We read with great interest the study published by Mukhopadhyay et al.[1] The article is interesting and promising in the lagging field of pediatric
neuropsychological assessment, especially in the Indian context. This study addresses an
important and growing area of enquiry in our field related to the identification of
learning-related difficulties in children with neurodevelopmental disorders (NDDs). The
developed battery appears to be comprehensive, with relevant domains.Given the foregoing, it is unfortunate that Mukhopadhyay et al.[1] did not document the theoretical framework used to generate culturally appropriate
items, method, and criteria for (sub)domain selection, the time required to complete the task,
and its ecological validity.NDDs include a variety of conditions that are unique in terms of clinical features,
comorbidity, and neurocognitive correlates. Therefore, developing culturally appropriate items
and tasks that could be sensitive across different NDDs with varying ages is a challenging
task. Information regarding the theoretical framework used to generate culturally appropriate
items and item validity is missing from the article, and this piece of information could be
useful for conducting similar research in the future.Cognitive skills are systematically and differentially correlated with academic skills in the
six domains of learning disabilities (LDs).[2] Similarly, a differential neurocognitive profile has been reported in autism spectrum
disorder (ASD),[3] attention deficit hyperactivity disorder (ADHD),[4-5] communication
disorder (CD),[6] and specific learning disorder (SLD).[2] It is apparent from the article that several core cognitive skills have not been
incorporated/included in the battery, such as processing speed, rapid naming speed, verbal
working memory, approximate number skills, executive functioning, fluency, social cognition,
and episodic memory. Therefore, we might not be able to tap these crucial cognitive components
while using this battery and probably miss certain vital information that is preserved or more
impaired in children with NDDs. Deficits in working memory and processing speed are found to
be shared across different LDs as well as ADHD.[2, 7] Further, social cognition and encoding-related problems could be affected
differently in children with various NDDs including ADHD, ASD, and SLD.[8-9] Deficits in social reciprocity and organizational resources such as encoding
might tax perceptual and executive resources in children with certain NDD.Further, the variability in the nature of the tasks (i.e., open-ended, semi-open-ended, and
closed-ended), as well as the number of items included in respective domains, might pose
further complications in establishing the sensitivity and specificity of the developed tool.
Several crucial cognitive skills are grouped under a single subdomain, and their descriptions
appear to be overinclusive. For example, auditory attention also assesses response inhibition;
visual reasoning includes perceptual reasoning, concept formation, and problem solving. In
NDDs, using the same task to assess multiple brain functions will adversely affect the profile
analysis, whereas domain-specific sensitive tasks will be more useful to assess neurocognitive
and academic functions.Several other important features of this paper are of concern, such as the total time taken
to administer the task and the smaller sample in the clinical groups. This battery will be
used to assess scholastic backwardness in children with NDDs. The majority of these children
will have marked difficulty in expressive and receptive speech, socialization, and attention
and concentration, in addition to sensory impairment. In this regard, it is crucial to use a
quick and easy method to evaluate cognitive and scholastic skills in these children. Further,
it is difficult to generalize the obtained findings due to the small sample size, as in this
study, the age ranged from 4.5 to 9.5 years and the children were from five different
categories, such as typically normal developing, ADHD, SLD, LD, and ASD. Therefore, a larger
sample (including normal and clinical subjects) is required in order to assess the usefulness
of the tool in different NDDs.Considerable attempts have been made to develop culture-specific tools to identify learning
difficulty in Indian contexts.[10] However, the majority of these tools cannot be used judiciously due to a lack of
normative data. Therefore, future studies are warranted to develop robust normative data for
these tools. There is a pressing need to connect knowledge across studies and achieve
consensus regarding their specific usefulness in the Indian context. In our opinion,
developing culture-specific tests for scholastic problems is a long and tedious process that
involves challenges in training and research, especially when we have an acute shortage of
mental health services in the country. In this regard, we appreciate the efforts of the
investigators. However, the several issues we listed need to be considered to make this tool
more useful.
Authors: Lauren M McGrath; Bruce F Pennington; Michelle A Shanahan; Laura E Santerre-Lemmon; Holly D Barnard; Erik G Willcutt; John C Defries; Richard K Olson Journal: J Child Psychol Psychiatry Date: 2010-12-03 Impact factor: 8.982