includes lower score on the Freedom From Distractibility (FFD) Index (replaced by the Working Memory Index on the WISC-IV) and the Processing Speed Index (PSI) as compared with other indexes.[8-14] As for data obtained from WISC-IV, there has been preliminary data on the subtest patterns of ADHD reported in the English WISC-IV manual. Also, Mayes et al. have examined the profile differences between the WISC-III and WISC-IV and the results showed that all children in the WISC-IV sample scored lowest on Working Memory Index (WMI) or PSI, whereas only 88% of the WISC-III children scored lowest on FFD or PSI. In addition, the index discrepancies were greater for the WISC-IV, suggesting that the WISC-IV might be better than the WISC-III in delineating the strengths and weaknesses of children with ADHD. Furthermore, prior studies have demonstrated an association between ADHD symptoms and weaknesses in both working memory and processing speed. Using hierarchical cluster analysis Thaler et al. found a relation between reduced processing speed in WISC-IV and inattention in a sample of ADHD children.
The WISC-IV has been in clinical use in Taiwan since 2007, when the translation and standardization were completed. During the standardization of the WISC-IV-Chinese version in this Mandarin-speaking population, data were drawn from 968 samples, but not collected specifically from clinical subjects. Even though there has been literature published discussing the validity of the four-factor scoring structure of the WISC-IV-Chinese and the Cattell-Horn-Carroll theory-based interpretative approach, there has been no previous report, to the best of our knowledge, on the application of the WISC-IV-Chinese in clinical populations in Mandarin-speaking contexts. With this in mind, the current study was designed to examine WISC-IV-Chinese performance in 338 children with ADHD using two different profile analytic approaches. The goal was to examine whether the profiles of the WISC-IV-Chinese index scores of the Mandarin-speaking ADHD was similar to that of ADHD children in English-speaking countries.
In addition, we wanted to inspect whether cognitive profile can contribute to the clinical subtyping of the heterogeneous ADHD. The rationale for this is that it has been shown that children diagnosed with Predominantly Inattentive (ADHD-I) and Combined subtypes of ADHD (ADHD-C) differ in cognitive tempo, age of onset, sex ratio, and comorbidity, yet a differentiating endophenotype has not been unequivocally identified. Solanto et al. have evaluated children with subtypes of ADHD-C, ADHD-I and normal control by WISC-III and neuropsychological tests battery. They found children diagnosed with the ADHD-I showed worse performance than the ADHD-C and control groups on the PSI of WISC-III. However, there was no support in the data for hypothesized differences between subtypes in specific functioning of the brain systems, nor in involvement of processes as revealed by neuropsychological tests. In this current survey, we also wanted to examine whether there was difference between the subtypes in cognitive performance that can be revealed by the WISC-IV-Chinese version.
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For the total sample of 334 children, the means of all four indexes were significantly below the normal mean of 100 (VCI z = –8.40, PRI z = –5.00, WMI z = –5.83, PSI z = –9.91, P ≤ 0.0001). The total sample and two subtype profiles are reported in Table 1. There was no difference between the two subtypes of children (ADHD-C and ADHD-I) in terms of index scores and subtest scores using the Bonferroni correction (to control for the number of comparisons made).
Table 1. Descriptive statistics for the WISC-IV Subtest and Index scores in 334 children with ADHD
|WISC-IV scores|| || || |
|Index|| || || |
|Verbal Comprehension||93.1 (12.0)||91.9 (11.8)||95.1 (12.2)|
|Perceptual Reasoning||95.9 (14.6)||94.5 (13.5)||98.2 (16.0)|
|Working Memory||95.2 (12.5)||95.6 (12.8)||94.6 (12.1)|
|Processing Speed||91.9 (15.6)||92.1 (16.4)||91.4 (14.3)|
|Full-scale IQ||92.3 (13.0)||91.6 (12.8)||93.5 (13.2)|
|Subtest|| || || |
|Similarities||9.1 (3.2)||8.9 (3.2)||9.4 (3.0)|
|Vocabulary||9.0 (2.7)||8.7 (2.6)||9.4 (2.8)|
|Comprehension||8.6 (2.4)||8.4 (2.5)||8.9 (2.2)|
|Block Design||10.2 (2.8)||10.1 (2.8)||10.4 (3.0)|
|Picture Concepts||8.7 (3.2)||8.4 (3.1)||9.2 (3.3)|
|Matrix Reasoning||9.2 (2.9)||8.9 (2.8)||9.5 (3.0)|
|Digit Span||9.3 (2.6)||9.4 (2.6)||9.3 (2.6)|
|Letter–Number Sequencing||9.0 (2.8)||9.1 (2.7)||8.8 (2.8)|
|Coding||8.4 (3.5)||8.4 (3.6)||8.4 (3.3)|
|Symbol Search||8.8 (3.0)||9.0 (2.9)||8.5 (3.1)|
The results of using CFA to examine the adequacy of the four-factor structure of the WISC-IV-Chinese indicated that the values of all indices met our goodness-of-fit standards (χ2 =50.47, P = 0.008, RMSEA = 0.048, SRMR = 0.038, NNFI = 0.98, CFI = 0.99). The results indicated that the four-factor model of the WISC-IV-Chinese fitted well for Taiwanese children with ADHD. Standardized factor loadings of the four-factor model of the WISC-IV are shown in Table 2.
Table 2. Standardized factor loadings and correlations between four-factor model of the WISC-IV in Taiwanese children with ADHD
|Vocabulary||0.805|| || || |
|Similarity||0.722|| || || |
|Comprehension||0.562|| || || |
|Block Design|| ||0.694|| || |
|Picture Concepts|| ||0.529|| || |
|Matrix Reasoning|| ||0.724|| || |
|Digit Span|| || ||0.608|| |
|Letter–Number Sequencing|| || ||0.718|| |
|Coding|| || || ||0.463|
|Symbol Search|| || || ||0.944|
| || || || || |
|VCI||1.000|| || || |
|PRI||0.716||1.000|| || |
As for profile pattern analysis, the index score differences among the ADHD children using repeated-measure anova were as follows: for the whole group, index scores of PSI/VCI were the weaknesses; for ADHD-I, PSI/WMI were the weaknesses; while for ADHD-C, PSI/VCI were the weaknesses. The detailed descriptions were reported as below and summarized in Table 3. For all 334 ADHD children, the repeated measures anova examining potential differences between the four index scores was significant (F(3,999) = 10.40, P ≤ 0.001). Contrasts indicated that there were no significant differences among the VCI and PSI, but significant differences were present between the PRI and VCI, P = 0.001, and the PSI, P < 0.001; and between the WMI and VCI, P = 0.013, and the PSI, P = 0.001. For the 127 children with ADHD-I, the repeated measures anova examining potential differences between the four index scores was also significant (F(3,378) = 8.54, P < 0.001). Contrasts indicated that significant differences were present between the PRI and WMI (P = 0.023); and the PSI (P < 0.001). For the 207 children with ADHD-C, the repeated measure anova was also significant (F(3,618) = 6.29, P < 0.001). Contrasts indicated that there were no significant differences among the VCI and PSI, but significant differences were present between the PRI and VCI (P = 0.014), and between the WMI and VCI (P < 0.001), and the PSI (P = 0.023). For all tests, the alpha level was set at P = 0.05.
Table 3. Profile analysis of WISC-IV-Chinese for Taiwanese children with ADHD
|Total n = 334|
|VCI|| || || || |
|PRI||D = 2.8*, P = 0.001|| || ||D = 4, P < 0.001|
|WMI||D = 2.1, P = 0.013|| || ||D = 3.4, P = 0.001|
|PSI|| || || || |
|Summary: WMI > PSI/VCI, PRI > PSI/VCI|
|ADHD-C N = 207|| || || || |
|VCI|| || || || |
|PRI||D = 2.6, P = 0.014|| || || |
|WMI||D = 3.7, P < 0.001|| || ||D = 3.4, P = 0.023|
|PSI|| || || || |
|Summary: PRI > VCI, WMI > VCI/PSI|
|ADHD-I N = 127|| || || || |
|VCI|| || || || |
|PRI|| || ||D = 3.6, P = 0.023||D = 6.7, P < 0.001|
|WMI|| || || || |
|PSI|| || || || |
|Summary: PRI > WMI, PRI > PSI|
The results for the ipsative comparison are summarized in Table 4. Among the 334 children with ADHD, various percentages of children had individual index scores that were either strengths or weaknesses; however, PSI stood out as the most frequently reported weakness among the four index scores, using ipsative analysis (for total ADHD: 20.4%; for ADHD-C: 16.4%; for ADHD-I: 26.8%). χ2 analysis revealed that for the whole group of ADHD children, PSI was significantly more frequently a weakness in the profile (percentage of VCI as the weakness < percentage of PSI as the weakness, P = 0.031).
Table 4. Percentage of children showing strengths or weaknesses in WISC-IV profile by ipsative comparison
| ||Strength in||Weakness in|
|Total ADHD n = 334||12.6%||15.9%||13.2%||11.7%||14.4%||6.3%||9.0%||20.4%|
|ADHD-C n = 207||10.1%||12.6%||15.9%||12.1%||14.5%||7.2%||7.2%||16.4%|
|ADHD-I n = 127||16.5%||21.3%||8.7%||11.0%||14.2%||4.7%||11.8%||26.8%|
As for inspection of the PSI index, both Coding (mean = 92) and Symbol Search (mean = 94) were significantly lower than the normal mean of 100 (z = −9.9 and −7.2, P < 0.0001) for the total sample; however, Coding was not significantly lower than Symbol Search using Bonferroni correction for the total sample. Subtype comparison on the processing speed discrepancy index revealed that children with ADHD-I had a greater weakness in processing speed performance (FSIQ-Symbol Search discrepancy score) than children with ADHD-C, t(331) = 3.1, P = 0.002.
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Establishing a cognitive profile of children with ADHD based on standard cognitive tests may achieve several objectives. One of them is to examine whether a particular profile on the WISC may help diagnose ADHD. Another objective of conducting a profile analysis is to check whether IQ subtests or index scores may help to determine cognitive strengths and weaknesses in children with ADHD. In our current study, results indicated that the four-factor model of the WISC-IV-Chinese fitted well for Taiwanese children with ADHD. In addition, different methods of pattern analysis showed similar findings of the index score of PSI to be the weakness domain in Taiwanese children with ADHD. Our findings were, in the main, consistent with those of previous Western reports, though details require further discussion.
Most of the previous Western studies have reported that both PSI and WMI index were among the weakness domains in children of ADHD; however, we do not replicate this finding. At this stage, we cannot fully explain the reasons why our patterns of WMI scores and those of Western reports differ, but we postulate this to be related to the novel nature of some of the WISC-IV index scores and the different ways of administration of certain subtests in cultural adaptation and translation of this assessment tool. For example, the Working Memory Index in the English WISC-IV is specially assessed through changes made to the Digit Span subtest and the addition of a new subtest, ‘Letter–Number Sequencing’. In the ‘Letter–Number Sequencing’ subtest, the child listens to sequences of random letters and digits and repeats the digits in numerical order and then the letters in alphabetical order. In contrast to Digit Span and Arithmetic on the FFD Index of WISC-III (which replaces WMI), the Arithmetic subtest now becomes the optional test, which was substituted for ‘Letter–Number Sequencing’ when the latter was invalidated or if the examiner deemed Arithmetic a preferable substitute.
Nevertheless, in the Mandarin-Chinese system, there is no corresponding alphabetical symbols system that comes in a fixed order that is familiar to every child. Instead, Chinese is a morphosyllabic language in which each character, the primary unit of writing, represents both a syllable and a lexical morpheme. A character and its components (strokes or radicals) do not represent phonemes. During the Chinese translation of WISC-IV, the authors chose the 12-animal zodiac system (i.e. mouse, ox, tiger, rabbit, dragon, snake, horse, sheep, monkey, rooster, dog, pig) as the ‘Letter’ part of the ‘Letter–Number Sequence’ subtest; however, the 12-animal zodiac system originating from folk stories is unfamiliar to many young children, especially in clinical sample. In our total sample of 334 children, only 167 of them can be tested by the ‘Letter–Number Sequencing’ subtest, and more than half of them (171) had to use the Arithmetic subtest as substitute for the derivation of the WMI. As reported in the Wechsler Technical and Interpretative Manual, there is a relatively lower correlation between Arithmetic and WMI (r = 0.57) when compared to the correlation between ‘Letter–Number Sequencing’ and WMI (r = 0.86). The cognitive demands between the Arithmetic and ‘Letter–Number Sequencing’ subtests might differ and be confounded by mathematical abilities. The Technical Report of the WISC-IV has emphasized that both the lineage and the newest of the Working Memory and Processing Speed factors require restricted interpretation until ample experimental research on the validity of the new scale labels is available. Nevertheless, the validity of a particular interpretation of scale variability, and especially the hypothetical constructs being assessed, are experimental questions separate from the statistical analysis of group data.
We found the PSI index score to be significantly lower than the FSIQ, which is in line with previous Western studies.[8-10, 12] The PSI was first introduced on the WISC-III and was primarily visuomotor. Previous data indicate that PSI is more independent of IQ than the other factors in the Wechsler series; however PSI also had lower reliability than the other index coefficients. Because PSI is relatively unique, this factor may have clinical significance for individual children and diagnostic groups.
Children with ADHD have been shown to demonstrate slowed processing speed relative to typically developing peers in graphomotor speed, as measured by WISC-IV Processing Speed subtests.[14, 25] On the WISC-IV, PSI consists of Coding and Symbol Search as on the WISC-III. Coding measures writing speed while Symbol Search is related to visual mental speed; however, it remains unclear to what extent the slowed performance in children with ADHD is a function of slow motor control, rather than slowed information processing at the level of response selection and preparation, prior to execution of the motor response.
In our data, we also found both the Coding and Symbol Search subtest to be lower than the population mean of 100; also, the ADHD-I subgroup can be demonstrated to have processing speed performance problems in the PSI discrepancy scale. These findings all implied that we should look for performance speed weaknesses of the children with ADHD in the real world function. While low PSI scores by themselves do not predict clinical diagnoses, the identification of weaknesses in these areas is helpful in understanding the neuropsychological profiles of these children and may have important implications for educational intervention (i.e. the need to remediate, compensate for, and circumvent the attention, writing, and performance speed weaknesses). From our data we may conclude that in the case of Taiwanese children with ADHD, attending to the weakness in performance speed is probably the first thing adults need to consider in attempting to improve the child's daily function. Clinicians should ensure that these areas are properly assessed and that intervention is provided. For example, homework assignment with repetitive writing practice should be avoided.
As reported in our data obtained from the ipsative comparison, 14.4% of the children in our sample were found to score lowest on VCI, 6.3% scored lowest on PRI, 9.0% scored lowest on WMI, and 20.4% scored lowest on PRI. In essence, even though the index of PRI was found statistically to be the most frequent weakness domain in Chinese-speaking children with ADHD, not all children scored lowest on any particular index score. There seemed to be plenty of individual differences.
Our data showed that ADHD-C and ADHD-I subtypes differed in processing speed performance as noted from processing speed discrepancy scores. Given that we only arranged general intelligence tests without concomitant neuropsychological assessments, this finding can only provide limited information in the field of ADHD subtyping. Our data corroborates previous Western findings;[16, 17] however, there is still inadequate support for using the cognitive assessment data for subtyping ADHD, and for the claim about different involvement of brain processes.
There were several limitations of this study. First, we relied on a convenience sample that was referred to a single hospital for disorder evaluation. The methodology employed here advantageously provided a direct link between clinical practice and WISC-IV test score interpretation in ADHD; however, a single institution does not have a sufficient number of patients to control for the numerous family-specific and region-specific variables involved. Second, a finding of significant variation in strengths and weaknesses revealed by statistical methods is only indicative of a reliable difference. Third, the sample was without the condition of mental retardation by inclusion criteria, so the results may not be applicable to children whose FSIQ are below 70. Fourth, we used the report by Naglieri et al. on values of difference for significance in conducting our ipsative comparison and these data were derived from US samples. In the WISC-IV-Chinese Administration and Scoring Manual, values are provided for comparing all possible pair-wise combinations of the four index scales, but values for ipsative approach when psychologists want to determine whether any of the combination of the index scores are significantly different are absent; however, the available Chinese pair-wise comparison values are similar to the US ones published in the English WISC-IV Manual. We hope the similarities will lessen the doubt in our taking advantage of the Western data in conducting an ipsative approach but we do acknowledge this limitation in methodology.
In conclusion, the current study examined the WISC-IV-Chinese IQ profile of school-aged Taiwanese children with ADHD. We replicated some of the previous Western works by documenting the PSI as the weakness in ADHD. It is believed that profile analysis at the subtest level with supporting data will be useful in understanding a child's strengths and weaknesses and in guiding treatment and educational programming.