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Child Neuropsychology: A Journal onNormal and Abnormal Development inChildhood and AdolescencePublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/ncny20

Conners' continuous performance test(CCPT-II) in children with ADHD, ODD,or a combined ADHD/ODD diagnosisLinda H. Munkvold a b c , Terje Manger a & Astri J. Lundervold c d ea Department of Psychosocial Science , University of Bergen ,Bergen , Norwayb Department of Child and Adolescent Psychiatry , HaukelandUniversity Hospital , Bergen , Norwayc Centre for Child and Adolescent Mental Health , UNI Research ,Bergen , Norwayd Department of Biological and Medical Psychology , University ofBergen , Bergen , Norwaye K. G. Jebsen Center for Research on Neuropsychiatric Disorders ,University of Bergen , Bergen , NorwayPublished online: 17 Dec 2012.

To cite this article: Linda H. Munkvold , Terje Manger & Astri J. Lundervold , Child Neuropsychology(2012): Conners' continuous performance test (CCPT-II) in children with ADHD, ODD, or a combinedADHD/ODD diagnosis, Child Neuropsychology: A Journal on Normal and Abnormal Development inChildhood and Adolescence, DOI: 10.1080/09297049.2012.753997

To link to this article: http://dx.doi.org/10.1080/09297049.2012.753997

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Child Neuropsychology, 2012http://dx.doi.org/10.1080/09297049.2012.753997

Conners’ continuous performance test (CCPT-II) in

children with ADHD, ODD, or a combined ADHD/ODD

diagnosis

Linda H. Munkvold1,2,3 , Terje Manger1, and Astri J. Lundervold3,4,5

1Department of Psychosocial Science, University of Bergen, Bergen, Norway2Department of Child and Adolescent Psychiatry, Haukeland University Hospital, Bergen,Norway3Centre for Child and Adolescent Mental Health, UNI Research, Bergen, Norway4Department of Biological and Medical Psychology, University of Bergen, Bergen,Norway5K. G. Jebsen Center for Research on Neuropsychiatric Disorders, University of Bergen,Bergen, Norway

The current study investigated if results on the Conners’ Continuous Performance Test (CCPT-II)could discriminate between children with ADHD (n = 59), ODD (n = 10), ADHD+ODD (n = 15),and normal controls (n =160), and how the results are associated with and explained by the intellec-tual function of the child. The sample was derived from the Bergen Child Study (BCS), a longitudinal,ongoing, population-based study of children’s development and mental health. CCPT-II performancedid not differentiate between the three diagnostic groups (i.e., ADHD, ODD, and ADHD+ODD).Children with ODD (with or without comorbid ADHD) did not differ from children in the controlgroup on any CCPT-II parameters. Children with ADHD made statistically significant more errors ofomissions and showed a more variable response time to targets than the control group. The correlationsbetween CCPT-II measures and IQ were mild to moderate, and there was a statistically significantgroup difference in IQ: Children with ADHD, and children with ADHD+ODD, obtained lower IQscores than normal controls. A hierarchical multiple regression analysis showed that IQ, but not diag-nostic group status, was significant predictors of CCPT-II performance. CCPT-II performance shouldbe interpreted with caution when assessing ADHD and/or ODD in children.

Keywords: ADHD; Oppositional defiant disorder; Continuous Performance Test; IQ; Neuro-psychological function; Child psychopathology; Kiddie-SADS; CCPT-II; ODD.

The present study was supported by fellowship from the Centre of Child and Adolescent Mental Health,UNI Research, Bergen, and was also funded by the University of Bergen, the Norwegian Directorate for Healthand Social Affairs, the Norwegian Research Council, and the Western Norway Regional Health Authority. Thestudy was also supported by “The National Program for Integrated Clinical Specialist and PhD-training forPsychologists” in Norway. This program is a joint cooperation between the Universities of Bergen, Oslo, Tromsø,The Norwegian University of Science and Technology (Trondheim), the Regional Health Authorities, and theNorwegian Psychological Association. The program is funded jointly by The Ministry of Education and Researchand The Ministry of Health and Care Services. We are grateful to the children, parents, and teachers for partic-ipating in the BCS and to Kjell Morten Stormark, Einar Heiervang, and other members of the project groupfor making the study possible. We thank Jim Stevenson and Robert A. Wicklund for helpful comments on themanuscript.

Address correspondence to Linda H. Munkvold, University of Bergen, Faculty of Psychology, ChristiesGate 12, 5015 Bergen, Norway. E-mail: Linda.Munkvold@psysp.uib.no

© 2012 Taylor & Francis

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2 L. H. MUNKVOLD ET AL.

Disruptive behavior problems commonly seen in children and adolescents include the psy-chiatric syndromes of attention deficit/hyperactivity disorder (ADHD) and oppositionaldefiant disorder/conduct disorder (ODD/CD; American Psychological Association [APA],2000). Disease theory states that a psychiatric disorder must be symptomatic of a dysfunc-tion within the child in order to be valid (Wakefield, 1992). Neurocognitive dysfunctionsare increasingly seen as potential validators of these disorders (Nigg, 2005). Researchcarried out over the past few decades has accumulated evidence that some form ofneurocognitive impairment is involved in the etiology of ODD/CD (Hill, 2002; Raineet al., 2005) and ADHD (Barkley, 2006; Seidman, 2006). Neurocognitive impairment prob-ably mediates the severity of symptoms associated with ODD/CD and ADHD by causingdeficits in general intellectual abilities (IQ; Crosbie & Schachar, 2001; Koenen, Caspi,Moffitt, Rijsdijk, & Taylor, 2006) and cognitive control functions such as attention andinhibition (Barkley, Edwards, Laneri, Fletcher, & Metevia, 2001; Baving, Rellum, Laucht,& Schmidt, 2006; Eme, 2009; Nigg, 2003). The costly and subjective nature of a clini-cal diagnostic evaluation has increased the quest for laboratory-based assessments of theneurocognitive impairment that potentially are associated with common child psychiatricdisorders (Nichols & Waschbusch, 2004). But it is still unclear whether laboratory testperformance can distinguish between children with different psychiatric diagnoses such asADHD and ODD/CD or can distinguish them from normal controls (Sergeant, Geurts, &Oosterlaan, 2002).

Continuous performance tests (CPTs) are widely used laboratory-based measures ofneurocognitive processes that are related to attentional control and inhibition (Aaron, Joshi,Palmer, Smith, & Kirby, 2002; Conners, Epstein, Angold, & Klaric, 2003). Several CPTversions have been developed since its basic paradigm was first described half a centuryago (Rosvold, Beck, Mirsky, Sarason, & Bransome, 1956). CPTs are generally consideredto be tests of sustained attention (vigilance), which require the subject to remain attentive,by pressing a key in response to specific target stimuli presented among distracting stimulion a computer screen (Edwards et al., 2007). One of the most common CPT versions usedby clinicians today is the second edition of Conners’ CPT (CCPT-II; Conners, 2000). It isbased on a response inhibition paradigm of 90% target stimuli and 10% nontarget stimuli.The CCPT-II generates a standard set of performance measures, some of which have beenfound to be sensitive to impaired attention and inhibition (Aaron et al., 2002). CCPT-IIperformance has been shown to improve with age, and boys tend to have faster reactiontimes and to make more impulsive errors as compared to girls (Conners et al., 2003).

CPT studies have demonstrated that children with ADHD exhibit performancedeficits relative to normal controls (Epstein et al., 2003; Losier, McGrath, & Klein, 1996).Children with ADHD commonly make more errors of commission and omission (Conners,2000; Losier et al., 1996; Willcutt, Doyle, Nigg, Faraone, & Pennington, 2005), they havefaster and more variable reaction times with a more impulsive response style (Epstein et al.,2003), they show lower signal detectability (Losier et al., 1996), and they perform worsewhen the interstimulus intervals increase (Conners, 2000). In two separate CPT studies, thenumber of correctly identified children and adults with ADHD was reported to be 52% and55%, respectively (Epstein, March, Conners, & Jackson, 1998; McGee, Clark, & Symons,2000). Although research has indicated that CPTs can differentiate children with ADHDfrom normal controls, CPTs commonly show less specificity when ADHD groups are com-pared with other clinical groups (Conners, 2000; McGee et al., 2000; Oosterlaan, Logan,& Sergeant, 1998).

ODD/CD is the most common comorbid condition of ADHD (Angold, Costello, &Erkanli, 1999; Barkley, 2006). According to the International Classification of Mental

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CCPT-II IN CHILDREN WITH ADHD AND/OR ODD 3

and Behavioural Disorders, 10th revision (ICD-10) (World Health Organization, 1999),ADHD+ODD/CD is an independent diagnostic category, and certain studies suggest thatchildren with combined attention deficit/hyperactivity and antisocial behavior displaymore neurocognitive problems (Moffitt & Henry, 1989; Moffitt & Silva, 1988). Studieshave demonstrated that ODD/CD is associated with deviant attentional processing (Bavinget al., 2006) and poor working memory function (Seguin, Nagin, Assaad, & Tremblay,2004). One study found that children with ODD had CPT performance deficits indepen-dent of ADHD comorbidity (Baving et al., 2006). CPT performance has also been foundto differentiate between children with ADHD, CD, and ADHD+CD combined (O’Brienet al., 1992). Another study found that children aged 48–67 months with hyperactivityproblems performed worse than their peers on the Conners’ Kiddie CPT, particularlyif they had co-occurring oppositional-defiant-behavior problems (Youngwirth, Harvey,Gates, Hashim, & Friedman-Weieneth, 2007).

Other studies have found no evidence for neurocognitive deficits among childrenwith ODD/CD, unless the children have comorbid ADHD (Oosterlaan, Scheres, &Sergeant, 2005; Thorell & Wåhlstedt, 2006). Authors have argued that neurocognitivedeficits are specifically related to ADHD (Clark, Prior, & Kinsella, 2000; Oosterlaan et al.,1998), and that the presence of ADHD accounts for the lower test performance in childrenwith ADHD+ODD/CD (Oosterlaan et al., 2005). This was supported by results from theNational Institute of Mental Health Collaborative Multisite Multimodal Treatment Studyof Children With ADHD that showed that, among children aged 7–9 years, those witha comorbid ADHD+ODD had high levels of impulsivity, but it was not different fromthat of children with ADHD alone (Newcorn et al., 2001). The neurocognitive dysfunc-tions possibly associated with the separate diagnostic category of ADHD+ODD thereforeremain relatively unclear.

A key issue in the literature has been the extent to which performance onneurocognitive tests is influenced by general intellectual abilities (IQ; Jester et al., 2009).This issue is particularly important, since low IQ in itself is associated with an increasedrisk for childhood psychopathology (Emerson, 2003). Children with ADHD commonlyobtain IQ scores about one standard deviation below the population mean (Crosbie &Schachar, 2001). Lower IQ is also associated with antisocial behavior problems (Koenenet al., 2006), and children with ODD/CD commonly obtain IQ scores about half astandard deviation below the population mean (Hinshaw, 1992; Nigg & Huang-Pollock,2003). Thus, when examining the association between psychopathology and test scores,the question arises as to whether IQ could confound results (Nigg, 2001). Some claimthat the key elements of neurocognitive functions are independent of general cognitiveabilities (Crinella & Yu, 2000). Other studies have demonstrated a substantial overlapbetween neurocognitive test performance and IQ (Duncan, Johnson, Swales, & Freer,1997), at least for individuals with IQ below the normal range (Dodrill, 1999). In orderto deal with this issue studies commonly covary IQ from specific neurocognitive mea-sures or they exclude subjects with an IQ below 80 (see, for instance, Banaschewskiet al., 2004; Barkley et al., 2001; Klorman et al., 1999; Schachar et al., 2007; Seidman,Biederman, Monuteaux, Doyle, & Faraone, 2001). Some authors have argued that theseare misguided and unjustified procedures (e.g., Dennis et al., 2009), as long as gen-eral cognitive abilities cause, and therefore never can be separated from more specificneurocognitive skills. It has also been argued that children in the mild range of mentalretardation (i.e., IQ between 50 and 70) are the lower extension of the normal distribution(Ziegler & Hodapp, 1986) and therefore could be included in studies of general intellectualfunctions.

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4 L. H. MUNKVOLD ET AL.

Some previous studies of neurocognitive deficits are limited by the inclusion ofsamples without reliable Diagnostic and Statistical Manual of Mental Disorders (DSM)diagnoses (e.g., Moffitt, 1993), or because they have disregarded the diagnostic distinc-tion between ODD and CD by using mixed ODD/CD samples (e.g., Oosterlaan et al.,2005). As a consequence, ODD has seldom been studied as an independent disorder, andthe knowledge about attentional processes and possible associations with low IQ is thuslimited within this diagnostic group. Even though low IQ is associated with psychiatricdiagnoses, it is still unclear how IQ relates to neurocognitive test performance among chil-dren with ADHD and/or ODD. A study of 117 referred children aged 6–16 found fewsignificant correlations between neurocognitive measures of attention/inhibition and IQscores (Naglieri, Goldstein, Delauder, & Schwebach, 2005). However, the study did notdifferentiate between children with different diagnoses, it included only two children with-out any diagnosis, and did not differentiate between children with high/low IQ. In orderto better understand how specific neurocognitive functions such as attention and inhibitionrelate to general intellectual function in children with ADHD and/or ODD/CD, furtherstudies should interpret test performance in the light of the child’s general intellectualabilities.

Aims of the Present Study

The current study investigated whether performance on the second version of theConners’ CPT (CCPT-II) could discriminate between children with ADHD, ODD, a com-bined ADHD+ODD and controls without any diagnosis. We expected lower CCPT-IIperformance in the ADHD-group (with and without comorbid ODD) than in the ODD-group and the control group, and that children with ODD would perform close to the levelof the controls. We also expected that children with ADHD and/or ODD would obtainslightly lower IQ scores than normal controls. A second aim was to examine associationsbetween IQ and CCPT-II results, and to examine the unique contribution of IQ and diagnos-tic group status to performance on separate CCPT-II parameters. We expected a moderateassociation between IQ and CCPT-II scores regardless of diagnostic group status.

MATERIAL AND METHODS

Participants

The sample was derived from the first wave of the Bergen Child Study (BCS),a longitudinal, ongoing, population-based study of children’s development and mentalhealth. The study design and protocol of the first wave is described elsewhere (Heiervanget al., 2007), and only a brief presentation will be given here. The sampling frame includedall children in the 1993 through 1995 birth cohorts (aged 7–9) in the municipality of Bergen(n = 9430) and Sund (n = 222), Norway. The first wave of the BCS included three phases.Phase 1 was conducted in October 2002 when the children attended second to fourth grade.In this first screening phase, a four-page questionnaire, covering a wide range of symptomsand associated functional impairment, was administered to parents and teachers. The ques-tionnaire included the Strengths and Difficulties Questionnaire (SDQ; Goodman, 2001),which is divided into five subscales (hyperactivity or inattention, emotional symptoms,conduct problems, peer relationship problems, and prosocial behavior). A total difficultiesscore is computed by combining the first four subscale scores. An impact assessment is

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CCPT-II IN CHILDREN WITH ADHD AND/OR ODD 5

based on the overall problem severity, distress to the child, interference in everyday life,and burden to others. A child was defined as screen positive if (a) the total difficulties scoreexceeded the 90th percentile for parents and/or teachers SDQ scores, and/or (b) there weresevere impairments according to the impact section of the SDQ, and/or (c) scores on one ofthe other scales included in the screening questionnaire were equal or above the 98th per-centile. Based on parental informed consent, more than 70% participated in the screeningphase of the study (n = 7007). In Phase 2, the parents of all screen-positive children, plusa random sample of screen-negative children from Phase 1 were interviewed, using thesemi-structured interview Development and Well-Being Assessment (DAWBA; Goodman,Ford, Richards, Gatward, & Meltzer, 2000) (n = 1080). All children who had received adiagnosis according to the DAWBA (n = 139), plus a random sample children from Phase2, where 50% were defined as screen positive and 50% as screen negative in Phase 1(n = 282), were invited to participate in an extensive clinical examination procedure ofPhase 3. Of the 421 children invited to Phase 3, 78% (n = 329) completed the clinicalexamination. The sample consisted of 210 boys (64%) and 119 girls (36%), aged 7–11(M = 9.5 yrs). The majority were Norwegian (87.8%), and 3% were from non-Westerncountries. Eight children (2.4%) were adopted, and 69% (n = 227) lived with both of theirbiological parents.

Instruments

The clinical examination in Phase 3 of the first wave of the BCS included (a) a diag-nostic semi-structured interview of the parent and the child (the Kiddie-SADS Present andLifetime Version [K-SADS-PL]; Kaufman, Birmaher, Brent, Rao, & Ryan, 1996), (b) theNorwegian version of Wechsler’s Intelligence Scale for Children, third edition (WISC-III;Wechsler, 2003a), and (c) the Conners’ Continuous Performance Test, second version(CCPT-II; Conners, 2000). The Diagnostic Interview for Social and CommunicationDisorders (DISCO; Wing, Leekam, Libby, Gould, & Larcombe, 2002) was included toidentify children in the autism spectrum (Posserud, Lundervold, Lie, & Gillberg, 2010;Posserud, Lundervold, & Gillberg, 2009). Clinicians trained in using the instruments spentabout 6 hours examining each child.

The Diagnostic Interview. The K-SADS-PL is a semi-structured interviewdesigned to assess current and past episodes of psychopathology in children and ado-lescents aged 6–18 (Kaufman et al., 1996). It is based on the diagnostic criteria of theDiagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV; APA,1994) and covers lifetime and current episodes of affective disorders, anxiety disorders,disruptive behavioral disorders (including ADHD, ODD, and CD), eating disorders, psy-chosis, tic disorders, substance abuse, encopresis, and enuresis. The K-SADS-PL is basedon a flexible yet systematic inquiry to assess the presence of psychopathology with sug-gested verbal probes that assist the examiner in clarifying the presence and severity ofsymptoms. It includes an initial 82-symptom screen interview where the examiner rateskey symptoms of current and past episodes of psychopathology in 20 different diagnosticareas. If there are positive screening symptoms, it is necessary to administer one or moreof the five supplemental score sheets (i.e., affective, psychotic, anxiety, behavioral, andsubstance abuse/other disorders), which encompass the confirmatory diagnostic symptomratings. The K-SADS-PL has been shown to be a reliable and valid instrument for assessingchild and adolescent psychiatric diagnoses (Ambrosini, 2000).

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6 L. H. MUNKVOLD ET AL.

The K-SADS-PL interview was conducted by a trained clinician, first with the par-ent(s) alone and later on the same day with the child alone. The diagnostic evaluation wasbased on the information provided by both informants according to the K-SADS-PL algo-rithms, where diagnoses are scored as definite, probable, or not present (Kaufman et al.,1996). A probable diagnosis is given when the child’s behavior fulfills all the diagnos-tic criteria except for one, and the symptoms cause impairment. In the present study, apsychiatric diagnosis was given when the current episode was rated as probable or definiteaccording to the clinician summary.

Assessment of General Intellectual Abilities (IQ). The WISC-III (Wechsler,1992) is a widely used instrument to assess intellectual abilities in children aged 6–16.The WISC-III consists of three broad IQ indexes (Verbal, Performance, and Full Scale),calculated from the scores on 12 different subtests. The Full Scale Intelligence Quotient(FSIQ) yields standard scores with a mean of 100 and a standard deviation (SD) of 15.In the current study, the Norwegian translation of the WISC-III (Wechsler, 2003a) wasused and scored according to standardized Swedish norms based on a representative sam-ple of 1036 children aged 6–15 (Sonnander, Ramund, & Smedler, 1998). A trained testtechnician administered and scored the 12 WISC-III subtests that comprise the FSIQ. TheWISC was revised in 2003 (WISC-IV), and the correlation between WISC-III FSIQ andWISC-IV FSIQ is reported to be .89 (Wechsler, 2003b). The WISC-III has been studiedextensively, and it is considered a valid and reliable instrument for assessing children’sgeneral intellectual abilities (see Wechsler, 2003a for details).

The Conners’ Continuous Performance Test. The Conners’ ContinuousPerformance Test-II (CCPT-II; Conners, 2000) is a standardized, computerized instrumentdesigned to assess different aspects of attention/executive functions. The CCPT-II takes12 minutes to complete. It consists of 360 single letters presented one by one on a com-puter screen in 18 consecutive blocks of 20 trials. Respondents are asked to press a buttonevery time a stimulus (letter) is presented, except for the letter “X.” The frequency of thetarget-stimulus “X” is 10%. The 18 blocks consist of interstimulus intervals (ISI) varyingbetween 1, 2, and 4 seconds. The entire CCPT-II can be divided into six time blocks, witheach time block containing all three ISI conditions.

The CCPT-II generates several measures. The number of omissions (failing torespond to non-“X” letters) and the number of commissions (erroneously responding tothe letter “X”) are accuracy measures. The mean hit reaction time (Hit RT) is the mainmeasure of speed of processing. The beta statistics, β, is a measure of the individual’strade-off between speed and accuracy. Higher values of beta reflect a cautious responsestyle (i.e., the child is trying hard to avoid errors), whereas lower values of beta are pro-duced by a response style in which children are more concerned with responding to mosttargets than with mistakenly responding to a nontarget. Consistency of response time isexpressed by the standard error (SE) of Hit RT and variability of SE, where lower values inthe latter indicate better ability to sustain performance level throughout the test. Vigilanceacross the six time blocks is expressed by the Hit RT and SE block change parameters (i.e.,changes in RT SE’s across the time blocks). A positive slope on the SE measure indicatesless consistent Hit RTs as the test progresses. The signal detection measure, d’, reflects howwell a subject discriminates between targets and nontargets. Higher values of d’ indicatehigher attentiveness, that is, better ability to distinguish target from nontarget stimuli.

The original normative data for the CCPT-II is based on a clinical sample of378 ADHD cases and 223 adult individuals with neurological impairment, plus a

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CCPT-II IN CHILDREN WITH ADHD AND/OR ODD 7

nonclinical sample of 1920 individuals (47.2% males) aged 6 and older from the generalpopulation in the United States of America (Conners, 2000). Detailed demographic charac-teristics of the nonclinical sample are listed in the CCPT-II manual. According to multisitestudies, the CCPT-II shows a satisfactory ability to differentiate ADHD clinical groupsfrom nonclinical groups, although less ability to differentiate between clinical groups(for details regarding validity studies, see Conners, 2000). The CCPT-II does not provideNorwegian norms, and raw scores were therefore used in the current study.

Selection Procedures

Children with an FSIQ < 50 (n = 12) were excluded from the current analyses, asan IQ of 50 or less is an exclusion criterion for ADHD according to the ICD-10 (WorldHealth Organization, 1999). Of the 329 children who completed the clinical examination inPhase 3 of the BCS, 13 were excluded due to having an autism spectrum disorder, 12 dueto having an IQ below 50, 1 due to missing FSIQ, and 12 due to invalid or missing CCPT-IIprotocols. The remaining sample consisted of 181 boys and 110 girls (n = 291). Of these291 children, 131 children (70% boys) were identified with a probable or definite psy-chiatric diagnosis according to the diagnostic interview (K-SADS-PL). Sixty-five childrenhad ADHD (83% boys) and 25 children had ODD (88% boys). Fifty-three children (57%boys) had diagnoses other than ADHD or ODD and were excluded from the analyses.As Conduct Disorder (CD) is an exclusion criterion for ODD according to DSM-IV guide-lines, three children (1 boy and 2 girls) identified with CD were excluded. The remaining235 children were allocated to the following diagnostic groups: (a) no ADHD or ODD(n = 160), (b) “pure” ADHD (n = 50), (c) “pure” ODD (n = 10), and (d) ADHD + ODD(n = 15) (see Figure 1). The children with a known diagnosis of ADHD were requested torefrain from taking any medication on the day of the examination.

Statistical Analyses

Differences in the boy-girl ratio between the groups were examined by a chi-squaretest for independence. One-way between-groups analyses of variance (ANOVAs) wereperformed to test for differences in age and IQ between the four independent groups.Separate analyses of covariance (ANCOVAs) were performed for each CCPT-II param-eter in order to examine differences between groups (covarying for sex). In a subsequentset of analyses, IQ was added as a covariate. In the event of significant group differences,post hoc Bonferroni tests were performed. Due to different group sizes, all variance andcovariance analyses were customized to run Type III Sums of Squares. The relationshipsbetween CCPT-II parameters, IQ, age, and sex were first investigated using the Pearsonr correlation coefficient (a point biserial correlation was used for the sex variable).Then hierarchical multiple regression was used to assess the relative ability of diagnos-tic status (i.e., ADHD, ODD, ADHD+ODD, or no diagnosis) and IQ to predict CCPT-IIscores, after controlling for the influence of sex. SPSS 18.0 was used for all statisticalanalyses.

Ethics

The study was approved by the Regional Committee of Ethics on Medical Researchin Western Norway and the Ombudsman for Privacy in Research, Norwegian SocialScience Data Services.

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8 L. H. MUNKVOLD ET AL.

Excluded

BCSPhase 3(n = 329)

No CPT(n = 7)

Invalid CPT(n = 5)

No FSIQ(n = 1)

FSIQ < 50(n = 12)

K-SADS(n = 291)

ADHDDefinite (n = 37)Probable (n = 28)

(n = 65)

ODDDefinite (n = 17)Probable (n = 8)

(n = 25)

“pure”ADHD

(n = 50)

“pure”ODD

(n = 10)

Nodiagnosis(n = 160)

ADHD +ODD

(n = 15)

Comorbiddisorders(n = 15)

Comorbiddisorders(n = 15)

Comorbiddisorders

(n = 5)

n = 3 Tics n = 7 Simple phobia n = 3 Social phobian = 1 Depression n = 4 Enuresis n = 2 Encopresis

n = 2 Tics n = 5 Simple phobia n = 1 GAD n = 1 Separation anx n = 2 Enuresis

n = 2 Tics n = 1 OCD n = 1 Simple phobia n = 1 GAD n = 1 Social phobia n = 2 Depression n = 1 Enuresis

Excluded

Diagnoses otherthan ADHD orODD (n = 53)

ConductDisorder (n = 3)

Autism (n = 13)

Figure 1 A flowchart showing the selection of children in the present study.Note: BCS = Bergen Child Study; OCD = Obsessive Compulsive Disorder; GAD = Generalized AnxietyDisorder.

RESULTS

Overall CCPT-II Performance and Correlations

CCPT-II performance in the entire sample (n = 235) is shown in Table 1. The meanscores of omissions, commissions, Hit RT, variability (SE), and vigilance were within aver-age range. Hit RT (SE), detectability (d’), and response style (β) were mildly atypical,as compared to normative data and results from epidemiological studies (Conners, 2000;

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CCPT-II IN CHILDREN WITH ADHD AND/OR ODD 9

Table 1 Overall CCPT-II Performance (n = 235).

M SD Minimum Maximum

Omissions 17.74 14.40 1 90Commissions 24.59 6.68 2 35Hit RT 378.98 73.35 256.46 795.68Hit RT (SE) 12.21 6.80 3.26 43.18Response style (β) 0.38 0.30 0.02 1.97Detectability (d’) 1.17 0.77 −0.41 3.88Vigilance∗ 0.07 0.10 −0.18 0.38Variability (SE) 26.28 21.56 3.70 116.34

Note. CPT-II = Conner’s Continuous Performance Test; RT = Reaction Time;SE = standard error.

∗Hit RT (SE) Block change.

Conners et al., 2003; Miranda, Sinnes, Pompeia, & Bueno, 2008). This could be due to therelatively high number of children with a mental disorder in our sample (31.9%).

The correlations among the CCPT-II parameters, age, sex, and FSIQ (as measured bythe WISC-III) are listed in Table 2. The correlations between the seven CCPT-II parameterswere all statistically significant with the exception of Hit RT and β (ns). The magnitude ofthe statistically significant correlations varied from small (r = .13) to large (r = −.87),according to the guidelines of Cohen (1988). Sex was most strongly correlated withDetectability (d’) (r = .26, p < .01), with a higher level of discrimination between targetsand nontargets associated with being female (Table 2).

FSIQ was significantly correlated with all CCPT-II parameters except forCommissions, with statistically significant correlation coefficients ranging from small,r = −.20 (Vigilance), to medium, r = −.33 (Omissions). Exploratory analyses showedthat these correlations mainly were significant among children with an IQ above 70(n = 210). Among children with an IQ between 50 and 69 (n = 25), there was astatistically significant correlation between FSIQ and Omissions (r = −.43, p < .05),whereas all other correlations between FSIQ and CCPT-II parameters were nonsignificant.When comparing the two groups (i.e., IQ = 50–69 and IQ > 70), children with an IQbetween 50 and 69 made significantly more errors of omissions, they had slower and lessconsistent reaction times, and they had a more impulsive response style (results availableon request from the first author).

Group Differences in Sex, Age, and IQ

There was a statistically significant sex difference between the four groups,χ2(3, n = 235) = 17.68, p < .01. The percentage of boys was highest in the ADHD+ODDgroup (100% boys), and lowest in the normal control group (56% boys). Subsequent analy-ses were therefore statistically controlled for the effect of sex. The mean age of the samplewas 9.5 years (SD = 0.9). The age difference between the groups was not statisticallysignificant, F (3, 231) = 1.24, p = .30.

After adjusting for the effect of sex, there was a statistically significant differencein FSIQ (as measured by the WISC-III) between the four groups, F(3, 230) = 6.53,p < .001, with a medium effect size according to the guidelines of Cohen (1988) (par-tial eta squared = .08). A Bonferroni post hoc test indicated that the mean IQ scores forchildren with ADHD (M = 84.2, SD = 13.4) and children with ADHD+ODD (M = 80.9,

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10 L. H. MUNKVOLD ET AL.

Tabl

e2

Cor

rela

tions

(Pea

rson

r)am

ong

CC

PT-I

IM

easu

res,

Age

,Sex

,and

FSIQ

(n=

235)

.

Age

FSIQ

Om

issi

ons

Com

mis

sion

sH

itR

TH

itR

T(S

E)

βd’

Vig

ilanc

ebV

aria

bilit

y(S

E)

Sexa

−.06

.17∗

∗−.

17∗

−.25

∗∗.1

4∗−.

17∗

−.23

∗∗.2

6∗∗

−.07

−.17

∗A

ge−.

11−.

17∗

−.01

−.33

∗∗−.

13−.

11.0

7−.

05−.

09FS

IQ−.

33∗∗

−.10

−.21

∗∗−.

29∗∗

−.25

∗∗.2

4∗∗

−.20

∗∗−.

25∗∗

Om

issi

ons

.14∗

.34∗

∗.7

2∗∗

.69∗

∗.5

6∗∗

.30∗

∗.6

8∗∗

Com

mis

sion

s−.

47∗∗

.20∗

∗.4

7∗∗

−.87

∗∗.1

8∗∗

.29∗

∗H

itR

T.4

4∗∗

.05

.23∗

∗.1

3∗.2

4∗∗

Hit

RT

(SE

).6

0∗∗

−.49

∗∗.4

4∗∗

.94∗

∗R

espo

nse

styl

e(β

)−.

76∗∗

.30∗

∗.6

0∗∗

Det

ecta

bilit

y(d

’)−.

30∗∗

−.53

∗∗V

igila

nceb

.50∗

∗

Not

e.a Po

intb

iser

ialc

orre

latio

ns.b

Hit

RT

(SE

)B

lock

chan

ge.

∗ p<

.05.

∗∗p

<.0

1.

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CCPT-II IN CHILDREN WITH ADHD AND/OR ODD 11

Table 3 Demographic Characteristics of the Sample.

NC(n = 160)

ADHD(n = 50)

ODD(n = 10)

ODD+ADHD(n = 15) Group Comparison

Measure M (SD) M (SD) M (SD) M (SD) F p η2 Bonferroni

Boys/Girls 89/71 39/11 7/3 15/0 5.89 .001Age 9.4 (1.0) 9.6 (0.8) 9.3 (0.8) 9.7 (1.0) 1.24 .297Full scale IQb 93.7 (14.6) 84.2 (13.4) 86.3 (11.0) 80.9 (18.7) 6.53 .000 0.08 ADHD &

ODD+ADHD < NC

Note. NC = normal controls; ADHD = attention deficit/hyperactivity disorder; ODD = oppositional defiantdisorder.

badjusted for sex.

SD = 18.7) were significantly lower than for normal controls (M = 93.7, SD = 14.6)(see Table 3). One child with ODD (10%), 7 children with ADHD (14%), and 5 childrenwith ADHD+ODD (33%) had an IQ level in the area of mild intellectual disability (i.e.,IQ < 70), as compared to 12 children (8%) in the NC group. At the opposite end of the IQscale, no children with a diagnosis of either ADHD, ODD, or ADHD+ODD had a superiorIQ level (i.e., IQ > 115), whereas 8% in the NC group did.

Group Differences in CCPT-II Scores

Due to multicolinearity (i.e., strong correlations between the CCPT-II parameters),a series of separate ANCOVAs were performed for each CCPT-II parameter, covarying forsex. Exploratory analyses were conducted to ensure that there were no violations of theassumptions of homogeneity of variances (Levene’s test) and homogeneity of regressionslopes (i.e., no interaction effects between sex and diagnostic group status).

After adjusting for the effect of sex, the only overall group differences to reach sta-tistical significance were Omissions, F(3, 230) = 2.8, p < .05; partial eta squared = .04,and Hit RT (SE), F(3, 230) = 3.0, p < .05; partial eta squared = .04. According tothe guidelines of Cohen (1988), these differences represent small-to-medium effect sizes.Bonferroni corrected group-wise analyses showed that it was the children with ADHD(without comorbid ODD) who made more errors of omission (p < .05) and who had lessconsistency of Hit RTs (p < .05), as compared to normal controls (see Table 4). When FSIQwas added as a covariate, none of the group differences retained statistical significance.

Post hoc analyses showed that there were no statistically significant differ-ences in CCPT-II scores between the three diagnostic groups (i.e., ADHD, ODD, andADHD+ODD), and children with ODD (with or without comorbid ADHD) did not differsignificantly from normal controls on any CCPT-II parameters.

Explained Variance in CCPT-II Scores

Hierarchical multiple regression analyses were used to examine the incremen-tal contribution of sex, diagnostic group status (i.e., ADHD, ODD, ADHD+ODD, ornormal controls), and FSIQ to the eight selected CCPT-II-parameters. The analyses wereconducted in three steps: sex was entered first, followed by diagnostic group status, and

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12 L. H. MUNKVOLD ET AL.

Table 4 Comparisons of Differences in CCPT-II Scores Between the Four Diagnostic Groups (EstimatedMarginal Means, Adjusted for the Effect of Sex).

NC(n = 160)

ADHD(n = 50)

ODD(n = 10)

ODD+ADHD(n = 15) Group Comparison

CCPT-II Measure M (SE) M (SE) M (SE) M (SE) F p η2 Bonferroni

Omissions∗ 15.9 (1.1) 21.6 (2.0) 22.1 (4.4) 22.1 (3.7) 2.8 .04 .04 ADHD > NCCommissions 24.6 (0.5) 24.2 (0.9) 25.9 (2.1) 25.1 (1.7) 0.2 .88 .01Hit RT 372.6 (5.8) 399.2 (10.3) 399.0 (22.9) 372.3 (19.0) 2.0 .11 .03Hit RT (SE)∗ 11.3 (0.5) 13.9 (0.9) 14.9 (2.1) 14.5 (1.7) 3.0 .03 .04 ADHD > NCResponse style (β) 0.36 (0.02) 0.38 (0.04) 0.40 (0.09) 0.51 (0.08) 1.1 .34 .02Detectability (d’) 1.22 (0.06) 1.14 (0.10) 0.95 (0.24) 0.98 (0.20) 0.9 .46 .01Vigilancea 0.07 (0.01) .08 (0.02) 0.12 (0.03) 0.07 (0.03) 0.9 .42 .01Variability (SE) 24.0 (1.7) 29.9 (3.0) 33.1 (6.7) 34.4 (5.6) 2.1 .11 .03

Note. NC = normal controls (no diagnosis); ADHD = attention deficit/hyperactivity disorder;ODD = oppositional defiant disorder; RT = Reaction Time; SE = standard error.

aHit RT (SE) Block change.∗p< .05.

Table 5 Hierarchical Multiple Regression Analyses Measuring the Incremental Contributionof Sex, Diagnostic Group Statusa, and FSIQ to the Prediction of CCPT-II Scores.

CCPT-II Measure Predictor B β R2 � F �

Omissions Sex −2.82 −.09 .03 6.65∗Diagnostic Statusa 1.57 .09 .03 6.17∗FSIQ −0.27 −.29∗∗ .07 19.60∗∗

Commissions Sex −3.32 −.24∗∗ .06 15.55∗∗Diagnostic Statusa 0.07 .01 .00 0.11FSIQ −0.02 .05 .00 0.63

Hit RT Sex 27.72 .18∗∗ .02 4.51∗Diagnostic Statusa 1.31 .02 .01 1.23FSIQ −1.15 −.24∗∗ .05 12.73∗∗

Hit RT (SE) Sex −1.39 −.10 .03 6.91∗∗Diagnostic Statusa 0.94 .12 .03 7.21∗∗FSIQ 1.11 −.24∗∗ .05 13.51∗∗

Response style (β) Sex −0.11 −.18∗∗ .05 12.88∗∗Diagnostic Statusa 0.02 .06 .01 2.83FSIQ −0.00 −.20∗∗ .04 9.76∗∗

Detectability (d’) Sex 0.34 .22∗∗ .07 17.06∗∗Diagnostic Statusa −0.05 −.05 .01 2.44FSIQ 0.01 .19∗∗ .03 8.58∗∗

Vigilanceb Sex −0.01 −.03 .00 1.00Diagnostic Statusa 0.00 .01 .00 0.82FSIQ −0.00 −.19∗∗ .03 8.19∗∗

Variability (SE) Sex −4.64 −.10 .03 6.63∗Diagnostic Statusa 2.74 .11 .02 5.79∗FSIQ −0.29 −.21∗∗ .04 9.77∗∗

Note. FSIQ = Full Scale IQ (from WISC-III); SE = standard error; B & β = the values forthe regression coefficients with all three variables in the equation; R2 � & F � = the valuesfor the change statistics at the step it was entered in the model.

aADHD, ODD, ODD+ADHD, or normal controls. bHit RT (SE) Block change.∗p < .05. ∗∗p < .01.

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CCPT-II IN CHILDREN WITH ADHD AND/OR ODD 13

finally FSIQ. The results of the analyses are outlined in Table 5. Sex, entered in Step 1,was a statistically significant predictor of performance on four CCPT-II parameters: Sexexplained 6% of the variance in Commissions, 2% in Hit RT, 5% in Response style (β),and 7% in Detectability (d’). The diagnostic variable was entered in Step 2, and the totalvariance explained then increased with 3% for Omissions, 3% for Hit RT (SE), and 2% forVariability (SE). Although these changes were statistically significant, the improvementsin explained variance were small.

After entry of FSIQ at Step 3, the total variance explained by the model as a wholeranged from 0% (Commissions) to 7% (Omissions), averaging a 3.9% explained vari-ance for the eight CCPT-II parameters. In the final model with all three variables in theequation, only sex and FSIQ were statistically significant predictors of CCPT-II scores,whereas diagnostic group status was not. Sex was a statistically significant predictor ofscores on Commissions (beta = −.24, p <.01), Hit RT (beta = .18, p <.05), Response style(beta = −.18, p <.01), and Detectability (beta = .22, p <.01). FSIQ was a statistically sig-nificant predictor of scores on all CCPT-II parameters, except for Commissions, with betavalues ranging from .19 to −.29. FSIQ recorded the highest beta values on all CCPT-IIparameters with one exception: Sex recorded a slightly higher beta value (beta = .22) thanFSIQ (beta = .19) on Detectability (d’).

DISCUSSION

The main purpose of the present study was to investigate the utility of the secondedition of Conners’ CPT (CCPT-II) in distinguishing between children with ADHD, ODD,ADHD+ODD, and normal controls. A second aim was to address the association betweenIQ and CCPT-II performance, and the unique contribution of group and IQ in explainingthe CCPT-II results. Post hoc analyses showed that CCPT-II performance did not differ-entiate between the three diagnostic groups (i.e., ADHD, ODD, and ADHD+ODD), andchildren with ODD (with or without comorbid ADHD) did not differ significantly fromnormal controls on any CCPT-II parameters. However, children with “pure” ADHD madesignificantly more errors of omissions and showed a more variable response time to targetsthan the control group. When controlling for the possible confounding effect of IQ, thegroup differences in CCPT-II performance between children with “pure” ADHD and nor-mal controls were no longer statistically significant. In general, high CCPT-II performancewas positively correlated with a high-IQ score. There was a statistically significant groupdifference in IQ, whereby children with ADHD and ADHD+ODD had significantly lowerIQ scores than normal controls. Considered together with the effect of sex, IQ was a signif-icant predictor of performance on all CCPT-II parameters, except one, whereas diagnosticgroup status was not a significant predictor on any CCPT-II parameters.

In line with other studies (Conners et al., 2003), we found that children’s sex affectedCCPT-II performance on several parameters: Sex explained 6% of the variance in commis-sions, 2% of the variance in reaction times, 5% of the variance in response style, and 7%of the variance in detectability. This indicates that girls, as compared to boys, make fewererrors of commissions, they have faster reaction times, and they have higher levels of atten-tiveness. This supports the hypothesis that in general, boys exceed girls in neurocognitivedeficits (Eme, 2009).

According to the normative data for the CCPT-II, as children grow older, theywill have faster reaction times, have less variability and make fewer errors of omissionsand commissions (Conners, 2000). We found partial support for the original findings ofConners in that age correlated with Omissions, reaction time (Hit RT), consistency in

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14 L. H. MUNKVOLD ET AL.

reaction time (Hit RT [SE]), and response-style (β). However, age was not significantlycorrelated with commissions. Age was most strongly correlated with Hit RT (r = −.33,p < .01), with faster reaction times associated with higher age.

Previous studies of the clinical utility and sensitivity of CPTs in distinguishing chil-dren with ADHD from healthy controls have been favorable (Conners, 2000; Losier et al.,1996). But studies of the specificity of the CPT have not yielded favorable results regard-ing the ability of the CPT to distinguish children with ADHD from other clinical groups(Nichols & Waschbusch, 2004; Swaab-Barneveld et al., 2000). This last notion was sup-ported by our study in that there were no significant differences between children withADHD and ODD on any CCPT-II measures. However, we did find that children withADHD differed significantly from children in the normal control group on two of theCCPT-II variables that, according to Conners (2000), are core measures of inattention:errors of omission and variability in reaction time (Hit RT [SE]). Our results, therefore,support other studies indicating that fluctuations in speed of responding (Swaab-Barneveldet al., 2000) and errors of omissions (Edwards et al., 2007; O’Brien et al., 1992) are twokey parameters in identifying children with ADHD. Although statistical significant, theeffect sizes were small to medium; diagnostic group status accounted only for 4% of thevariance in omission and Hit RT (SE) scores (unadjusted for the effect of IQ), which is avery small proportion. When considering the contribution of diagnostic group status (i.e.,ADHD, ODD, ADHD+ODD, or normal controls), together with sex and IQ, the threevariables combined explained a maximum of 7% of the variance in any CCPT-II parame-ter (Omissions). This indicates that performances on any CCPT-II parameters are stronglyinfluenced by other variables in addition to the presence of ADHD.

Neurocognitive deficits related to attention and inhibition/impulsivity have com-monly been cited as core features of ADHD (Barkley, 2001; Schachar et al., 2007; Willcuttet al., 2005). The assumption that CPTs are measuring symptoms of inattention andimpulsivity is largely intuitively based and not founded on empirical investigations of thecorrelations between the different CPT components and corresponding behavioral mea-sures. For instance, errors of omission (i.e., absence of response to target) are assumed toreflect symptoms of inattention, errors of commission (i.e., responding when no responseis required) are assumed to reflect impulsivity, and the measures across the six blocks areassumed to reflect sustained attention/vigilance (Barkley, 1991; Conners, 2000; Corkum& Siegel, 1993). However, studies have found little empirical support for the intuitive inter-pretation of CPT performance (Barkley, 1991; Epstein et al., 2003). This may explainwhy the significant group differences in CCPT-II performance in the present study wererestricted to omissions and Hit RT (SE) for the ADHD group, and that no significantlydeviant CCPT-II scores were found in the ODD group. In other words, although thediagnostic criteria for ADHD and ODD involve behavioral descriptions of impulsivityand inattention, this deviant behavior is not manifested as lower CCPT-II performance.In line with a recent meta-analytic review (Willcutt et al., 2005), our results indicate thatneurocognitive deficits are neither necessary nor sufficient to identify ADHD in children,and test scores on the CCPT-II should be interpreted with caution when used as a part of adiagnostic evaluation.

The assumption that children with ODD suffer from neurocognitive dysfunctionsrelated to inattention (Baving et al., 2006) was not supported in our study. In fact, childrenwith ODD (with or without comorbid ADHD) did not differ significantly from normalcontrols on any CCPT-II parameter. This is somewhat surprising, in that the children in ourstudy were relatively young (7–11 years old), and childhood-onset antisocial behavior is

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CCPT-II IN CHILDREN WITH ADHD AND/OR ODD 15

considered to be associated with more severe neurocognitive dysfunctions than adolescent-onset antisocial behavior (Moffitt & Caspi, 2001). At the same time, numerous studies havefound no evidence of neurocognitive dysfunctions among children with ODD and/or CDas compared to normal controls or children with ADHD (Klorman et al., 1999; O’Brienet al., 1992; Speltz et al., 1999; van Goozen et al., 2004). Our study supports this latter lineof research. However, our results regarding differences in CCPT-II scores for the ODD andADHD+ODD groups should be interpreted with caution due to the relatively small n andthe unbalanced sex ratio. Several of the mean CCPT-II scores for ODD children with orwithout comorbid ADHD were in the atypical range according to the guidelines of Conners(2000), and low statistical power could thus be one important explanation for the lack ofstatistically significant results.

Another possible explanation for this lack of support for the CCPT-II’s potential sen-sitivity to ADHD and ODD symptomatology could be that we included children both witha probable and definite diagnosis according to the K-SADS-PL interview. Furthermore,our clinical diagnostic evaluation was based on information provided solely by the par-ent and the child. A recent study by Oosterlaan and colleagues (2005) found that it wasonly teacher-rated ADHD, not parent-rated ADHD, that contributed to the prediction ofneurocognitive test performance. The authors also found no neurocognitive deficits to beassociated with teacher- or parent-reported symptoms of ODD/CD. However, the studydid not include the CCPT-II in the neurocognitive test battery. Future studies of the utilityof the CCPT-II in distinguishing children with ADHD and/or ODD from normal controlsshould therefore include teacher symptom reports.

It has been shown repeatedly that children with ADHD and/or ODD commonlyobtain lower IQ scores than their peers (Frazier, Demaree, & Youngstrom, 2004; Koenenet al., 2006; Speltz et al., 1999). This hypothesis was partly supported in our study, aschildren with ADHD and ADHD+ODD had significantly lower IQ than normal controls.There were no significant differences in IQ scores between children with ADHD and ODD,and the mean IQ for children with “pure” ODD was not significantly lower than for normalcontrols. This indicates that, although the majority of children with ADHD have IQ scoresin the average range, ADHD is associated with having lower IQ than normal controls.ODD is probably not associated with lower IQ. But again, low statistical power due to arelatively small n in the ODD group could be an explanation for the lack of statisticallysignificant results.

A moderate-to-strong relationship between general intelligence and neurocognitivefunctions, such as attention, working memory, and inhibition, has already been establishedin the literature (Ackerman, Beier, & Boyle, 2005; Friedman et al., 2006; Mahone et al.,2002; Miyake et al., 2000; Schweizer & Moosbrugger, 2004). In support of the findings ofConners (2000), we found that, although the correlations between CCPT-II parameters andFSIQ were highly statistically significant, they were only small to moderate in strength.It could thus be argued that the CCPT-II is not merely a measure of general intellectualabilities, even though the CCPT-II performance of children with and without mental dis-orders increased with higher IQ. It is debated whether or not one should control for IQ instudies of neurocognitive dysfunction, as it can be argued that impaired intellectual func-tioning is a consequence of ADHD in itself (Barkley, 1997; Willcutt et al., 2005), and thatIQ never can be separated from the neurocognitive deficits associated with a developmen-tal disorder (Dennis et al., 2009). Thus, by controlling for IQ, a part of the core featureof ADHD is removed. Neurocognitive test performance is commonly used by cliniciansas an aid in diagnosing ADHD and other mental disorders in children, and it is important

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16 L. H. MUNKVOLD ET AL.

to understand how test performance relates to the child’s IQ. According to our results, IQscores accounted for a consistently greater proportion of variance in CCPT-II scores thandid the diagnostic group status. The contribution of the diagnosis variable was not statisti-cally significant on any CCPT-II parameter when IQ and sex was taken into account. Thus,our results indicate that IQ scores must be taken into account when interpreting low per-formance on neurocognitive tests. However, the explained variance in CCPT-II scores waslow, even when considering the combined contribution from sex, diagnostic status, and IQ.CCPT-II performance should be interpreted carefully when children have low IQ, and thefield needs more studies of the association between IQ and neurocognitive dysfunction andhow this relates to the behavioral expression of different mental disorders in children.

The main strengths of the present study are the inclusion of a relatively large sam-ple (n = 291) of boys and girls, the inclusion of children with both high and low IQ, andthe use of DSM-IV diagnoses based on a clinical evaluation. The main limitation of ourstudy is the use of a single test (CCPT-II) as a measure of neurocognitive dysfunctions.Different tests measure different aspects of neurocognition, and our results should not begeneralized across different neurocognitive domains. Previous studies have demonstratedlow sensitivity and limited discriminating ability when applying a single neurocognitivetest to differentiate children with psychiatric disorders from normal controls. The use ofa battery of tests is therefore recommended, although the improvement of the diagnosticefficiency by using multiple tests has been debated (Doyle, Biederman, Seidman, Weber, &Faraone, 2000). Another limitation is related to the fact that IQ is measured as a total score.A recent study has suggested that fluid intelligence, as compared to crystallized intelli-gence, provides significant information about neuropsychological impairments in childrenwith ADHD (Tillman, Bohlin, Sørensen, & Lundervold, 2009). A third limitation is thesmall size of the ODD group, and the inclusion of children with a probable diagnosis inthe ADHD, ODD, and ADHD+ODD groups.

Our results add to the growing number of studies indicating a high degree of vari-ability in neurocognitive test performance among children with mental disorders such asADHD and ODD (Doyle et al., 2000; McGee et al., 2000). This variability limits the util-ity of neurocognitive tests in making diagnostic differentiations, as our results indicatedspecifically for the CCPT-II. The clinical implication of our study is therefore that testperformance on the CCPT-II must be interpreted with caution in a clinical setting andshould be cross-validated with IQ scores. Practitioners need to be aware that the informa-tion yielded from behavioral rating scales, semi-structured interviews, and standardizedtests, such as the CCPT-II and the WISC-III, are likely to be inconsistent (Naglieri et al.,2005). The presence of neuropsychological dysfunction is neither sufficient nor neces-sary in order for a child to be diagnosed with ADHD or ODD (Willcutt et al., 2005). Thediagnostic assessment of psychiatric disorders in children still relies on a thorough clin-ical evaluation of information provided by informants who know the child well. Futureresearch should examine if children who have psychiatric disorders such as ADHD andODD and neurocognitive dysfunctions differ from those who have the disorder(s) with-out neurocognitive dysfunctions. As hypothesized by Naglieri et al. (2005), the distinctionbetween cognitive and behavioral dimensions in child psychopathology may hold diag-nostic utility and determine what specific interventions that should be provided for theindividual child.

Original manuscript received December 2, 2010Revised manuscript accepted November 25, 2012

First published online December 18, 2012

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CCPT-II IN CHILDREN WITH ADHD AND/OR ODD 17

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