Relationships between neuropsychological measures of executive function and behavioral measures of ADHD symptoms and comorbid behavior

Archives of Clinical Neuropsychology 21 (2006) 383–394

Relationships between neuropsychological measures of executive function and behavioral measures of ADHD symptoms and comorbid behavior Solveig Jonsdottir a,∗ , Anke Bouma b , Joseph A. Sergeant c , Erik J.A. Scherder d b

a Psychological Health Services, Landspitali-University Hospital, Reykjavik, Iceland Department of Clinical and Developmental Psychology, Rijksuniversiteit Groningen, Groningen, The Netherlands c Department of Clinical Neuropsychology, Vrije Universiteit, Amsterdam, The Netherlands d Institute of Human Movement Sciences, Rijksuniversiteit Groningen, Groningen, The Netherlands

Accepted 8 May 2006

Abstract Objective: The aim of this study was to examine the relationship between executive functions (EFs), as measured by neuropsychological tests, and symptoms of attention deficit hyperactivity disorder (ADHD) and comorbid behavior, as rated by parents and teachers. As intelligence and language ability are important covariates they were also assessed. Method: The sample consisted of 43 children aged 7–11 years who were referred for neuropsychological assessment at a tertiary clinical facility. Most of the children had the diagnosis of ADHD combined or inattentive type. Different aspects of EFs were assessed. Results: EFs were not significantly related to symptoms of ADHD, but only to comorbid symptoms of depression and autistic symptomatology. Language ability rather than EFs best predicted teacher ratings of inattention. Conclusions: The results of the study do not support the EF theory of ADHD. The importance of screening for comorbid language disorders in children referred for ADHD is emphasized. © 2006 National Academy of Neuropsychology. Published by Elsevier Ltd. All rights reserved. Keywords: Attention deficit hyperactivity disorder; Executive function; Neuropsychology; Behavioral ratings; Children; Language

1. Introduction Attention deficit hyperactivity disorder (ADHD) is the most prevalent neurobehavioral condition of childhood, affecting a substantial proportion of the population around the world (Faraone, Sergeant, Gillberg, & Biederman, 2003). The disorder is characterized by age inappropriate symptoms of inattention, motor restlessness and impulsive behavior (DSM-IV-TR; American Psychiatric Association, 2000). The DSM-IV delineates three subtypes of the disorder: the predominantly inattentive (ADHD-IA), the predominantly hyperactive-impulsive (ADHD-HI), and the combined (ADHD-C). Children with ADHD place a heavy financial burden on educational, social and clinical services and some are impaired for lifetime. In view of the prevalence and financial cost of ADHD and its possible overdiagnosis, it is imperative that measures be used in the diagnostic process that are refined and specific (Sergeant, Geurts, & Oosterlaan, 2002). ∗ Correspondence to: Psychological Health Services, Landspitali-University Hospital, Grens´ as, 108 Reykjav´ık, Iceland. Tel.: +354 543 1000; fax: +354 543 9105. E-mail address: [email protected] (S. Jonsdottir).

0887-6177/$ – see front matter © 2006 National Academy of Neuropsychology. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.acn.2006.05.003

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While the etiology of ADHD remains unknown at this time, most recent neuropsychological theories have targeted deficient executive function (EF) as being the main characteristic of the disorder (Barkley, 1997, 2003; Pennington & Ozonoff, 1996; Willcutt, Doyle, Nigg, Faraone, & Pennington, 2005). Executive functions have been defined as “neurocognitive processes that maintain an appropriate problem solving set to attain a future goal” (Welsh & Pennington, 1988). A recent meta-analysis (Willcutt et al., 2005) showed that, while EF deficits are prevalent in ADHD populations, they are “neither necessary nor sufficient to cause all cases of ADHD”. A recent review of studies in the area of EF deficits in children with neurodevelopmental disorders has shown that they are not specific to ADHD (Sergeant et al., 2002). The strongest and most consistent EF deficits in ADHD have been found to be on measures of response inhibition, vigilance, working memory (WM), and planning (Willcutt et al., 2005). It has been suggested that EFs rely on structures in the frontal cortex (e.g. Max et al., 2005), and structural brain imaging studies have shown that children with ADHD tend to have smaller volumes in various areas of the brain including the dorsolateral prefrontal cortex (Seidman, Valera, & Makris, 2005). A dysfunctional frontostriatal system has also been implicated in other neurodevelopmental disorders such as autism, depression, obsessive compulsive disorder, schizophrenia, and Tourette’s syndrome (Bradshaw & Sheppard, 2000). ADHD is highly comorbid with other disorders, mainly externalizing disorders like oppositional defiant disorder (ODD) and conduct disorder (CD), internalizing disorders like anxiety and depression and language related disorders like dyslexia and language impairment (LI). Research has shown that the three subtypes of ADHD have differing types and degrees of comorbidity. Cognitive and language related disorders and internalizing problems have mainly been associated with inattention symptoms rather than hyperactivity/impulsivity symptoms (e.g. Chhabildas, Pennington, & Willcutt, 2001; Harrier & Deornellas, 2005; Willcutt, Pennington, Chhabildas, Friedman, & Alexander, 1999). There has been relatively little research on the relationship between ADHD and its comorbid disorders with the executive function system (e.g. Oosterlaan, Scheres, & Sergeant, 2005; Sarkis, Sarkis, Marshall, & Archer, 2005), and research has shown that there is often considerable lack of agreement between the various behavioral and cognitive measures conventionally used in the diagnostic process of children with ADHD. Naglieri, Goldstein, Delauder, and Schwebach (2005) examined the relationships between the Wechsler Intelligence Scale for Children Third Edition (WISC-III) and the Cognitive Assessment System (CAS), with Conners’ Behavior Rating Scale and Conners’ Continuous Performance Test (CPT) in a sample of children with attention, emotional and behavioral problems. The results showed that there were generally low and non-significant correlations between parent and teacher behavioral ratings and performance on measures purported to be sensitive to ADHD symptoms. The authors concluded “practitioners should expect to find a lack of consistency between the scores provided by the measures examined and should be conservative of their use in clinical settings”. One reason for Naglieri and co-workers’ findings might possibly be that the measures used in their study are not specific enough for ADHD problems. The Conners’ behavioral rating scale used in their study, does not, for example, differentiate between inattention symptoms and hyperactivity/impulsivity symptoms and research has shown that neuropsychological impairment is mainly related to inattention but not to hyperactivity/impulsivity in children with ADHD (Chhabildas et al., 2001; Harrier & Deornellas, 2005). One of the behavioral instruments often used, when diagnosing children with ADHD, is the Behavior Assessment System for Children (BASC; Reynolds & Kamphaus, 1992). The BASC is a multi-method, multi-dimensional instrument designed to evaluate the behavior and emotions of children, including symptoms of ADHD. One advantage of the BASC, compared to other similar broadband behavioral instruments, is that it measures inattention symptoms and hyperactivity/impulsivity symptoms on two separate scales. Research has demonstrated the usefulness of the BASC in the diagnostic process of ADHD and shown that it is especially well suited in differentiating between subtypes of ADHD (e.g. Jarratt, Riccio, & Siekierski, 2005; Ostrander, Weinfurt, Yarnold, & August, 1998; Vaughn, Riccio, Hynd, & Hall, 1997). In addition to ADHD symptoms, the BASC also evaluates symptoms of aggression, conduct problems, anxiety, depression, somatization, learning problems, atypical behavior (autistic symptomatology) and withdrawal. To our knowledge, parent and teacher ratings on the BASC have not thus far been examined in relation to performance on EF tasks. A recently developed neuropsychological battery for children, the NEPSY (Korkman, Kirk, & Kemp, 1998), examines five domains of neuropsychological functioning in children. One of these is called Attention/Executive Functions, which is purported to be sensitive to ADHD symptoms. There have not been many validation studies comparing the NEPSY with behavioral measures (e.g. Schmitt & Wodrich, 2004). The NEPSY manual (Korkman et al., 1998) reports one study using the Devereux Scales of Mental Disorders (DSMD; Naglieri, LeBuffe, & Pfeiffer, 1994). The sample used was a mixed one of 10 non-clinical children and 13 children diagnosed with either ADHD or LD. The results

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of that study showed that DSMD ratings of attention and conduct problems were negatively correlated with Attention/Executive Functions Core Domain Scores on the NEPSY. The study also showed that internalizing problems were generally not related to neuropsychological functioning. Korkman, Jaakkola, Ahlroth, Pesonen, and Turunen (2004) examined the validity of a newly developed parental rating scale, Five to Fifteen (FTF), in detecting developmental disorders in 5-year-old children using the NEPSY as the external criterion measure. The FTF was designed to assess ADHD and comorbid conditions in 5- to 15-year-old children (Kadesj¨o et al., 2004). The results of this study showed that the NEPSY Attention/Executive Functions Domain of the NEPSY and the Attention and Impulsivity Domain of the FTF were only almost significantly related. This study examined the association between parent and teacher ratings of ADHD symptoms and comorbid behavior and performance on EF tasks. This is the first study on this relationship using broadband behavioral ratings that separate inattention and hyperactivity/impulsivity symptoms. The different aspects of EF examined were planning, vigilance and WM. The neuropsychological instruments used to assess EF, were the Tower and the Visual Attention subtests from the NEPSY and the Number Recall and Word Order subtests from the Kaufman Assessment Battery for Children (K-ABC; Kaufman & Kaufman, 1983). The behavioral measures used were the Parent Rating Scale (PRS) and the Teacher Rating Scale (TRS) of the BASC. Based on the existing literature it was expected that EF measures would correlate with parent and teacher ratings of inattention and hyperactivity/impulsivity. It has been demonstrated previously that measures of EF tend to correlate with IQ (e.g. Arffa, Lovell, Podell, & Goldberg, 1998; Harrier & Deornellas, 2005; Mahone et al., 2002), and it has been debated if IQ should be controlled for in studies on EF. It has been argued that it is a stronger case when EF differences exist after taking IQ into account (Sergeant et al., 2002). In view of the known relationship between EF and IQ, we assessed intellectual ability with the K-ABC. As language disorders have been found to be a highly prevalent comorbidity in ADHD (e.g. Cohen et al., 2000; Jonsdottir, Bouma, Sergeant, & Scherder, 2005), language ability was assessed with the Test of Language Development (TOLD; Hammill & Newcomer, 1988). 2. Method 2.1. Participants The sample consisted of 43 children (30 boys and 13 girls), aged 7–11 years (mean age was 9.27 years S.D. = 1.34). Full Scale IQ was 99.88 (S.D. = 11.90). All the children had been referred for neuropsychological assessment because of serious behavioral and/or learning problems at the Department of Child and Adolescent Psychiatry of the LandspitaliUniversity Hospital in Reykjavik, which is a tertiary facility serving the whole population of Iceland. Most of the children had the diagnosis of either ADHD combined or inattentive subtype. The diagnostic procedures used were an in-depth interview with the parents based on DSM-IV criteria, and parent/teacher ratings on the Icelandic versions of the Child Behavior Checklist (CBCL; Achenbach, 1991; Hannesdottir, 2002) and the ADHD rating scale (Magnusson, Smari, Gretarsdottir, & Thrandardottir, 1999). 2.2. Instruments 2.2.1. The NEPSY: a developmental neuropsychological assessment The NEPSY: a developmental neuropsychological assessment (Korkman et al., 1998) is a comprehensive measure of neuropsychological functioning in children aged 3–12 years. It has been validated for use with children diagnosed with learning disabilities, ADHD, autistic disorders, and speech and language impairment and is designed for use in a variety of cultural and ethnic groups. The NEPSY is divided into five functional domains. The tests used in this study are two subtests from the Attention/Executive Functions Domain: the Tower test and the Visual Attention test. The Tower test is designed to assess the EFs of non-verbal planning, monitoring, self-regulation, and problem solving. The child moves three colored balls to target positions on three pegs in a prescribed number of moves. The Tower test is based on the Tower of London test (ToL; Shallice, 1982) that has been extensively used in the neuropsychological literature to assess EFs. Studies have suggested that performance on the ToL relies to a large extent on the functioning of the frontostriatal system (Beauchamp, Dagher, Aston, & Doyon 2003; Owen, 1997). The Visual Attention test is designed to measure selective and sustained attention and assesses the speed and accuracy with which a child is able to focus selectively on and maintain attention to visual targets within an array. The child is penalized for both omission

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and commission errors, thus, in addition to vigilance, the test is also sensitive to inhibition. Standard scores with a mean of 10 and S.D. of 3 are used for the NEPSY subtests. 2.3. Kaufman Assessment Battery for Children The Kaufman Assessment Battery for Children (Kaufman & Kaufman, 1983) is an individually administered measure of intelligence and achievement intended for children aged 2.5–12.5 years. It is based on research and theory in cognition and neuropsychology and is designed to measure ability (intelligence) on the basis of the processing style (sequential or simultaneous), required to solve tasks. The K-ABC has been widely used in the literature to assess cognitive function in children. Two subtests from the Sequential Processing scale: Number Recall and Word Order were combined to assess the EF of verbal WM (see Jonsdottir et al., 2005). The K-ABC uses standard scores with a mean of 100 and S.D. of 15 for its composites and a mean of 10 and S.D. of 3 for its subtests. 2.4. Test of Language Development The Test of Language Development (Hammill & Newcomer, 1988) is a comprehensive measure of structural language designed to assess verbal ability in children. The TOLD is comprised of several subtests that are combined to make composite scores of a Spoken Language Quotient (SLQ), receptive language, expressive language, semantics and syntax. The Icelandic version of the TOLD (S´ımonard´ottir & Guðmundsson, 1996) was used here. The TOLD uses standard scores with a mean of 100 and S.D. of 15 for its composites and a mean of 10 and S.D. of 3 for its subtests. 2.4.1. The Behavior Assessment System for Children (BASC) The Behavior Assessment System for Children (Reynolds & Kamphaus, 1992) is a well-validated comprehensive multi-dimensional measure designed to evaluate various externalizing, internalizing and school problems in children and adolescents aged 2.5–18 years. It measures both adaptive and problematic dimensions, as well as behavior linked to ADHD. The Parent Rating Scale of the BASC has nine clinical scales. Three scales called Hyperactivity (including both hyperactivity and impulsivity items), Aggression, and Conduct Problems measure externalizing problems. Three scales called Anxiety, Depression, and Somatization, assess internalizing problems. Three additional scales are called Attention Problems, Atypicality and Withdrawal. The Teacher Rating Scale has, in addition to the aforementioned nine scales, a clinical scale called Learning Problems. The child version of the BASC (ages 6–11) was used in this study. Parents and teachers rated 138 and 148 symptoms, respectively. Symptoms are rated on a 4-point scale of frequency (never = 0, sometimes = 1, often = 2, and almost always = 3). Internal consistency coefficients (Kjartansdottir, 2002) for the BASC Icelandic-language version of the PRS child form range from .52 (Atypicality) to .90 (Depression). The TRS child form correspondingly has coefficients that range from .69 (Withdrawal) to .93 (Aggression). 2.5. Procedure The NEPSY subtests, the K-ABC, and the TOLD were all administered to the participants by a licensed clinical child neuropsychologist according to the standard testing procedures. In addition, the children’s parents/teachers filled out the BASC versions for ages 6–11. 2.6. Statistical analyses To analyse the group’s deviation from the standardized mean on tests of EF, the K-ABC and on the TOLD, t-tests were employed. To compare parent/teacher ratings of the clinical group on the BASC with those of a normal school sample, t-tests were used. Effect sizes (eta-squared: η2 ) were calculated, that is small .01, medium .06, and large .14 (Cohen, 1988). In addition, correlational analyses were performed to investigate the relationships between EFs, intelligence and language measures. Furthermore, correlational analyses were performed to examine the relationships between parent/teacher ratings on the BASC and performance on EF tasks, intelligence and language ability, both with and without intelligence controlled.

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Finally stepwise regression analyses were executed to analyse which cognitive variables best predicted parent/teacher ratings on the BASC. Results were analysed utilizing SPSS version 11.0 for Windows. 3. Results Means and standard deviations for age and the BASC TRS and PRS scores are presented in Table 1. As the BASC has not been standardized in the Icelandic population, the means and standard deviations for a normal Icelandic school sample of 115 children are provided for comparison (Jonsdottir et al., submitted for publication). The results show that the clinical group examined in this study was rated significantly higher than the normal comparison group on the Attention Problems and Hyperactivity subscales of the PRS and TRS of the BASC. In addition, the clinical group also scored significantly higher than the comparison group on most other clinical scales. The greatest difference between the groups, according to both parents and teachers, is on the Attention Problems subscale, with large effects sizes (η2 = .38 and .34, respectively). Table 2 shows the means and standard deviations for the NEPSY Tower and Visual Attention subtests, the verbal WM composite, the K-ABC full-scale IQ (Mental Processing Composite, MPC), Sequential Processing, Simultaneous Processing and the full-scale language ability score (Spoken Language Quotient, SLQ) of the TOLD. The results showed that the clinical group scored lower than expected on the Tower test, the Visual Attention test, and on verbal WM. The results also showed that the clinical group has an average full-scale IQ. However, the Sequential Processing score of the clinical group is lower than the expected group’s mean, but the Simultaneous Processing score of this group is higher than expected. Moreover, the group’s total language ability score was lower than would be expected. Table 3 shows the Pearson correlations between the three executive measures (the Tower test, the Visual Attention test and verbal WM), and the relationship between the EF tasks and the K-ABC MPC, Sequential Processing and Simultaneous Processing scales, and the TOLD SLQ scale. Of the three EF tasks, only verbal WM appeared to be Table 1 Comparison of means and S.D.s for BASC Teacher Rating Scale (TRS) and Parent Rating Scale (PRS)

Age

Clinical group (n = 43)

Normal controls (n = 115)

Mean

Mean

S.D.

S.D.

F

d.f.

p

η

9.27

1.34

9.05

1.65

.65

1.156

.42

.00

BASC-TRS Hyperactivity Aggression Conduct Problems Anxiety Depression Somatization Attention Problems Learning Problems Atypicality Withdrawal

14.23 11.87 3.36 6.15 8.56 4.38 14.28 13.33 5.56 7.00

11.14 10.19 3.59 3.81 6.27 4.34 5.29 5.76 4.19 4.36

7.03 7.15 1.68 2.78 3.11 1.83 6.03 5.62 1.28 3.49

7.02 7.88 2.35 3.47 3.88 2.85 4.96 5.10 2.38 3.37

22.24 8.96 11.16 26.20 40.99 17.67 78.07 62.43 62.04 27.14

1.152 1.152 1.152 1.152 1.152 1.152 1.152 1.152 1.152 1.152

.000 .003 .001 .000 .000 .000 .000 .000 .000 .000

.13 .06 .07 .15 .21 .10 .34 .29 .29 .15

BASC-PRS Hyperactivity Aggression Conduct Problems Anxiety Depression Somatization Atypicality Withdrawal Attention Problems

10.00 11.49 4.65 12.09 12.26 7.33 5.51 5.42 12.12

5.44 4.66 3.13 6.13 7.71 5.00 3.86 2.68 3.61

5.70 7.81 2.21 7.67 5.10 4.28 2.36 5.36 5.71

3.84 3.88 2.15 4.50 4.91 3.03 2.25 3.14 3.64

30.79 25.21 31.03 24.57 47.66 21.63 40.40 .01 97.37

1.156 1.156 1.156 1.156 1.156 1.156 1.156 1.156 1.156

.000 .000 .000 .000 .000 .000 .000 .91 .000

.17 .14 .17 .14 .23 .12 .21 .00 .38

Note. BASC, Behavior Assessment System for Children; TRS, Teacher Rating Scale; PRS, Parent Rating Scale. BASC values are raw scores. Normal comparison group is an Icelandic school sample of 115 children.

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Table 2 Means and S.D.s for tests of executive function, Kaufman Assessment Battery for Children and Test of Language Development Mean Tests of executive function Tower Visual Attention Verbal Working Memory Kaufman Assessment Battery for Children (K-ABC) Mental Processing Composite (MPC) Sequential Processing Simultaneous Processing Test of Language Development (TOLD) Spoken Language Quotient (SLQ)

S.D.

t

d.f.

p

7.90 8.90 8.66

2.61 2.77 2.37

−5.20 −2.51 −3.69

41 39 42

.000 .016 .001

99.88 93.26 104.51

11.90 12.56 11.10

−.06 −3.52 2.67

42 42 42

ns .001 .011

92.05

18.71

−2.69

40

.011

Note. K-ABC and TOLD values are standard scores (mean of 100, S.D. of 15). Executive function values are standard scores (mean of 10, S.D. of 3).

significantly related to Tower. Moreover, the different EF functions were significantly related to all IQ measures, except the Visual Attention test was not related to the Sequential Processing scale. Only verbal WM was significantly related to the language test, the TOLD. The results further showed that language ability as measured with the TOLD is significantly related to intelligence as measured with the K-ABC (r = .51, p = .001). Table 4 shows the Pearson correlations between the BASC TRS and PRS and performance on the Tower test, the Visual Attention test, verbal WM, K-ABC and TOLD. The major finding is that there were no significant relationships between teacher rated hyperactivity symptoms and EFs, IQ and language. There were no significant correlations between parent rated symptoms of ADHD (Hyperactivity, Attention Problems) and the cognitive measures. In contrast, teacher rated symptoms of inattention were significantly related to the Tower test (r = −.38, p = .02), the K-ABC full-scale IQ (r = −.33, p = .04), simultaneous processing (r = −.36, p = .03), and language (r = −.38, p = .02). Another major finding is that there were significant correlations between teacher rated Learning Problems and all three EF measures: Tower (r = −.33, p = .04), Visual Attention (r = −.46, p = .004), and verbal WM (r = −.49, p = .002). Teacher rated Learning Problems were significantly and negatively related to intelligence (r = −.62, p = .000), and language ability (r = −.67, p = .000). Interestingly, teacher rated Atypicality and Depression was significantly and negatively related to the Tower test (r = −.43, p = .007 and r = −.38, p = .02, respectively) and teacher rated Anxiety was significantly and negatively related to the Visual Attention test (r = −.37, p = .03). The only significant relationship on the PRS was between Conduct Problems and the Visual Attention test (r = −.32, p = .05). In order to examine to what extent EFs and behavioral variables were due to IQ, partial correlations were run with IQ as a covariate (see Table 5). When the influence of IQ on EFs was controlled, only associated ADHD behavior was related to executive functioning. Teacher rated Atypicality and Depression related significantly and negatively Table 3 Pearson Correlations between tests of executive function, intelligence and language development NEPSY Tower Tower Visual Attention Verbal WM

1

K-ABC Vis. Att. .04 1

TOLD

V. WM

MPC

Seq. Pr.

Sim. Pr.

SLQ

.42**

.43**

.41**

.36*

.24

.44** .83**

.24 .95**

.51** .58**

.13 .31 .48**

1

Note. NEPSY, A Developmental Neuropsychological Assessment; K-ABC, Kaufman Assessment Battery for Children; TOLD, Test of Language Development; Vis. Att., Visual Attention; V. WM, Verbal Working Memory; MPC, Mental Processing Composite; Seq. Pr., Sequential Processing; Sim. Pr., Simultaneous Processing; SLQ, Spoken Language Quotient. * Correlation is significant at the .05 level (2-tailed). ** Correlation is significant at the .01 level (2-tailed).

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Table 4 Pearson correlations between BASC TRS and PRS and performance on tests of attention/executive function, intelligence and language development Tower

Vis. Att.

V. WM

MPC

Seq. Pr.

Sim. Pr.

SLQ

BASC-TRS Hyperactivity Aggression Conduct Problems Anxiety Depression Somatization Attention Problems Learning Problems Atypicality Withdrawal

−.29 −.09 −.14 −.26 −.38* −.31 −.38* −.33* −.43** −.16

−.03 −.02 −.07 −.37* −.19 −.16 −.21 −.46** −.32 −.16

.14 .05 −.07 −.07 −.17 −.10 −.19 −.49** −.04 −.29

.01 −.00 −.14 −.16 −.09 −.09 −.33* −.62** −.09 −.11

.15 .09 −.07 −.08 −.09 −.08 −.19 −.57** −.05 −.21

−.10 −.07 −.17 −.19 −.06 −.09 −.36* −.54** −.11 −.01

.11 .17 .06 −.29 .01 −.16 −.38* −.67** .04 −.26

BASC-PRS Hyperactivity Aggression Conduct Problems Anxiety Depression Somatization Atypicality Withdrawal Attention Problems

−.27 −.18 −.15 −.16 −.29 −.16 −.06 −.06 −.10

−.24 −.17 −.32* .02 .05 −.08 −.03 .11 .07

−.15 −.16 −.06 −.11 −.11 −.07 −.23 −.05 −.25

−.23 −.15 −.12 −.07 −.09 −.11 −.03 −.02 −.16

−.08 −.07 −.01 −.10 −.04 −.06 −.16 −.06 −.21

−.30 −.18 −.19 −.04 −.11 −.13 .07 .02 −.11

.09 .21 .16 −.08 .09 .02 −.01 .26 −.22

Note. Vis. Att., Visual Attention; MPC, Mental Processing Composite (full scale intelligence), Seq. Pr., Sequential Processing; Sim. Pr., Simultaneous Processing; V. WM, Verbal Working Memory; SLQ, Spoken Language Quotient; BASC, Behavior Assessment System for Children; TRS, Teacher Rating Scale, PRS, Parent Rating Scale. Bold fonts for significant correlations (* p < .05; ** p < .01).

Table 5 Pearson correlations between BASC TRS and PRS and tests of executive function controlling for intelligence Tower

Visual Attention

Verbal WMa

BASC-TRS Hyperactivity Aggression Conduct Problems Anxiety Depression Somatization Attention Problems Learning Problems Atypicality Withdrawal

−.32 −.09 −.09 −.22 −.37* −.32 −.28 −.09 −.43** −.13

−.08 −.05 −.04 −.34* −.19 −.17 −.10 −.25 −.34* −.15

.25 .11 .06 .10 −.21 −.04 .07 −.15 .04 −.37*

BASC-PRS Hyperactivity Aggression Conduct Problems Anxiety Depression Somatization Atypicality Withdrawal Attention Problems

−.20 −.13 −.11 −.14 −.27 −.14 −.04 −.04 −.04

−.19 −.15 −.32* .05 .06 −.09 −.09 .11 .15

−.05 −.13 −.03 −.10 −.09 .01 −.35* −.10 −.26

Note. NEPSY, A Developmental Neuropsychological Battery; BASC, Behavior Assessment System for Children; TRS, Teacher Rating Scale, PRS, Parent Rating Scale. Bold fonts for significant correlations (* p < .05; ** p < .01). a K-ABC Nonverbal Intelligence Scale was used to control for intelligence.

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Table 6 Stepwise regression analyses for cognitive variables predicting ratings on BASC TRS and PRS Variable TRS Depression Tower TRS Attention Problems SLQ TRS Learning Problems SLQ MPC TRS Atypicality Tower

Unstandardised coefficient (B)

t-Value

p-Value

−.89

−2.07

.05

−.12

−2.52

.02

−.13 −.20

−2.99 −2.97

.005 .006

−.72

−2.73

.01

F-Value

p-Value

4.29

.05

6.34

.02

18.62

.000

7.45

.01

Note. BASC, Behavior Assessment System for Children; TRS, Teacher Rating Scale; PRS, Parent Rating Scale; SLQ, Spoken Language Quotient; MPC, Mental Processing Composite. Predictors in the model: Tower, Visual Attention, Verbal Working Memory, MPC, and SLQ.

with the Tower test (r = −.43, p = .008, and r = −.37, p = .02, respectively). Teacher rated Anxiety and Atypicality was significantly and negatively related to Visual Attention (r = −.34, p = .05 and r = −.34, p = .04), and teacher rated Withdrawal was significantly and negatively related to verbal WM (r = −.37, p = .02). On the PRS Conduct Problems were significantly and negatively related to Visual Attention (r = −.38, p = .02), and Atypicality was significantly and negatively related to verbal WM (r = −.35, p = .03). In order to examine which cognitive variables best predicted behavior on the BASC TRS and PRS, stepwise regression analyses were performed (see Table 6). Table 6 shows that the TRS Atypicality and Depression subscales were best predicted by performance on the Tower test. Teacher ratings of Attention Problems were best predicted by performance on the language test. Low scores on both the language test and the intelligence test best predicted teacher ratings of Learning Problems. No parent ratings were significantly predicted by performance on EF tasks. 4. Discussion The aim of the present study was to examine the relationship between neuropsychological measures of attention/executive functions and behavioral symptoms of ADHD and associated behavior as rated by parents and teachers. Previous studies have shown a lack of consistency between these measures, although they are all meant to assess similar constructs (e.g. Naglieri et al., 2005). One of the main findings of our study is that, when intelligence was controlled for, there were no significant relationships between parent and teacher ratings of ADHD symptoms and performance on EF tasks. These findings are in agreement with those of Marks et al. (2005), who studied the neuropsychological status of 22 preschoolers at risk for ADHD. They found no relations between performance on executive measures and objective indices of activity level or ratings of ADHD symptoms. The authors concluded that their findings cast doubt on whether EF deficits and/or frontostriatal networks contribute etiologically to early behavioral manifestations of ADHD. Sonuga-Barke, Dalen, Daley, and Remington (2002) did not find any association between the EFs of planning and WM and symptoms of ADHD in a heterogeneous sample of preschool children. Our findings contrast with those of Oosterlaan et al. (2005), who found relationships between teacher rated ADHD and performance on EF tests. The authors concluded that EF deficits were unique to ADHD and not caused by associated conduct problems. The reason for the conflicting results might be that Oosterlaan et al. used different rating scales to assess ADHD symptoms and different tasks to assess EFs than we did. Another main finding of our study is that we found significant relationships between EF tasks and behavioral constructs commonly co-occurring with ADHD and between non-EF tasks and ADHD symptoms, but only for teacher rating of behavior. Our findings partly agree with those of Sarkis et al. (2005), who studied the impact that comorbidity in children with ADHD has on EF. In their study a computerized version of the Tower of London test was used to assess EF and a semi-structured interview with the parents was used to assess behavior. Sarkis et al. found that comorbid disorders did not have a significant effect on performance of EF. Similarly in our study, we did not find a significant association of parent ratings with EF. In contrast, teacher ratings of comorbid ADHD symptoms were significantly related to performance on EF tasks.

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Interestingly, among the three different aspects of EF examined in our study, only the Tower test and verbal WM were significantly related (Table 3). A recent study by Joseph, McGrath, and Tager-Flusberg (2005) showed, that the NEPSY Tower test was significantly related to language ability in normal children but not in children with autism. The authors interpreted this finding as suggesting that children with autism are less able than normal children to verbally encode and manipulate goal-related information in WM, when performing the Tower task. Lewis et al. (2003) showed a positive relationship between verbal WM and performance on the Tower of London test in patients with Parkinson’s disease. They found that patients with impaired performance on the ToL were specifically impaired at manipulating information within verbal WM, compared to both controls and patients who were not impaired on the ToL. These findings are somewhat surprising considering that the towers tests are considered to be visuospatial and non-verbal measures of EF. All three measures of EF were significantly related to IQ, except the Visual Attention test, which was not significantly related to the Sequential Processing scale of the K-ABC. These findings are in line with previous research that has shown a strong relationship between IQ and EF (Arffa et al., 1998; Harrier & Deornellas, 2005; Mahone et al., 2002). On the other hand, only verbal WM was significantly related to language development, supporting the contention that the core problem in language disorders is deficient verbal WM (e.g. Baddeley & Wilson, 1993; Gathercole & Baddeley, 1989; Montgomery, 2003; Swank, 1999). Interestingly, the Tower test was the only EF measure that related to ratings of behavior, i.e. teacher ratings of depressive and autistic symptomatology (Table 6). Previous studies have found impairment in performance on towers tests in groups suffering from depression. Purcell, Maruff, Kyrios, and Pantelis (1997) studied neuropsychological function in young patients with unipolar major depression. Among their findings was that, compared to controls, the depressive group displayed impaired subsequent movement latencies on the ToL task. The authors interpreted this finding as suggesting deficits in the ability to sustain motor responses in depression. Sarkis et al. (2005) found that, although the presence of mood disorders did not predict total move score in a sample of ADHD children, those children with comorbid mood disorders took more moves to solve a ToL problem than other children. The authors speculated that this might be caused by depression symptoms of psychomotor retardation, fatigue, or reduced ability to concentrate. Similarly, Goethals et al. (2005) studied planning times and accuracy in depressed patients and found that, compared to controls, they spent more time thinking, although they were just as accurate. In view of the current and previous research, it might be speculated that ineffective performance on towers tests might in part be caused by depression. The strong relationships between performance on the Tower test and ratings of Atypicality on the TRS of the BASC, is a somewhat unexpected finding. According to Reynolds and Kamphaus (1992), clinical groups with childhood autism and depression have been found to score high on the Atypicality scale. These two clinical groups have also been found to score high on the Hyperactivity and Attention Problems scales of the BASC showing the great overlap between these childhood disorders (e.g. Blackman, Ostrander, & Herman, 2005; Bradshaw & Sheppard, 2000; Clark, Feehan, Tinline, & Vostanis, 1999; Towbin, Pradella, Gorrindo, Pine, & Leibenluft, 2005). Studies have shown that ADHD and autism often co-occur (Geurts, Vert´e, Oosterlaan, Roeyers, & Sergeant, 2004; Sturm, Fernell, & Gillberg, 2004) and that it may prove to be difficult to differentiate between these two disorders on behavioral scales commonly used to screen for attentional and behavioral disorders (Jensen, Larrieu, & Mack, 1997). Children with high functioning autism (HFA) have been shown to have more general and severe EF deficits (Geurts et al., 2004; Pennington & Ozonoff, 1996), and to score lower on towers tests, than children with ADHD (Sergeant et al., 2002). Childhood autism, depression and ADHD are all neurodevelopmental disorders that often co-occur and have all been associated with dysfunction of the frontostriatal system (Bradshaw & Sheppard, 2000) which in turn has been shown to be involved in the performance of the towers tests (e.g. Dagher, Owen, Boecker, & Brooks, 2001; van den Heuvel et al., 2003). The finding that the Visual Attention test was not significantly related to parent/teacher ratings of inattention supports previous findings indicating that ADHD is not characterized by deficient visual attention (e.g. Booth et al., 2005; HuangPollock & Nigg, 2003; van der Meere, Wekking, & Sergeant, 1991). The finding that a test of language ability best predicted teachers’ ratings of inattention in children is intriguing. Language impairment (LI) is highly prevalent in children with psychiatric disorders and behavioral problems. The most common psychiatric diagnosis of children with LI is ADHD (Cohen et al., 1998, 2000), and conversely, LI is a frequent comorbidity in children with ADHD (Cantwell, 1996; Kovac, Garabedian, Du Souich, & Palmour, 2001; Purvis & Tannock, 1997). In children referred for psychiatric services, those with LI have been shown to be the most impaired regardless of the psychiatric diagnosis (Cohen et al., 2000). Additional studies have shown that the EF construct of WM, which has been considered to be a core problem in ADHD, is more closely related to LI than to ADHD (Cohen et al., 2000; Jonsdottir et al., 2005). Denckla (2003) has

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suggested that many of the externally observable diagnostic characteristics of ADHD, particularly of the inattentive subtype, might be caused by language processing difficulties. Our results here seem to support that contention. It is somewhat surprising that in spite of the fact that language disorders are so frequently associated with ADHD, they are not generally screened for in its diagnostic process. Regression analyses (see Table 6) showed only relationships between the various cognitive constructs and teacher as opposed to parent ratings of behavior. These results are similar to those of previous studies (e.g. Oosterlaan et al., 2005) emphasizing that teachers may be better informants of neuropsychological problems in children than parents. The reason for that might be that teachers see children in more structured situations than parents do, and that they focus on cognitive functions. 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