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A comparison of WISC-IV and WISC-V verbal comprehension index scores for children with autism spectrum disorder

Autism Disorder Comparison

Objectives: This study aimed to explore changes in verbal comprehension subtest and index scores from Wechsler Intelligence Scale for Children, fourth edition (WISC)-IV to WISC-V for individuals with autism spectrum disorder (ASD), as the test revision dropped the subtest that has proven to be most challenging for those with ASD (i.e. Comprehension).

Methods: In all, 48 children with ASD who had been assessed with WISC-IV and re-evaluated with WISC-V were included in this study. Paired samples t-tests were used to examine changes in scores between administrations.

Results: Results indicated that changes in subtest scores were minimal although a statistically significant index score change occurred.

Discussion: These data suggest that administering additional measures of verbal intellect to individuals with ASD (i.e. beyond the two core verbal comprehension subtests of WISC-V) is critical for capturing the totality of their strengths and weaknesses, to effectively inform treatment planning.

Autism spectrum disorder (ASD) is defined in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) as a neurodevelopmental disorder (American Psychiatric Association, 2013American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.[Crossref] [Google Scholar]). Genetic influences are thought to be a risk factor for ASD and approximately 15% of diagnoses are associated with a known genetic mutation; however, there are many other nonspecific risk factors and no definitive cause has been established (American Psychiatric Association, 2013American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.[Crossref] [Google Scholar]). With that said, it has historically been recognized that those with ASD have anomalous brain development from birth (Lincoln, Allen, Kilman, Schopler, & Mesibov, 1995Lincoln A. J., Allen M. H., & Kilman A. (1995). The assessment and interpretation of intellectual abilities in people with autism. In E. Schopler & G. B. Mesibov (Eds.), Learning and Cognition in Autism (pp. 89117). Boston, MA: Springer.[Crossref] [Google Scholar]). More recently, electroencephalogram (EEG) data obtained as early as 3 months of age detected atypical brain development in those subsequently diagnosed with ASD (Bosl, Tager-Flusberg, & Nelson, 2018Bosl, W. J., Tager-Flusberg, H., & Nelson, C. A. (2018). EEG analytics for early detection of autism spectrum disorder: A data-driven approach. Scientific Reports, 8, 120. doi: 10.1038/s41598-018-24318-x[Crossref], [PubMed], [Web of Science ®] [Google Scholar]). Relatedly, capturing the neuropsychological profiles of children with ASD is important for understanding how structural and functional neurologic differences may impact information processing skills. In particular, ASD is often associated with intellectual delays and language difficulties (American Psychiatric Association, 2013American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.[Crossref] [Google Scholar]) although given the diversity in presentations of individuals with ASD, a consistent neuropsychological profile is not typically present among those with the diagnosis. Recognizing the variability that exists is important, while also attempting to understand the needs of particular subgroups.

A diagnosis of ASD provides access to services that are critical for appropriately supporting individuals with this neurodevelopmental disorder across home, school, and community settings. However, individuals with ASD are a diverse group with varied strengths, weaknesses, and neuropsychological profiles. As such, a comprehensive evaluation is needed to measure an individual’s level of functioning across domains, specify whether the disorder is present with or without accompanying intellectual or language impairment, and to identify appropriate interventions and supports. Miller et al. (2015Miller, J. L., Saklofske, D. H., Weiss, L. G., Drozdick, L., Llorente, A. M., Holdnack. J. A., & Prifitera, A. (2015). Issues related to the WISC-V assessment of cognitive functioning in clinical and special groups. In L. G. Weiss, D. H. Saklofske, J. A. Holdnack, & A. Prifitera (Eds.), WISC-V assessment and interpretation: Scientist-practitioner perspectives (pp. 287343). San Diego, CA: Elsevier Science. [Google Scholar]) wrote, “Although the first intelligence tests were mainly used for classification, selection, and placement, the role of intelligence tests has broadened to include profile analysis that may characterize groups of patients with particular diagnoses and alternatively to use such information to recognize individual differences that may translate to targeted intervention planning” (p. 287). In the practice of clinical neuropsychology, the clinician’s role is to recognize data patterns that may serve to explain the client’s functioning but also to identify individual strengths and weaknesses that guide the selection of individualized supports.

Given the significant variability in presentation for those with a shared diagnosis of ASD, information about one’s level of cognitive functioning can inform treatment planning. In particular, cognitive assessment data may be used for making legal determinations about an individual’s eligibility for services. As an example, in some states, adult individuals with an ASD diagnosis are eligible for supports and services, but those who also carry a diagnosis of intellectual disability are eligible for additional services. Accordingly, understanding how individuals with ASD perform on widely used measures of intellect is important for providing effective assessment and intervention services to this population.

The verbal comprehension index (VCI) of the Wechsler Intelligence Scale for Children is a commonly used measure of verbal intelligence. The fourth edition of this measure (WISC-IV) included three subtests in calculation of the VCI index score: Similarities, Vocabulary, and Comprehension. Similarities is a task that measures one’s verbal concept formation and abstract reasoning skills, Vocabulary measures word knowledge and verbal concept formation, and Comprehension measures “verbal reasoning and conceptualization, verbal comprehension and expression, the ability to evaluate and use past experience, and the ability to demonstrate practical knowledge and judgment” (Weiss, Saklofske, Holdnack, & Prifitera, 2015Weiss, L. G., Saklofske, D. H., Holdnack, J. A., & Prifitera, A. (2015). WISC-V: Advances in the assessment of intelligence. In L. G. Weiss, D. H. Saklofske, J. A. Holdnack, & A. Prifitera (Eds.), WISC-V assessment and interpretation: Scientist-practitioner perspectives (pp. 323). San Diego, CA: Elsevier Science. [Google Scholar], p. 9). Success on the Comprehension subtest requires linguistic sophistication that many individuals with ASD do not possess, given commonly occurring core expressive and receptive language deficits (Kwok, Brown, Smyth, & Cardy, 2015Kwok, E. Y. L., Brown, H. M., Smyth, R. E., & Cardy, J. O. (2015). Meta-analysis of receptive and expressive language skills in autism spectrum disorder. Research in Autism Spectrum Disorders, 9, 202222. doi: 10.1016/j.rasd.2014.10.008[Crossref], [Web of Science ®] [Google Scholar]), as well as pragmatic language deficits (Whyte & Nelson, 2015Whyte, E. M. & Nelson, K. E. (2015). Trajectories of pragmatic and nonliteral language development in children with autism spectrum disorders. Journal of Communication Disorders, 54, 214. doi: 10.1016/j.jcomdis.2015.01.001[Crossref], [PubMed], [Web of Science ®] [Google Scholar]). In addition, the Comprehension subtest has a higher language load and the test items can be more difficult for those with ASD to manage while the Similarities and Vocabulary subtests are generally more simplified. Not surprisingly, the Comprehension subtest has been found to be the most challenging for individuals with ASD in previous research, with Similarities being the least challenging (Mayes & Calhoun, 2008Mayes, S. D., & Calhoun, S. L. (2008). WISC-IV and WIAT-II profiles in children with high-functioning autism. Journal of Autism and Developmental Disorders, 38, 428439. doi: 10.1007/s10803-007-0410-4[Crossref], [PubMed], [Web of Science ®] [Google Scholar]; Wechsler, 2003Wechsler, D. (2003). WISC-IV technical and interpretive manual. San Antonio, TX: The Psychological Corporation. [Google Scholar], 2014Wechsler, D. (2014). WISC-V technical and interpretive manual. Bloomington, MN: NCS Pearson. [Google Scholar]; Zayat, Kalb, & Wodka, 2011Zayat, M., Kalb, L., & Wodka, E. L. (2011). Performance pattern differences between children with autism spectrum disorders and attention deficit-hyperactivity disorder on measures of verbal intelligence. Journal of Autism and Developmental Disorders, 41, 17431747. doi: 10.1007/s10803-011-1207-z[Crossref], [PubMed], [Web of Science ®] [Google Scholar]). Notably, this pattern was not observed in a sample of individuals with attention deficit hyperactivity disorder (ADHD), suggesting that while children with ADHD and ASD have some similar behavioral deficits and shared executive functioning deficits, the core language formulation and social reasoning deficits are distinctive to ASD and this pattern can be useful to discriminate between the two groups (Zayat et al., 2011Zayat, M., Kalb, L., & Wodka, E. L. (2011). Performance pattern differences between children with autism spectrum disorders and attention deficit-hyperactivity disorder on measures of verbal intelligence. Journal of Autism and Developmental Disorders, 41, 17431747. doi: 10.1007/s10803-011-1207-z[Crossref], [PubMed], [Web of Science ®] [Google Scholar]).

Previous researchers have suggested that when cognitive assessment is used as part of diagnostic decision-making, the measure ought to capture relative strengths and weaknesses of the target population, as well as specific patterns unique to the population (Zayat et al., 2011Zayat, M., Kalb, L., & Wodka, E. L. (2011). Performance pattern differences between children with autism spectrum disorders and attention deficit-hyperactivity disorder on measures of verbal intelligence. Journal of Autism and Developmental Disorders, 41, 17431747. doi: 10.1007/s10803-011-1207-z[Crossref], [PubMed], [Web of Science ®] [Google Scholar]). Measures of verbal intellect are particularly important for those with ASD, as language impairments are a common challenge for many individuals across the spectrum and accordingly, their performance on measures of verbal intellect is often lower than typically developing individuals (Joseph, Tager-Flusberg, & Lord, 2002Joseph, R. M., Tager-Flusberg, H., & Lord, C. (2002). Cognitive profiles and social-communicative functioning in children with autism spectrum disorder. Journal of Child Psychology and Psychiatry, 43, 807821. doi: 10.1111/1469-7610.00092[Crossref], [PubMed], [Web of Science ®] [Google Scholar]; Klinger, O’Kelley, Mussey, Goldstein, & DeVries, 2012Klinger, L. G., O’Kelley, S. E., Mussey, J., Goldstein, S., DeVries, M. (2012). Assessment of intellectual functioning in autism spectrum disorder. In D. P. Flanagan & P. L.Harrison (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (3rd ed., pp. 670686). New York, NY: Guilford Press. [Google Scholar]; Mayes & Calhoun, 2008Mayes, S. D., & Calhoun, S. L. (2008). WISC-IV and WIAT-II profiles in children with high-functioning autism. Journal of Autism and Developmental Disorders, 38, 428439. doi: 10.1007/s10803-007-0410-4[Crossref], [PubMed], [Web of Science ®] [Google Scholar]; Wechsler, 2003Wechsler, D. (2003). WISC-IV technical and interpretive manual. San Antonio, TX: The Psychological Corporation. [Google Scholar]). Of course, patterns observed in assessment data must not be interpreted as a definitive indicator of a diagnostic condition, and it is the clinician’s responsibility to rule out other conditions (Miller et al., 2015Miller, J. L., Saklofske, D. H., Weiss, L. G., Drozdick, L., Llorente, A. M., Holdnack. J. A., & Prifitera, A. (2015). Issues related to the WISC-V assessment of cognitive functioning in clinical and special groups. In L. G. Weiss, D. H. Saklofske, J. A. Holdnack, & A. Prifitera (Eds.), WISC-V assessment and interpretation: Scientist-practitioner perspectives (pp. 287343). San Diego, CA: Elsevier Science. [Google Scholar]). However, given that weaknesses of those with ASD often include language abnormalities and social impairments, and given that measures of verbal intellect often require one to demonstrate language skills and social reasoning abilities, it is important to understand patterns of performance on such measures.

When the WISC-IV was revised and the fifth edition (WISC-V) was published, the Comprehension subtest was dropped from the VCI. Finding a specific clinical reason for the exclusion of Comprehension proved unsuccessful in a rather expansive literature search although an exploration of multiple presentations and materials from the WISC publishers revealed an emphasis on time and efficiency (i.e. the terms “faster” and “easier” were often used to describe administration). Now, the index score places less of an emphasis on practical knowledge and judgment, which is a reasonable concern for measuring the skills of individuals with ASD who demonstrate impaired theory of mind (Fadda et al., 2016Fadda, R., Parisi, M., Ferretti, L., Saba, G., Foscoliano, M., Salvago, A., & Doneddu, G. (2016). Exploring the role of theory of mind in moral judgment: The case of children with autism spectrum disorder. Frontiers in Psychology, 7, 18. doi: 10.3389/fpsyg.2016.00523[Crossref], [PubMed], [Web of Science ®] [Google Scholar]) and executive functioning weaknesses (Leung, Vogan, Powell, Anagnostou, & Taylor, 2016Leung, R. C., Vogan, V. M., Powell, T. L., Anagnostou, E., Taylor, M. J. (2016). The role of executive functions in social impairment in autism spectrum disorder. Child Neuropsychology 22(3), 336344. doi: 10.1080/09297049.2015.1005066[Taylor & Francis Online], [Web of Science ®] [Google Scholar]). This raises a very important question about the utility of the VCI, particularly with respect to the formulation of diagnostic impressions and the development of individualized treatment recommendations. More specifically, given that a goal of neuropsychological testing is to capture the totality of a child’s profile and accurately describe individual strengths and weaknesses, does the WISC-V VCI describe a patient’s profile differently than the WISC-IV did? We hypothesized there would be a statistically significant increase in the VCI composite score from the WISC-IV to WISC-V although we expected this to occur as a function of the measurement change (i.e. dropping the Comprehension subtest), rather than due to statistically significant changes on the individual subtests. Moreover, we expected that the above-described pattern (i.e. Similarities > Vocabulary > Comprehension) among the three subtests would persist on WISC-V, for those who were administered the Comprehension subtests as a supplemental measure.

Methods

Participants

Participants were a clinically referred sample of children with an ASD diagnosis, drawn from a de-identified, archival database that includes data previously collected as part of normal clinical practice. Institutional review board (IRB) resulted in an exempt determination for this project. All included participants received comprehensive neuropsychological evaluations at a multidisciplinary child development center in New England. All testing was supervised by one licensed psychologist with clinical neuropsychology fellowship training and over 20 years of practice, with test administration completed by approximately 10 post-doctoral fellows. Initially, all cases with reported results from the WISC-V were retrieved. From this sample, all cases in which the individual carried an ASD diagnosis (i.e. including those who had previously been diagnosed with Autism, Asperger’s syndrome, or pervasive developmental disorder not otherwise specified (PDD-NOS)) were retained. ASD diagnosis was determined by the evaluator based on current diagnostic criteria at the time of evaluation and was documented within the neuropsychological report and the patient’s electronic health record. The sample was then narrowed to individuals who were also administered the WISC-IV between 12 and 36 months prior to the WISC-V administration, as 12 months is the minimum suggested time between administrations and 36 months is the typical re-evaluation period for students on Individualized Education Programs. Finally, those who had been administered the WISC-IV more than three times were excluded to prevent the possible influence of practice effects. This resulted in a sample of 48 individuals (male n = 38).

The average age at the time of the WISC-IV was 10 years 1 month (SD = 24.85 months; range =6 years 5 months to 15 years 10 months) and the average age at the time of the WISC-V was 12 years 0 months (SD = 27.07 months; range =8 years 3 months to 16 years 10 months). The average time in months between WISC-IV and WISC-V administration was 22.29 (SD = 7.49; range =12–36). Available demographics are reported in Table 1, however, because these data were collected from an archival database with some missing data, demographic information was not available for the entire sample.

Table 1. Sample demographics.

Measures

WISC VCI. The WISC is an individually administered battery used to assess the intellectual ability of children from 6 years 0 months to 16 years 11 months. The previous edition of the WISC, the WISC-IV, included four primary composite score indices: VCI, perceptual reasoning index (PRI), working memory index (WMI), and processing speed index (PSI). The current edition of the WISC, the WISC-V, includes five primary composite score indices; VCI, visual spatial index (VSI), fluid reasoning index (FRI), WMI, and PSI. The reader is referred to the WISC-IV Technical and Interpretive Manual (Wechsler, 2003Wechsler, D. (2003). WISC-IV technical and interpretive manual. San Antonio, TX: The Psychological Corporation. [Google Scholar]) and the WISC-V Technical and Interpretive Manual (Wechsler, 2014Wechsler, D. (2014). WISC-V technical and interpretive manual. Bloomington, MN: NCS Pearson. [Google Scholar]) for the subtests’ psychometric properties.

For purposes of the present study, only the VCI composite score, which is a commonly used measure of verbal intelligence, and those subtests included as part of the composite were included in the analyses. As noted above, the subtests used to elicit the index score on the previous edition of the test, the WISC-IV were: Similarities, Vocabulary, and Comprehension, with Comprehension dropped from the composite score on the WISC-V. Though not included in the VCI composite score, 79.17% (n = 38) participants had been administered the Comprehension subtest on the WISC-V, as the evaluator had deemed it an appropriate supplemental measure.

Data analyses

Paired-sample t-tests were used to investigate differences among both index scores and subtest scores for the entire sample. To investigate whether the distinct pattern of performance (Similarities > Vocabulary > Comprehension) noted in previous studies (e.g. Mayes & Calhoun, 2008Mayes, S. D., & Calhoun, S. L. (2008). WISC-IV and WIAT-II profiles in children with high-functioning autism. Journal of Autism and Developmental Disorders, 38, 428439. doi: 10.1007/s10803-007-0410-4[Crossref], [PubMed], [Web of Science ®] [Google Scholar]; Zayat et al., 2011Zayat, M., Kalb, L., & Wodka, E. L. (2011). Performance pattern differences between children with autism spectrum disorders and attention deficit-hyperactivity disorder on measures of verbal intelligence. Journal of Autism and Developmental Disorders, 41, 17431747. doi: 10.1007/s10803-011-1207-z[Crossref], [PubMed], [Web of Science ®] [Google Scholar]) existed, further paired sample t-tests were completed.

Results

Mean standard and index scores for the current sample on the WISC-IV and WISC-V are reported in Table 2. To determine whether there was an increase in the VCI from WISC-IV to WISC-V for the entire sample, a paired samples t-test was conducted. Results indicated a statistically significant increase in VCI scores from WISC-IV (M = 89.98, SD = 19.77) to WISC-V (M = 95.06, SD = 18.92), t (47) = 4.22, p < .001 (two-tailed), displayed in Figure 1. The mean increase in VCI scores was 5.08 with a 95% confidence interval ranging from 2.66 to 7.51. The eta squared statistic (0.27) indicated a large effect size, following Cohen’s (1988Cohen, J. W. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates. [Google Scholar]) effect size guidelines using partial eta squared (0.01 = small effect, 0.06 = moderate effect, 0.14 = large effect).

Table 2. Mean scores of current sample and from WISC-IV and WISC-V special group validity studies.

Figure 1. Mean scaled score changes from WISC-IV to WISC-V on the Verbal Comprehension Index (VCI) in children and adolescents with Autism Spectrum Disorder. Similarities, Vocabulary, and Comprehension subtests have a standard deviation of three, and the VCI composite score has a standard deviation of 15. *p < .05. **p < .001.

Additional paired sample t-tests were conducted to determine whether there were significant differences in participants’ performance on each of the three subtests from WISC-IV to WISC-V. Figure 1 depicts the scaled score changes across administrations for each of the VCI subtests. There was a statistically significant decrease in the Similarities subtest scores from WISC-IV (M = 10.50, SD = 3.18) to WISC-V (M = 9.77, SD = 3.53), t (47)=–2.53, p=.02 (two-tailed). Although the mean change was significant, the decrease was merely 0.73 with a 95% confidence interval ranging from –1.31 to –0.15. The eta squared statistic (0.12) indicated a moderate effect. There was not a statistically significant difference on either of the other subtests. WISC-IV and WISC-V mean scores from special group validity studies (Wechsler, 2011Wechsler, D. (2011). Wechsler Abbreviated Scale of Intelligence. (2nd ed., WASI-II). San Antonio, TX: Pearson. doi: 10.1177/0734282912467756[Crossref] [Google Scholar], 2014Wechsler, D. (2014). WISC-V technical and interpretive manual. Bloomington, MN: NCS Pearson. [Google Scholar]) are included in Table 2 for comparison with the scores of the current sample.

Further paired samples t-tests were completed to examine whether the distinct pattern of performance (Similarities > Vocabulary > Comprehension) noted in previous studies (e.g. Mayes & Calhoun, 2008Mayes, S. D., & Calhoun, S. L. (2008). WISC-IV and WIAT-II profiles in children with high-functioning autism. Journal of Autism and Developmental Disorders, 38, 428439. doi: 10.1007/s10803-007-0410-4[Crossref], [PubMed], [Web of Science ®] [Google Scholar]; Zayat et al., 2011Zayat, M., Kalb, L., & Wodka, E. L. (2011). Performance pattern differences between children with autism spectrum disorders and attention deficit-hyperactivity disorder on measures of verbal intelligence. Journal of Autism and Developmental Disorders, 41, 17431747. doi: 10.1007/s10803-011-1207-z[Crossref], [PubMed], [Web of Science ®] [Google Scholar]) existed within the current data set. For the WISC-IV, the tests indicated significant differences between Similarities (M = 10.50, SD = 3.18) and Vocabulary (M = 8.10, SD = 3.98); t (47) = 7.55, p < .001, significant differences between Similarities (M = 10.50, SD = 3.18) and Comprehension (M = 6.25, SD = 4.06); t (47) = 11.37, p<.001 and significant differences between Vocabulary (M = 8.10, SD = 3.98) and Comprehension (M = 6.25, SD = 4.06); t (47) = 5.09, p<.001, demonstrating the existence of the pattern found in previous research. Similarly, for the WISC-V, tests indicated significant differences between Similarities (M = 9.77, SD = 3.53) and Vocabulary (M = 8.38, SD = 3.72); t (47) = 4.40, p<.001, significant differences between Similarities (M = 9.92, SD = 3.47) and Comprehension (M = 6.87, SD = 3.74); t (37) = 7.21, p<.001, and significant differences between Vocabulary (M = 8.82, SD = 3.81) and Comprehension (M = 6.87, SD = 3.74); t (37) = 5.27, p<.001, again demonstrating the existence of the pattern. The percentage of participants whose scores followed the distinct pattern of performance are reported in Table 3. A McNemar test showed that the proportions of participants with the distinct pattern of performance on the WISC-IV and on the WISC-V did not significantly differ, p = .227 (two-sided). Additionally, the proportion of participants with the Comprehension subtest as their lowest score on the WISC-IV and on the WISC-V did not significantly differ, p = .344 (two-sided).

Table 3. Percent of participants with distinct performance pattern.

Discussion

As outlined above, it was expected that the change in measurement of verbal intellect from WISC-IV to WISC-V would result in significant composite score changes for individuals with ASD. The results lent support to this notion, as a statistically significant score increase was found for the total sample of participants, despite a statistically significant drop in the Similarities score and a non-significant change in the Vocabulary score. This suggests that the removal of the Comprehension subtest may be an explanatory factor for the improved VCI composite score on the WISC-V. This finding is particularly important in light of the special group validity study data (shown in Table 2), given that this study had a larger sample size than those validity studies and also followed participants longitudinally. The validity study data suggest that verbal comprehension subtest and index scores are similar across administrations, but repeated measurement in the current study has demonstrated otherwise, with a significant index score increase from one administration to the next.

Despite the score change on Similarities holding little practical significance, the statistically significant decrease from WISC-IV to WISC-V was unanticipated and must be acknowledged. Although causality cannot be attributed, one possible explanation for the decline in Similarities scores may be the raised start points on WISC-V, as exposure to low-level items may have provided opportunities for learning on WISC-IV. That is, an examination of the protocols reveals that the age-based start points have changed on WISC-V, with older students beginning the task on higher-level items. Future research could certainly examine whether or not practice with low-level items leads to improved subtest performance.

Importantly, we do not claim that core ASD symptomatology is the sole causal factor in the composite score change, as pragmatic language deficits and executive functioning challenges must also be recognized as possible contributors. With that said, pragmatic language is a rather broad construct and causes of deficits are ill-defined, as the role of various mechanisms (e.g. central coherence, executive control, theory of mind) has not been definitively established for individuals with various diagnostic conditions (Martin & McDonald, 2003Martin, I. & McDonald, S. (2003). Weak coherence, no theory of mind, or executive dysfunction? Solving the puzzle of pragmatic language disorders. Brain and Language, 85, 451466. doi: 10.1016/S0093-934X(03)00070-1[Crossref], [PubMed], [Web of Science ®] [Google Scholar]). As such, while other contributors to challenges with the Comprehension subtest must be considered, examining trends within particular diagnostic groups remains valuable for treatment planning.

Furthermore, the Flynn Effect (Flynn, 1984Flynn, J. R. (1984). The mean IQ of Americans: Massive gains 1932 to 1978. Psychological Bulletin, 95(1), 2951. doi:10.1037/0033-2909.95.1.29[Crossref], [Web of Science ®] [Google Scholar]) must be considered as a contributor to improved performance over time, as this theory posits that the mean intellectual quotient for the general population rises over time, but the hypothesized rate of 0.3-point increase per year for the full-scale intelligent quotient (FSIQ) does not explain the observed mean score change. Moreover, although Flynn’s (1984Flynn, J. R. (1984). The mean IQ of Americans: Massive gains 1932 to 1978. Psychological Bulletin, 95(1), 2951. doi:10.1037/0033-2909.95.1.29[Crossref], [Web of Science ®] [Google Scholar]) original study examined full-scale scores, subsequent studies have examined changes at the index level, and a recent meta-analysis revealed crystallized intelligence, often measured through verbal IQ tasks, to change the least over time (Pietschnig & Voracek, 2015Pietschnig, J. & Voracek, M. (2015). One century of global IQ gains: A formal meta-analysis of the Flynn Effect (1909-2013). Perspectives on Psychological Science, 10(3), 282306. doi: 10.1177/1745691615577701[Crossref], [Web of Science ®] [Google Scholar]). Lastly, the validity studies reported in the WISC-V Technical Manual (Wechsler, 2014Wechsler, D. (2014). WISC-V technical and interpretive manual. Bloomington, MN: NCS Pearson. [Google Scholar]) describe a lower VCI on WISC-V to account for the Flynn Effect. As such, the changes observed during this study should not be attributed to the Flynn Effect alone.

The results of this study indicated that Comprehension remains the subtest of most difficulty for the majority of those with ASD (Table 3), when administered as a supplemental subtest. This raises a concern the new index score may not adequately capture all individuals’ verbal intellectual ability and therefore, clinicians must recognize the utility of the Comprehension subtest for identifying cognitive patterns relevant for diagnosis and treatment. Moreover, it suggests that utilization of alternate or expanded measures may be particularly meaningful for this population. For example, Raiford, Drozdick, Zhang and Zhou (2015Raiford, S. E., Drozdick, L., Zhang, O., & Zhou, X. (2015). Expanded index scores (Technical Report No. 1). San Antonio, TX: NCS Pearson. [Google Scholar]) describe a new ancillary index score that can be used for clinical interpretation; the Verbal Expanded Crystallized Index (VECI), which includes the four available verbal subtests on the WISC-V (i.e. Similarities, Vocabulary, Comprehension, and Information). Future research should examine whether this expanded index is a more appropriate tool for capturing the strengths and weaknesses of those with ASD. Although the reality facing many clinicians on a daily basis is a push for efficiency, the data discussed herein suggest that basing measures of verbal intellect on just two subtests is not appropriate for some patients. When one considers that the Wechsler Abbreviated Scale of Intelligence-Second Edition (WASI-II) has the same number of verbal subtests as the VCI on the WISC-V, there is certainly cause for concern about how comprehensive the measure is, especially for patients with the most complex profiles. With a focus on expediency, important clinical information may be lost.

This study was limited in that it relied upon extant data and had a rather small sample size. With that said, the special group validity studies reported in the WISC-IV (2003) and WISC-V (2014) technical manuals included between 19 and 32 children, which is less than the current sample size, suggesting that studies of this size are relevant for clinical work. A second limitation of this project was that the Comprehension subtest was not administered as a supplemental measure on WISC-V to 10 of the included participants, further reducing the sample size for analysis of the distinct score pattern. Finally, a consistent diagnostic tool was not utilized across neuropsychological evaluations and therefore, verification of participant diagnosis rested on the evaluator’s written assertion of a diagnosis based on diagnostic criteria at the time of evaluation. Although clinical research with extant data provides a meaningful opportunity to investigate trends in assessment, future research with a larger patient sample will provide further information about this phenomenon.

Furthermore, acknowledging the diversity of individuals with ASD, future research should examine this trend across subgroups of children with various levels of functioning (e.g. as defined by the DSM-5 severity levels and specifiers; American Psychiatric Association, 2013American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.[Crossref] [Google Scholar]). In particular, examining this particular score change in those with and without language impairment, similar to the special group validity studies, would provide useful clinical information. It would also be worthwhile to explore the score changes for other relevant diagnostic groups, including individuals with receptive and/or expressive language disorder, as they too may have been more significantly impacted by the change in test structure than the typically developing population. Finally, available demographic information suggested that the included sample of participants lacked racial diversity and therefore, the results may not be applicable to all cultural groups.

With the above limitations acknowledged, the current data do suggest that a clinically relevant score change has occurred with the WISC revision and future research must continue to explore this trend. In the short term, clinicians should continue to administer the Comprehension subtest as a supplemental measure of verbal intellect, as it holds particular value for understanding the cognitive profiles of individuals with ASD. Moving forward, it will be critical to explore how changes in estimates of cognitive ability are impacting service provision, as score increases could result in individuals failing to access needed interventions, if alternate methods of identifying weaknesses are not identified as part of eligibility determination.

References

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