High Prevalence of Dysgraphia in Elementary Through High School Students With ADHD and Autism

OBJECTIVE

Prevalence of dysgraphia by age across all grade levels was determined in students with ADHD or autism.

METHOD

Referred children with normal intelligence and ADHD-Combined, ADHD-Inattentive, or autism ( N = 1,034) were administered the Developmental Test of Visual-Motor Integration (VMI) and Wechsler Intelligence Scale for Children (WISC).

RESULTS

VMI and WISC Coding scores were significantly lower than IQ and the normal mean of 100 for all diagnoses. More than half (59%) had dysgraphia, and 92% had a weakness in graphomotor ability relative to other abilities. Dysgraphia prevalence did not differ between diagnostic or age groups (6-7 years, 56%; 8-10 years, 60%; and 11-16 years, 61%).

CONCLUSION

Dysgraphia is common at all ages in children and adolescents with ADHD and autism. Accommodations and strategies for addressing this problem are discussed.

Test of the Definition of Learning Disability Based on the Difference between IQ and Achievement

A learning disability is commonly defined as a discrepancy between IQ and achievement. This has been criticized for identifying too many children as having a learning disability who have high IQs and average academic achievement. Such overidentification as actually occurred was assessed in 473 referred children (8–16 years, M= 10, SD = 2) with normal intelligence. Learning disability was defined as a significant discrepancy ( p<.05) between predicted and obtained achievement in reading, mathematics, or written expression on the Wechsler Individual Achievement Test. Predicted achievement was based on the child's WISC-III Full Scale IQ. Overidentification was considered to occur when a child scored at or above age level in reading, mathematics, and writing but still had a significant discrepancy between predicted and obtained achievement by virtue of a high IQ. Learning disability was diagnosed in 312 (66%) of the children. There was no overidentification because all children had one or more WIAT scores below the normative level for their age, i.e., < 100. Further, only 7% of the children were identified with a learning disability based on a WIAT score in the 90s. These children had a mean IQ of 123 and were rated by their teachers and parents as having learning problems.

Learning, attention, writing, and processing speed in typical children and children with ADHD, autism, anxiety, depression, and oppositional-defiant disorder

Learning, attention, graphomotor, and processing speed scores were analyzed in 149 typical control children and 886 clinical children with normal intelligence. Nonsignificant differences were found between control children and children with anxiety, depression, and oppositional-defiant disorder. Control children performed better than children with ADHD and autism in all areas. Children with ADHD and autism did not differ, except that children with ADHD had greater learning problems. Attention, graphomotor, and speed weaknesses were likely to coexist, the majority of children with autism and ADHD had weaknesses in all three areas, and these scores contributed significantly to the prediction of academic achievement.

WISC-IV and WIAT-II Profiles in Children With High-Functioning Autism

Children with high-functioning autism earned above normal scores on the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) Perceptual Reasoning and Verbal Comprehension Indexes and below normal scores on the Working Memory and Processing Speed Indexes and Wechsler Individual Achievement Test-Second Edition (WIAT-II) Written Expression. Full Scale IQ (FSIQ) and reading and math scores were similar to the norm. Profiles were consistent with previous WISC-III research, except that the new WISC-IV motor-free visual reasoning subtests (Matrix Reasoning and Picture Concepts) were the highest of the nonverbal subtests. The WISC-IV may be an improvement over the WISC-III for children with high-functioning autism because it captures their visual reasoning strength, while identifying their attention, graphomotor, and processing speed weaknesses. FSIQ was the best single predictor of academic achievement.

Diagnosing children's writing disabilities: different tests give different results

Writing problems are common in children with clinical disorders. However, there are significant intra-individual differences between the ability to spell words, construct sentences, and compose text. Therefore, achievement tests measuring different writing skills may not be consistent in identifying children who have these various writing disabilities. Our study compared scores on the Woodcock-Johnson Written Language subtests (which measure the ability to produce single words and single sentences) with scores on the Wechsler Individual Achievement Test Written Expression subtest (which assesses compositional writing skills) in 54 children referred by their teachers to a school psychologist for writing problems. The Woodcock-Johnson only identified 35% of children as having significant writing problems, whereas the Wechsler test identified 78%. Our study suggests that the latter is more likely than the Woodcock-Johnson to identify students who have problems in compositional writing.

Similarities and differences in Wechsler Intelligence Scale for Children--Third Edition (WISC-III) profiles: support for subtest analysis in clinical referrals

Our study supports the reliability and validity of profile analysis in children with neurobiological disorders. Three mutually exclusive WISC-III profiles were identified that characterized the majority of children with autism (low coding or Freedom from Distractibility Index with low Comprehension), attention deficit hyperactivity disorder and learning disability (low Coding or FDI without low comprehension), and brain injury (low Performance without low Coding or FDI). The profiles suggest attention, writing, and performance speed deficits in autism, ADHD, and LD; global visual-motor problems in brain injury; and specific difficulty with language comprehension and social reasoning in autism. Children with anxiety, depression, and behavior disorders did not exhibit distinct profiles. Our profile analysis is based on the simple rank ordering of standard scores. The profiles are clinically useful because they may alert clinicians to certain diagnostic possibilities, they reveal characteristic strengths and weaknesses that have implications for educational intervention, and they are consistent with preliminary WISC-IV data.

Ability profiles in children with autism: influence of age and IQ

To understand the effect of IQ and age on ability in children with autism, psychological data were analyzed for 164 3- to 15-year-olds with autism (IQs 14-143). As age increased, so did IQ, which probably reflects both an actual increase in IQ over time and the likelihood that brighter children are diagnosed later. Early in life, 67 percent had normal motor and delayed speech milestones. Verbal IQ continued to lag behind non-verbal IQ during the preschool years. By school age, the gap between verbal and non-verbal IQs had closed. Visual reasoning exceeded graphomotor scores for all children, and surpassed IQ for most. Graphomotor scores were significantly below IQ for both high-IQ groups. For school-age children with low IQs, math, spelling, and writing scores were consistent with IQ and reading was above IQ. School-age children with high IQs had average reading, math, and spelling scores and a weakness in writing.

Learning disabilities and ADHD: overlapping spectrumn disorders

Clinical and psychoeducational data were analyzed for 119 children ages 8 to 16 years who were evaluated in a child diagnostic clinic. A learning disability (LD) was present in 70% of the children with attention-deficit/hyperactivity disorder (ADHD), with a learning disability in written expression two times more common (65%) than a learning disability in reading, math, or spelling. Children with LD and ADHD had more severe learning problems than children who had LD but no ADHD, and the former also had more severe attention problems than children who had ADHD but no LD. Further, children with ADHD but no LD had some degree of learning problem, and children with LD but no ADHD had some degree of attention problem. Results suggest that learning and attention problems are on a continuum, are interrelated, and usually coexist.