Seidman, LJ- Impact of Gender and Age on Executive Functioning (2005)

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Impact of Gender and Age on ExecutiveFunctioning: Do Girls and Boys

With and Without Attention DeficitHyperactivity Disorder Differ

Neuropsychologically in Preteenand Teenage Years?

Larry J. Seidman Pediatric Psychopharmacology Unit, Psychiatry Service

Massachusetts General Hospital, Boston

Department of Psychiatry

Harvard Medical School

Department of Psychiatry Massachusetts Mental Health Center, Boston

Commonwealth Research Center,

Massachusetts Mental Health Center, Boston

Joseph Biederman, Michael C. Monuteaux, Eve Valera,and Alysa E. Doyle

Pediatric Psychopharmacology Unit, Psychiatry Service


Department of Psychiatry Harvard Medical School

Stephen V. Faraone Pediatric Psychopharmacology Unit, Psychiatry Service


Department of Psychiatry

Harvard Medical School

Department of Epidemiology

Harvard School of Public Health

DEVELOPMENTAL NEUROPSYCHOLOGY, 27 (1), 79–105Copyright © 2005, Lawrence Erlbaum Associates, Inc.

Requests for reprints should be sent to Larry J. Seidman, Pediatric Psychopharmacology Unit



ADHD is known to have neuropsychological correlates, characterized mainly by ex-

ecutive function (EF) deficits. However, most available data are based on studies of

boys through age 12. Our goal was to assess whether girls with ADHD expressneuropsychological features similar to those found in boys, and whether these im-

pairmentsare found in both preteen and teen samples. Participants were 101 girls and

103 boys with DSM–III–R ADHD, and 109 comparison girls and 70 boys without

ADHD, ages 9 to 17 years. Information on neuropsychological performance was ob-

tained in a standardized manner blind to clinical status. Primary regression analyses

controlled for age, socioeconomic status, learning disability, and psychiatric comor-

bidity. Girls and boys with ADHD were significantly more impaired on some mea-

sures of EFs than healthy comparisons but did not differ significantly from each

other. With the exception of 1 test score there were no significant Sex × Diagnosis in-

teractions. Moreover, there were no more significant interactions among age, gender,and diagnosis than would be expected by chance. Neuropsychological measures of

EFs were comparably impaired in girls compared to boys with ADHD, and these im-

pairments are found at ages 9 to 12 and ages 13 to 17. These findings suggest that ex-

ecutive dysfunctions are correlates of ADHD regardless of gender and age, at least

through the late teen years.

Cognitive deficits, particularly impairments in attention and executive functions

(EFs), are considered to be a core part of attention deficit hyperactivity disorder

(ADHD) (Barkley, 1997; Douglas, 1972). Many studies show that ADHD chil-dren are impaired on various tasks of vigilance, processing speed, verbal learn-

ing, memory, and EFs (e.g., set shifting, planning and organization, complex

problem solving, and response inhibition) (Barkley, 1997; Barkley, Grodzinsky,

& DuPaul, 1992; Denckla, 1991; Grodzinsky & Diamond, 1992; Pennington,

Groisser, & Welsh, 1993; Pennington & Ozonoff, 1996; Seidman, Benedict et

al., 1995; Seidman, Biederman, et al., 1995; Seidman, Biederman, Faraone,

Weber, Mennin, et al., 1997; Seidman, Biederman, Faraone, Weber, & Ouellette,

1997). These dysfunctions have been shown in a number of studies to persist

into late adolescence (at least in boys with ADHD; Fischer, Barkley, Edelbrock,& Smallish, 1990; Seidman, Biederman, Faraone, Weber, & Ouellette, 1997)

and adulthood (Seidman, Biederman, Weber, Hatch, & Faraone, 1998) and are

found in nonreferred siblings of ADHD patients who have been diagnosed with

ADHD (Seidman, Biederman, Monuteaux, Weber, & Faraone, 2000). More im-

portant, EF deficits have been shown to be independent of psychiatric comor-

bidity (Seidman, Biederman, Faraone, Weber, & Ouellette, 1997; Seidman et al.,

2000; Seidman et al., 1998).

The central theoretical construct guiding our neuropsychological understand-

ing of ADHD is that of executive dysfunction (Barkley, 1997). The hypothesis thatthe neuropsychological underpinnings of ADHD are characterized by executive

80 SEIDMAN ET AL.



damage (Mattes, 1980; Shue & Douglas, 1992). They observed that lesions in the

frontal lobe (and especially prefrontal cortex) in experimental animals and human

neurological patients are often associated with impulsivity, distractibility, and hy-peractivity, in combination or as isolated deficits (Fuster, 1989). EFs are distinct

from other mental functions such as perception or memory per se. There is, how-

ever, considerable overlap with domains such as attention, and with certain com-

ponents of learning and memory, such as those involved with encoding and re-

trieval (Pennington & Ozonoff, 1996).

Although this hypothesis has received general support, several studies have not

found EF deficits in children with ADHD, additional studies have found that chil-

dren with ADHD perform poorly on some EF tasks but not others, and EF deficits

are not unique to ADHD (cf. reviews in Barkley et al., 1992; Pennington &Ozonoff, 1996; Sergeant, Geurts, & Oosterlaan, 2002; and studies by Klorman et

al., 1999; and Weyandt & Willis, 1994). Moreover, individual classification of per-

sons with ADHD using neuropsychological measures has had limited success

(Doyle, Biederman, Seidman, Weber, & Faraone, 2000). These findings indicate

that more research is necessary, particularly on important dimensions known to ef-

fect neuropsychological functioning, such as age and sex.

Although ADHD affects both genders, most of the research literature, includ-

ing studies evaluating neuropsychological functioning, is devoted to males

(Berry, Shaywitz, & Shaywitz, 1985; Gaub & Carlson, 1997; Gershon, 2002).Gaub and Carlson’s review indicated that few studies included sufficient num-

bers of female participants to warrant gender-based conclusions. Nevertheless,

there are data supporting the presence of a valid syndrome of ADHD in girls. A

previous study of girls with Diagnostic and Statistical Manual of Mental Disor-

ders (3rd ed. [ DSM–III ]; American Psychiatric Association, 1980) attention defi-

cit disorder (Faraone, Biederman, Keenan, & Tsuang, 1991) documented the

same patterns of comorbidity and familiality in girls that had been observed in

boys. Recent work by our group (Biederman et al., 2002), reporting on the larg-

est data set to date on girls with ADHD, identified more similarities than differ-ences in the core features of ADHD with a few notable exceptions. Girls were

more likely than boys to have a somewhat higher rate of predominantly inatten-

tive type of ADHD (although the combined type was the leading type in both

genders), a lesser likelihood to have a learning disability (LD), a lesser likeli-

hood to manifest problems in school or in their spare time, and a lower risk for

comorbid conduct disorder and oppositional defiant disorder (Biederman et al.,

2002). Their results are consistent with Gershon’s meta-analytic review (2002)

that indicated more externalizing problems in boys with ADHD. Our research

team has also demonstrated that the familial transmission of ADHD andcomorbid disorders was similar in boys and girls (Faraone, Biederman, Mick, et

EXECUTIVE FUNCTIONING 81



Some research has suggested that girls with ADHD are more neuropsy-

chologically impaired than boys with the disorder (Gaub & Carlson, 1997). This

observation, although possibly true for measures of intelligence (Gershon,2002), may not generalize to EFs, which only partially overlap with intelligence

(Pennington & Ozonoff, 1996). Although the literature is limited, in fact, most

studies suggest that, although there are neuropsychological impairments in girls

with ADHD compared to control girls (Hinshaw, Carte, Sami, Treuting, &

Zupan, 2002; Seidman et al., 2004), there are no differences between girls and

boys with ADHD on EFs. For example, DeHaas (1986) showed that both girls

and boys with ADHD scored significantly below controls on digit span and all

subtests of the Stroop. However, there were no significant differences between

ADHD girls and ADHD boys. Similarly, Houghton et al. (1999) found differ-ences between ADHD girls and controls on the Stroop and Wisconsin Card

Sorting Test (WCST), but they failed to find differences between girls and boys

with ADHD. Several studies (Arcia & Conners, 1998; Breen, 1989; Horn, Wag-

ner, & Ialongo, 1989; Schuerholz, Singer, & Denckla, 1998; Sharp et al., 1999)

failed to find any gender differences on Continuous Performance Test (CPT)

measures. Castellanos et al. (2000) demonstrated that girls with ADHD per-

formed more poorly than healthy controls on delayed response and Go–No-go

oculomotor tasks, consistent with EF impairments that have been noted in boys,

but they did not examine gender differences. Nigg (1999), using a stop-signaltask measuring inhibition, showed that ADHD girls were slower to respond than

were controls. In a pilot study, we reported that girls might have a milder

neuropsychological syndrome than that observed in boys with ADHD (Seidman,

Biederman, Faraone, Weber, Mennin, et al., 1997). However, we subsequently

reanalyzed the data on ADHD girls and sex-matched controls in a sample almost

three times larger than the pilot study (Seidman et al., 2004). In this larger sam-

ple we found clear deficits in ADHD seemingly comparable to those observed in

boys with ADHD, although we did not directly compare girls and boys with

ADHD (Seidman et al., 2004). In a comparable study, also with a large sampleand an extensive neuropsychological battery, Hinshaw et al. (2002) demon-

strated significant impairments in girls with ADHD.

Only two studies found significant gender differences between ADHD boys

and girls on some attention and executive tasks. Rucklidge and Tannock (2001)

found that girls and boys with ADHD (ages 13–16) were both impaired in process-

ing speed compared to normal teenagers, but the boys with ADHD were slower in

processing speed than the girls with the disorder. However, Rucklidge and

Tannock (2001) did not demonstrate significant differences on the Block Design,

Digit Span, Symbol Search, and Arithmetic subtests of the Wechsler IntelligenceScale–Third Edition (WISC–III; Wechsler, 1991) or on measures of word identifi-

82 SEIDMAN ET AL.



that ADHD girls made significantly fewer CPT impulsivity errors than did ADHD

boys, although no normal controls were studied. Newcorn et al. (2001) did not find

significant differences on the CPT Inattention and Dyscontrol scales.More important, very few studies have evaluated the effects of age on neuropsy-

chological function in ADHD, and none have addressed age in the context of

neuropsychological function in both genders. Surprisingly, whereas there are now

numerous studiesof adults with ADHD(a recent meta-analysis byHervey, Epstein,

& Curry, 2004, reviewed33 studies), there are only a handfulof studiesof teenagers

withADHD(Fischer etal., 1990;Newcorn etal.2001;Rucklidge& Tannock,2001;

Seidman, Biederman, Faraone, Weber, & Ouellette, 1997). The vast majority of re-

searchhasfocusedonchildrenunderage 13.We previouslyevaluated boyswithand

withoutADHD DiagnosticandStatisticalManualofMentalDisorders(3rded.,rev.[ DSM–III–R]; American Psychiatric Association, 1987), ages 9 to 22, on a wide

range of neuropsychological measures, including such EF measures as the Stroop,

WCST, AuditoryCPT(ACPT), andRey–OsterriethComplex Figure(ROCF),anda

measure ofverbal learning.We foundthat youngerandolderboyswithADHDwere

comparably impaired on the Stroop, WCST, and ROCF when contrasted with

age-matched controls above and below 15 years of age (Seidman, Biederman,

Faraone, Weber, & Ouellette, 1997). The older groups of controls and ADHD boys

showed better performance than the younger groups, but there was no Group × Age

interaction.Thus, the extant literature suggests effects of diagnosis (ADHD vs con-trol) and age, but no interactions. A similar finding was reported by Weyandt and

Willis (1994) in younger children.

This literature review suggests that there are some EF impairments in girls with

ADHD but provides limited data about age or gender differences on measures of

executive functioning. Moreover, methodological limitations impede conclusive

interpretations. These include (a) small sample sizes that do not provide enough

power to be conclusive; (b) failure to routinely include a substantial group of male

and female controls to address normal sex differences (Arnold, 1996); (c) failure to

evaluate teenage participants; virtually all studies are of children ages 6 to 12 or of adults; (d) relatively limited sets of EF measures that may not enable an evaluation

of an appropriate range of measurement; and (e) failure to control for the common

psychiatric comorbidities and learning disabilities (Faraone, Biederman, Mon-

uteaux, Doyle, & Seidman, 2001; Seidman, Biederman, Monuteaux, Doyle, &

Faraone, 2001; Semrud-Clikeman et al., 1992).

These data suggest the need for a well-controlled study using a large sample of

boys and girls with ADHD, from childhood through teenage years, using a range

of well-accepted measures of executive functioning. Thus, in this study, we evalu-

ate whether girls with ADHD have neuropsychological features that are similar tothose found in boys, and whether comparable neuropsychological deficits are ob-




tween the sexes. Furthermore, we expected that the observed group differences

(ADHD vs. control) would not be accounted for by psychiatric comorbidity, learn-

ing disabilities, or medications.

METHOD

Participants

Data from two virtually identical family studies of ADHD(differing only in ratesof

different ethnicities and range of ages at neuropsychological testing) were com-

bined. The first study (Biederman et al., 1992) provided neuropsychological data

from118maleADHDcasesand99controls,ages9to20,inwhichtheeffectsofagehad been previously studied (Seidman, Biederman, Faraone, Weber, & Ouellette,

1997).Thesecondstudy(Biedermanetal.,1999)providedneuropsychologicaldata

from140 femaleADHDcases and 122 comparisonchildren aged 6 to17 at the time

of ascertainment. Ina pilot studyof neuropsychological functioning inADHD girls,

we reported on a small subset of this sample; 43 girls, ages 6 to 17 years with

DSM–III–RADHD,and36comparisongirlswithoutADHD(Seidman,Biederman,

Faraone, Weber, Mennin, et al., 1997). We subsequently reanalyzed these data with

the complete girls sample described previously (Seidman et al., 2004). We havenot

previously reported any direct comparisons of executive functioning between theboys’andgirls’samples.Becausethegirls’samplerangedinagefrom6to17andthe

boys’sample rangedinage from9 to20at the timeoftesting,analyseswithboysand

girls were restricted to the age overlap (ages 9–17 inclusive, “age-restricted” sam-

ple). Participants were 101 girls (mean age 12.5 years, SD = 2.6) and 103 boys with

ADHD (mean age 13.5 years, SD = 2.2) and 109 comparison girls (mean age 12.7

years, SD = 2.6) and 70boys without ADHD(mean age 13.3years,SD = 2.5), rang-

ing from 9 to 17 years.

We obtained informed consent for all participants. Parents provided written in-

formed consent for their children, and children and adolescents provided writtenassent. All male participants were English-speaking, White, and non-Hispanic. In

the female sample, all participants were English-speaking, 91.6% were White,

5.3% African American, 1.9% Hispanic, and 1.2% Asian Americans. We excluded

children if they had major sensory–motor handicaps (e.g., paralysis, deafness,

blindness), psychosis, autism, or an estimated Full Scale IQ (FSIQ) less than 80.

Each of the cases of ADHD met diagnostic criteria for current ADHD at the time of

the clinical referral; at the time of testing, each had active symptoms of the disor-

der. This study is a naturalistic sample of referred persons in which some persons

with ADHD have been previously medicated. A subset of the sample described as“unmedicated” refers to absence of use of any psychotropic medications at the

84 SEIDMAN ET AL.



Psychiatric Assessments

All diagnostic assessments used structured interviews based on the criteria of the

DSM–III–R. Psychiatric assessments relied on the epidemiologic version of the

Schedule for Affective Disorder and Schizophrenia for Children (Orvaschel,

1985). Diagnoses were based on independent interviews with the mothers and di-

rect interviews of children except for children younger than 12 years of age, who

were not directly interviewed. The structured interviews assessed lifetime history

of psychopathology. ADHD symptoms reported here were measured at the time of

neuropsychological testing. The assessment personnel were blind to diagnosis

(ADHD or control) and ascertainment site (psychiatric or pediatric). All neuropsy-

chological function assessments were administered and scored by examiners who

were unaware of all other data on the participants.

Because the neuropsychological performance of the boys’sample was assessed

prior to the publication of DSM–IV, we used DSM–III–R criteria to define ADHD

case status. Similarly, the study of girls was developed and probands ascertained

before DSM–IV was made available. Thus, the case definition of all participants

was based on DSM–III–R criteria, which precludes the stratification of the sample

by DSM–IV ADHD subtypes.

The interviewers or testers had undergraduate degrees in psychology, and they

were trained to high levels of interrater reliability for psychiatric diagnosis by the

second author. We computed kappa coefficients of agreement by having experi-

enced, board-certified child and adult psychiatrists diagnose participants from

audiotaped interviews made by the assessment staff. Based on 173 interviews from

a mixed pediatric and adult data set, the median kappa for all diagnoses was 0.86;

the kappa for ADHD was 0.98, 0.93 for conduct disorder, 0.80 for multiple anxiety

disorders, and 0.83 for major depression.

A committee of board-certified child and adult psychiatrists resolved all diag-

nostic uncertainties. The committee members were blind to the participants’ascer-

tainment group, ascertainment site, all data collected from other family members,

and all nondiagnostic data (e.g., neuropsychological tests). Diagnoses were con-

sidered positive if, based on the interview results, DSM–III–R criteria were un-

equivocally met to a clinically meaningful degree. Rates of psychiatric disorders

reported here are lifetime prevalences. Psychiatric comorbidity was operationally

defined by presence of any of the following: two or more anxiety disorders, major

depression, or conduct disorder.

Neuropsychological Tests

Based on our review of the literature and our previous neuropsychological work




of the integrity of fronto-subcortical brain systems hypothesized to be abnormal in

ADHD (Mattes, 1980). The tests chosen include measures of vigilance (ACPT),

planning and organization (ROCF organization), response inhibition (StroopColor and Word Test), set shifting and categorization (WCST perseverations and

categories sorted), and verbal and visual learning and memory (Wide Range As-

sessment of Memory and Learning [WRAML] list learning). The tests used are

considered estimates of the hypothesized cognitive functions.

As in previous studies, tests were administered in a fixed order: (a) the ROCF

Copy (Osterrieth, 1944; Rey, 1941); (b) the Wechsler Intelligence Scale for

Children–Revised (WISC–R; Wechsler, 1974)–Wechsler Adult Intelligence

Scale–Revised (WAIS–R; Wechsler, 1981) Vocabulary and Digit Span; (c) the

ROCF Recall; (d) the WISC–R–WAIS–R Block Design, Arithmetic andCoding–Digit Symbol subtests; (e) the ACPT (Weintraub & Mesulam, 1985); (f)

the WRAML list learning test for children < 17 (Adams & Sheslow, 1990), or

the California Verbal Learning Test (CVLT) in children ≥ 17 years of age

(Delis, Kramer, Kaplan, & Ober, 1987); (g) the computerized WCST (Heaton,

Chelune, Talley, Kay, & Curtiss, 1993); and (h) the Stroop test (Golden, 1978).

There were very few participants in the age range (17–18), so no data is pre-

sented on the CVLT.

For the ACPT we measured omission, commission, and late errors that were

summed to a “total errors” score. We chose the WRAML list learning test for chil-dren <17 because the CVLT–Children’s Version (CVLT–C) was not available at

the time the study began, and it allowed a roughly comparable measure of verbal

learning. To make the WRAML verbal learning test more comparable to the CVLT

we added a fifth learning trial.

The ROCF was administeredandscored according to the methods of Waber and

Holmes (1985) subsequent to training by one of this system’s originators (Jane

Holmes Bernstein, PhD). This method was chosen because we hypothesized that

participants with ADHD would have organization deficits in contrast to simple vi-

sual–spatial deficits; the developmental scoring of Waber and Holmes assessessuch strategies. We used the “Organization” score of the ROCF because it reflects

planning, decision making, and strategy in constructing a figure (on copy and from

memory). Thus, the Organization score distinguishes EFs from visual–spatial pro-

cesses, which are codified by the “Accuracy” score. The analysis of the process by

which a person constructs a figure is considered to be a good index of executive

functioning (Kaplan, 1990; Seidman, 1997). Further administration and scoring

details on the ROCF are provided elsewhere (Seidman, Benedict, et al., 1995;

Teknos, Bernstein, & Seidman, 2003). The tests used in the study have interrater

reliabilities in the 0.90s (Lezak, 1995; Wechsler, 1981).All tests were administered and scored by examiners who were supervised by

86 SEIDMAN ET AL.



et al., 2002; Faraone et al., 1993; Faraone, Biederman, Mennin, Gershon, &

Tsuang, 1996), we will only report (for descriptive purposes) estimated FSIQ

(Brooker & Cyr, 1986), based on the vocabulary and block design subtests of theWISC–R (Wechsler, 1974) or WAIS–R (Wechsler, 1981). These two subtests are

frequently used for an IQ estimate because their estimate of IQ shows a high corre-

lation with FSIQ based on all of the subtests (Sattler, 1988). Academic achieve-

ment was assessed with the Reading and Arithmetic tests of the Wide Range

Achievement Test–Revised (WRAT–R) (Jastak & Jastak, 1985) to define forms of

LD. Participants with ADHD and LDs were grouped into one LD category, com-

bining arithmetic and reading disabilities when present. We used the procedure

recommended by Reynolds (1984) and others (Frick et al.,1991) to define LD.

FSIQ and achievement scores are initially converted to the z scores ZIQ and ZA,respectively. Expected achievement score, ZEA, is then estimated by the regres-

sion equation:

ZEA = rIQA ×ZIQ

In which rIQA is the correlation between the IQ and achievement tests. Values

from the control sample were used. Then, the discrepancy score is ZEA – ZA and

its SD = (1 – r2IQA)½. We defined as LD any participant who had a value greater

than 1.65 on the standardized discrepancy score:

(ZEA-ZA)/(1–r2IQA)½

Plan of Analysis

We chose 17 neuropsychological scores from five tests (Stroop, WCST, WRAML,

ACPT, and ROCF) as dependent measures for analysis. Three independent vari-

ables were used in analyses: Group (ADHD vs. Control), sex, and age. We first

modeled the neuropsychological variables as outcomes in linear regression models

with ADHD group as the independent variable, controlling for socioeconomic sta-tus (SES; Hollingshead, 1975), age, psychiatric comorbidity, and LD. To address

the comparability of executive functioning in girls and boys with and without

ADHD, we tested the interaction between ADHD status and gender, with the

neuropsychological variables as the outcomes. This interaction term tests if the ef-

fect of ADHD on neuropsychological performance differs by gender. If this inter-

action term is significant at α = 0.05, we present results separately by gender. If it is

not significant, we combine the samples and present the effect of ADHD on

neuropsychological performance, controlling for SES, age, psychiatric

comorbidity, LD, and gender. Analyses were also repeated with just the unmedi-cated participants, and using IQ as a covariate. Also, to assess the impact of age on




these subgroups. Ordinary least squares regression models were used for all analy-

ses, as implemented in STATA (Stata Corporation, 1992). All tests were two-tailed

and the alpha was set at 0.05.

RESULTS

We first present analyses testing whether girls with ADHD have neuropsycho-

logical features that are similar to those found in boys (“full sample”), followed up

by identical analyses of the smaller group of unmedicatedparticipants. We hypoth-

esized that EF deficits would be comparable between the sexes and that the ob-

served group differences (ADHD vs. control) would not be accounted for by psy-

chiatric comorbidity, learning disabilities, or medications.

Demographic Characteristics and Academic Functioning in

Full Sample (Table 1)

We found a number of differences in demographics and academic functioning be-

tween the boys and girls with ADHD as compared to controls. Not unexpectedly,

the combined sample of boys and girls with ADHD had significantly more psychi-atric comorbidity, higher rates of learning disabilities, more frequent use of

psychotropic medications, lower IQ estimates, lower achievement in arithmetic

and reading, and lower SES, compared to the controls. Girls with ADHD differed

significantly from controls on all clinical variables just described. Similarly, and

not surprisingly, boys with ADHD differed from the male comparisons on all the

same variables. Control girls had significantly lower grade levels, SES, and IQ es-

timates than control boys. Finally, ADHD girls were significantly younger and

from a lower grade level, had fewer LDs, more ADHD symptoms, and a lower IQ

estimate than ADHD boys.

Neuropsychological Functioning in the Full Sample of

ADHD Participants

There were significant group effects (ADHD participants performed worse in all

cases) on all four variables from the Stroop and on the WCST number of categories

sorted, perseverative, and nonperseverative error scores (see Table 2). Controlling

for IQ did not affect the Stroop but did attenuate the WCST scores.

There was almost no evidence of a Sex × Group interaction effect as only 1 of 17 variables was significant: ROCF Copy organization showed a significant effect

88 SEIDMAN ET AL.



T A B L E 1

D e m o g r a p h i c V a r i a b l e

s f o r A l l B o y s a n d G i r l s W i t h A D H D a n d C o n t r o l s B e t w e e n t h e A g e s o f 9 a n d 1 7

A D H D

C o n t r o l s

g r a p h i c

V a r i a b l e s

G i r l s ( n = 1 0 1

)

B o y s ( n = 1 0 3 )

T

o t a l ( n = 2 0 4 )

G i r l s ( n = 1

0 9 )

B o y s ( n = 7 0 )

T o t a l (

n = 1 7 9 )

1 2 . 5

a * * ( 2 . 6 )

1 3 . 5 ( 2 . 2 )

1 3 . 0 ( 2 . 4 )

1 2 . 7 ( 2 . 6 )

1 3 . 3 ( 2 . 5 )

1 3 . 0 ( 2 . 6 )

7 . 0 a * * ( 2 . 6 )

7 . 8 ( 2 . 2 )

7 . 4 ( 2 . 5 )

7 . 3 a * ( 2 . 6

)

8 . 0 ( 2 . 7 )

7 . 6 ( 2 . 7 )

1 . 8 ( 0 . 9 )

1 . 9 b * * ( 1 . 0 )

1 . 9 c * * ( 0 . 9 )

1 . 7 a * ( 0 . 8

)

1 . 4 ( 0 . 7 )

1 . 6 ( 0 . 8 )

i a t r i c c o m o r b i d i t y

5 1 % b * * ( N = 5 1 )

6 3 % b * * ( N = 6 5 )

5 7 % c * * ( N = 1 1 6 )

6 % ( N = 7 )

1 4 % ( N = 1 0 )

9 %

( N = 1 7 )

i n g d i s a b i l i t y

1 8 % a * * b * * ( N =

1 8 )

4 6 % b * * ( N = 4 5 )

3 2 % c * * ( N = 6 3 )

5 % ( N = 5 )

1 3 % ( N = 9 )

8 %

( N = 1 4 )

c a t e d

6 5 % b * * ( N = 6 6 )

6 3 % b * * ( N = 6 5 )

6 4 % c * * ( N = 1 3 1 )

0 % ( N = 0 )

0 % ( N = 0 )

0 %

( N = 0 )

D s y m p

t o m s d

1 1 . 6

a * * b * * ( 1 . 9 )

9 . 3 b * * ( 3 . 6 )

1 0 . 5 c * * ( 3 . 1 )

1 . 4 ( 2 . 2 )

1 . 9 ( 2 . 6 )

1 . 6 ( 2 . 4 )

i m a t e

1 0 5 . 7 a * b * * ( 1 1 . 5 )

1 0 9 . 0 b * * ( 1 3 . 5 )

1 0 7 . 4 c * * ( 1 2 . 6 )

1 0 9 . 8 a * * ( 1

1 . 0 )

1 1 7 . 7 ( 1 0 . 5 )

1 1 2 . 9 ( 1 1 . 4 )

T – R A r i t h m e t i c

9 5 . 9

b * * ( 1 3 . 8 )

9 3 . 0

b * * ( 1 8 . 2 )

9 4 . 5 c * * ( 1 6 . 0 )

1 0 6 . 5 ( 1 5 . 7

)

1 0 9 . 9 ( 1 5 . 3 )

1 0 7 . 8 ( 1 5 . 6 )

T – R R e

a d i n g

1 0 0 . 7 b * * ( 1 5 . 6 )

1 0 1 . 3 b * * ( 1 6 . 3 )

1 0 1 . 1 c * * ( 1 5 . 9 )

1 1 0 . 0 ( 1 0 . 4

)

1 1 1 . 5 ( 1 0 . 2 )

1 1 0 . 6 ( 1 0 . 3 )

o t e . V

a l u e s i n t a b l e r e f l e c t m e a n s a n d s t a

n d a r d d e v i a t i o n s ( i n p a r e n t h e s e s ) u n l e s s o t h e r w i s e n o t e d . I Q e s t i m a t e b a s e d o n t h e V o c a b u l a r y a n d B l o c k D e s i g n

B r o o k e

r & C y r , 1 9 8 6 ) o f t h e W e c h s l e r

I n t e l l i g e n c e S c a l e f o r C h i l d r e n – R

e v i s e d ( W e c h s l e r , 1 9 7 4 ) o r t h e W

e c h s l e r A d u l t I n t e l l i g e n c e S c a l e

– R e v i s e d

h s l e r , 1 9 8 1 ) . A D H D = a t t e n t i o n d e f i c i t h y

p e r a c t i v i t y d i s o r d e r ; S E S = s o c i o e

c o n o m i c s t a t u s ( H o l l i n g s h e a d , 1 9 7 5 ) ; W R A T – R = W i d e R a n g e A c h

i e v e m e n t

R e v i s e d

( J a s t a k & J a s t a k , 1 9 8 5 ) .

G e n d e r e f f e c t w i t h i n d i a g n o s t i c s t a t u s . b A D H D e f f e c t w i t h i n g e n d e r . c D i f f e r e d f r o m t o t a l c o n t r o l g r o u p . d R e f e r s t o c u r r e n t A D H D s y m p t o m s e x p e r i e n c e d

n t h e p a

s t m o n t h .

< . 0 5 .

* * p < . 0 1 .



T A B

L E 2

N e u r o p s y c h o l o g i c a l P e r f o r m a n c e o f A l l B o y s a n d G i r l s

W i t h A D H D a n d C o n t r o l s B e t w

e e n t h e A g e s o f 9 a n d 1 7

C o n t r o l

A D H D

G i r l s a

B o y

s b

G i r l s c

B o y s d

h o l o g i c

a l T a s k

M

S D

M

S D

M

S D

M

S

D

G e n d e r

S t a t u s

I n t e r a c t i o n

t w s c o r e

8 8 . 6

1 3 . 7

8 8 . 1

1 6 . 8

7 9 . 6

1 6 . 0

8 1 . 7 1

6 . 4

t ( 3 5 6 ) = 0 . 3 , p = . 7 8 3

t ( 3 5 6 ) = – 3 . 3 , p = . 0 0 1 * *

t ( 3 5 5 ) = 1 . 2 , p = . 2 2 0

aw s c o r e

6 1 . 3

1 3 . 4

5 9 . 3

1 2 . 9

5 4 . 8

1 4 . 8

5 5 . 6 1

2 . 8

t ( 3 5 6 ) = – 2 . 0 , p = . 0 5 0 * *

t ( 3 5 6 ) = – 2 . 9 , p = . 0 0 4 *

t ( 3 5 5 ) = 1 . 5 , p = . 1 4 2

W o r d r a w s c o r e

3 5 . 5

9 . 7

3 5 . 6

1 0 . 7

2 9 . 4

1 1 . 5

3 0 . 7 1

0 . 8

t ( 3 5 6 ) = – 0 . 2 , p = . 8 5 0

t ( 3 5 6 ) = – 4 . 3 , p = . 0 0 0 * *

t ( 3 5 5 ) = 0 . 8 , p = . 4 2 9

e n c e t s c o r e

5 0 . 9

6 . 3

5 1 . 0

6 . 6

4 8 . 2

7 . 2

4 8 . 4

7 . 7

t ( 3 5 5 ) = 0 . 2 , p = . 8 2 8

t ( 3 5 5 ) = – 2 . 8 , p = . 0 0 5 *

t ( 3 5 4 ) = 0 . 1 , p = . 9 1 4

C a r d S

o r t T e s t

i e s

5 . 3

1 . 4

5 . 5

1 . 0

5 . 0

1 . 7

4 . 8

1 . 8

t ( 3 0 9 ) = – 0 . 2 , p = 8 3 2

t ( 3 0 9 ) = – 2 . 5 , p = . 0 1 3

t ( 3 0 8 ) = – 1 . 1 , p = . 2 5 9

t o m a i n

t a i n s e t

1 . 1

1 . 2

1 . 1

1 . 3

1 . 2

1 . 4

1 . 1

1 . 2

t ( 3 0 9 ) = 0 . 1 , p = . 9 1 3

t ( 3 0 9 ) = 0 . 2 , p = . 8 1 0

t ( 3 0 8 ) = – 0 . 2 , p = . 8 7 3

r a t i v e e r r o r s

1 5 . 1

1 0 . 2

1 1 . 3

7 . 9

1 7 . 1

1 2 . 8

1 6 . 7 1

1 . 7

t ( 3 0 9 ) = – 0 . 8 , p = . 4 4 9

t ( 3 0 9 ) = 2 . 3 , p = . 0 2 4

t ( 3 0 8 ) = 1 . 1 , p = . 2 8 1

s e v e r a t i v e e r r o r s

1 5 . 4

9 . 4

1 1 . 8

8 . 0

1 6 . 7

1 3 . 1

1 8 . 3 1

3 . 8

t ( 3 0 9 ) = 0 . 1 , p = . 9 3 5

t ( 3 0 9 ) = 2 . 6 , p = . 0 1 1

t ( 3 0 8 ) = 1 . 8 , p = . 0 7 2

t o t a l w o r d s

o n 5 t r i a l s

5 0 . 3

8 . 2

5 0 . 6

1 0 . 2

4 7 . 4

1 1 . 1

4 6 . 2 1

1 . 2

t ( 3 1 8 ) = – 0 . 5 , p = . 6 4 0

t ( 3 1 8 ) = – 1 . 5 , p = . 1 3 4

t ( 3 1 7 ) = – 0 . 6 , p = . 5 7 9



C P T

o n s

1 . 9

2 . 4

1 . 7

2 . 2

2 . 6

3 . 2

2 . 6

3 . 0

t ( 3 5 8 ) = – 0 . 3 , p = . 7 6 0

t ( 3 5 8 ) = 0 . 8 , p = . 4 2 8

t ( 3 5 7 ) = 0 . 2 , p = . 8 4 1

s s i o n s

0 . 1

0 . 3

0 . 2

0 . 4

0 . 2

0 . 5

0 . 4

1 . 2

t ( 3 5 6 ) = 1 . 7 , p = . 0 8 6

t ( 3 5 6 ) = 0 . 9 , p = . 3 6 8

t ( 3 5 5 ) = 0 . 3 , p = . 7 8 3

p o n s e s

2 . 3

2 . 3

2 . 2

2 . 3

2 . 9

3 . 1

2 . 1

1 . 9

t ( 3 6 0 ) = – 0 . 5 , p = . 6 4 1

t ( 3 6 0 ) = 0 . 8 , p = . 4 0 6

t ( 3 5 9 ) = – 1 . 5 , p = . 1 4 9

r o r s

4 . 3

3 . 9

4 . 1

3 . 5

5 . 7

5 . 0

5 . 1

4 . 4

t ( 3 5 6 ) = – 0 . 1 , p = . 9 3 7

t ( 3 5 6 ) = 1 . 3 , p = . 2 0 7

t ( 3 5 5 ) = – 0 . 8 , p = . 4 4 0

r e i t h

g a n i z a t i o n

9 . 0

3 . 3

1 0 . 5

3 . 3

8 . 6

3 . 8

8 . 5

4 . 0

—

— e

t ( 3 4 4 ) = – 2 . 4 , p = . 0 1 6 *

t a l a c c u

r a c y

6 4 . 2

2 . 5

6 4 . 2

2 . 8

6 3 . 3

3 . 9

6 2 . 9

6 . 0

t ( 3 4 4 ) = – 0 . 4 , p = . 6 7 9

t ( 3 4 4 ) = – 1 . 6 , p = . 1 0 1

t ( 3 4 3 ) = 0 . 0 , p = . 9 9 4

r g a n i z a

t i o n

7 . 6

4 . 2

8 . 9

4 . 2

7 . 0

3 . 9

7 . 3

4 . 5

t ( 3 3 5 ) = 1 . 3 , p = . 2 1 3

t ( 3 3 5 ) = – 1 . 5 , p = . 1 4 2

t ( 3 3 4 ) = – 1 . 3 , p = . 2 0 7

o t a l a c c u r a c y

4 6 . 2

9 . 6

5 2 . 0

8 . 2

4 7 . 5

1 0 . 9

4 9 . 7 1

1 . 6

t ( 3 3 5 ) = 2 . 8 , p = . 0 0 5

t ( 3 3 5 ) = 0 . 2 , p = . 8 6 9

t ( 3 3 4 ) = – 1 . 6 , p = . 1 1 5

P v a l u

e s a r e b a s e d o n t h e p r i m a r y r e g r e s

s i o n a n a l y s e s c o n t r o l l i n g s i m u l t a n

e o u s l y f o r a g e , s o c i o e c o n o m i c s t a

t u s , p s y c h i a t r i c c o m o r b i d i t y , a n d l e a r n i n g d i s a b l i l i t y ;

k s i n d i c a t e a s i g n i f i c a n t e f f e c t c o n t r o l l i n g f o r t h e s e v a r i a b l e s a n d I Q s . G e n

d e r a n d s t a t u s c o l u m n s a r e d e r i v e d f r o m m o d e l s r u n i n d e p e n d e n t l y o f t h e i n t e r a c t i o n

D H D = a t t e n t i o n d e f i c i t h y p e r a c t i v i t y d i s o r d e r ; W R A M L = W i d e R a n g e A c h

i e v e m e n t T e s t o f M e m o r y a n d L e a r n i n g ( A d a m s & S h e s l o w , 1 9 9 0 ) ;

C P T = C o n t i n u o u s

c e T e s t .

– 1 0 9 . S a m p l e s i z e s v a r y f o r d i f f e r e n t t e s t s d u e t o m i s s i n g d a t a . b n = 6 1 – 7 0 .

c n = 7 6 – 1 0 0 . d n = 8 6 – 9 8 . e A D H D

e f f e c t f o r b o y s , t ( 1 5 4 ) = – 2 . 7 , p = . 0 0 8 ; A D H D e f f e c t

1 9 6 ) =

– 0 . 5 , p = . 6 0 8 .

0 5 . * * p < . 0 1 .



There was little evidence of gender effects as only 2 of 17 models were signifi-

cant: the Stroop color score and ROCF accuracy of delayed recall. IQ correction

did not change the pattern of these results.We directly contrasted neuropsychological functioning between boys and

girls with ADHD, controlling for age, LD, symptom level, and IQ (not shown in

tables). Only 2 of 17 variables were significantly different: WCST categories

sorted and nonperseverative errors were slightly worse in boys than girls with

ADHD ( p < .05). The results were the same for analyses restricted to partici-

pants of White descent.

Neuropsychological Functioning in Unmedicated ADHD

Participants and Controls

We repeated the identical regression analyses with controls and persons with

ADHD who were unmedicated. There were significant group effects (ADHD par-

ticipants performed worse in all cases) on three variables from the Stroop and on

the WCST number of categories sorted, and nonperseverative errors, and on the

ROCF Copy organization score. Controlling for IQ tended to attenuate the results

(see Table 3).

There was no robust evidence of a Sex × Group interaction effect as only 1 of 17

variables was significant: ROCF Copy organization showed a significant effect ac-counted for by a large drop off in organization among the boys with ADHD com-

pared to male controls. IQ had little effect on these results.

Overall, there was little evidence of the effects of gender as only 3 of 17 com-

parisons were significant, and these were all on the ROCF. Controlling for IQ

tended to attenuate the results.

We evaluate whether the neuropsychological deficits observed in boys and girls

with the disorder are comparable in preteen and teenage years.

Effects of Age on Neuropsychological

Functioning in ADHD and Controls

Table 4 presents the demographic data for the age and sex stratified groups. Based

on visual inspection of the raw neuropsychological scores in Table 5, girls and

boys with and without ADHD in the 13 to 17 age group had better performance on

virtually all variables (65 of 68 comparisons) compared to those in the 9 to 12 age

group. This is consistent with our findings previously published with the sample of

boys, which showed age effects on most neuropsychological variables, but no

age-by-group interaction (Seidman, Biederman, Faraone, Weber, & Ouellette,1997). In these analyses, with the combined sample of boys and girls only 2 of the

92 SEIDMAN ET AL.



T A B

L E 3

N e u r o p s y c h o l o g i c a l T e s t P e r f o r m a n c e o f C o n t r o l s a n d U n m e d i c a t e d A D H D B o y s a n d G i r l s

B e t w e e n t h e A g e s o f 9 a n d 1 7

C o n t r o l

A D H D

G i r l s a

B o

y s b

G i r l s c

B o y s d

c h o l o g i c

a l T a s k

M

S D

M

S D

M

S D

M

S D

G e n d e r

S t a t u s


s t a w s c o r e

8 8 . 6

1 3 . 7

8 8 . 1

1 6 . 8

7 9 . 1

1 4 . 6

8 5 . 4

1 5 . 2

t ( 2 3 4 ) = 0 . 5 , p = . 6 3 3

t ( 2 3 4 ) = – 2 . 6 , p = . 0 1 1 *

t ( 2 3 3 ) = 1 . 8 , p = . 0 6 8

a w s c o r e

6 1 . 3

1 3 . 4

5 9 . 3

1 2 . 9

5 4 . 1

1 3 . 5

5 7 . 8

1 0 . 9

t ( 2 3 4 ) = – 1 . 5 , p = . 1 2 8 *

t ( 2 3 4 ) = – 2 . 8 , p = . 0 0 6 *

t ( 2 3 3 ) = 1 . 9 , p = . 0 5 9

w o r d r a w s c o r e

3 5 . 5

9 . 7

3 5 . 6

1 0 . 7

2 9 . 1

1 1 . 8

3 2 . 7

1 1 . 5

t ( 2 3 4 ) = 0 . 3 , p = . 7 6 6

t ( 2 3 4 ) = – 2 . 9 , p = . 0 0 5

t ( 2 3 3 ) = 1 . 5 , p = . 1 4 9

e n c e t s c o r e

5 0 . 9

6 . 3

5 1 . 0

6 . 6

4 7 . 2

7 . 3

4 9 . 0

8 . 7

t ( 2 3 4 ) = 0 . 7 , p = . 4 8 9

t ( 2 3 4 ) = – 1 . 8 , p = . 0 6 7

t ( 2 3 3 ) = 1 . 0 , p = . 3 1 4

C a r d S

o r t T e s t

i e s

5 . 3

1 . 4

5 . 5

1 . 0

4 . 8

1 . 8

4 . 6

1 . 9

t ( 2 0 2 ) = 0 . 9 , p = . 3 7 1

t ( 2 0 2 ) = – 2 . 0 , p = . 0 4 3

t ( 2 0 1 ) = – 0 . 6 , p = . 5 5 7

t o m a i n

t a i n s e t

1 . 1

1 . 2

1 . 1

1 . 3

1 . 3

1 . 5

1 . 1

1 . 3

t ( 2 0 2 ) = 0 . 1 , p = . 8 8 7

t ( 2 0 2 ) = 0 . 7 , p = . 4 7 0

t ( 2 0 1 ) = – 0 . 2 , p = . 8 4 0

r a t i v e e

r r o r s

1 5 . 1

1 0 . 2

1 1 . 3

7 . 9

1 6 . 6

1 4 . 3

1 6 . 4

9 . 8

t ( 2 0 2 ) = – 1 . 7 , p = . 0 9 3

t ( 2 0 2 ) = 1 . 3 , p = . 2 0 9

t ( 2 0 1 ) = 0 . 7 , p = . 4 9 3

s e v e r a t i v e e r r o r s

1 5 . 4

9 . 4

1 1 . 8

8 . 0

1 6 . 8

1 2 . 7

2 0 . 6

1 6 . 1

t ( 2 0 2 ) = – 0 . 8 , p = . 4 2 8

t ( 2 0 2 ) = 2 . 2 , p = . 0 3 3

t ( 2 0 1 ) = 1 . 8 , p = . 0 6 7

t o t a l w o r d s

o n 5 t r i a l s

5 0 . 3

8 . 2

5 0 . 6

1 0 . 2

4 7 . 3

1 0 . 9

4 7 . 1

9 . 7

t ( 2 0 9 ) = 0 . 2 , p = . 8 7 0

t ( 2 0 9 ) = – 1 . 3 , p = . 1 8 6

t ( 2 0 8 ) = – 0 . 1 , p = . 9 2 1

( c o n t i n u e d )



T A B L E 3 ( C o n t i n u e d )

C o n t r o l

A D H D

G i r l s a

B o

y s b

G i r l s c

B o y s d

c h o l o g i c

a l T a s k

M

S D

M

S D

M

S D

M

S D

G e n d e r

S t a t u s


C P T

o n s

1 . 9

2 . 4

1 . 7

2 . 2

2 . 7

2 . 9

2 . 4

2 . 8

t ( 2 3 4 ) = – 0 . 9 , p = . 3 8 2

t ( 2 3 4 ) = 1 . 1 , p = . 2 7 7

t ( 2 3 3 ) = – 0 . 1 , p = . 8 8 8

s s i o n s

0 . 1

0 . 3

0 . 2

0 . 4

0 . 1

0 . 4

0 . 1

0 . 4

t ( 2 3 2 ) = 1 . 7 , p = . 0 9 8 *

t ( 2 3 2 ) = – 0 . 2 , p = . 8 4 2

t ( 2 3 1 ) = – 0 . 5 , p = . 6 4 9

p o n s e s

2 . 3

2 . 3

2 . 2

2 . 3

3 . 2

2 . 6

2 . 2

2 . 1

t ( 2 3 6 ) = – 0 . 4 , p = . 7 2 6

t ( 2 3 6 ) = 1 . 1 , p = . 2 6 5

t ( 2 3 5 ) = – 1 . 7 , p = . 1 0 1

r o r s

4 . 3

3 . 9

4 . 1

3 . 5

6 . 0

4 . 9

4 . 7

4 . 4

t ( 2 3 2 ) = – 0 . 5 , p = . 6 1 3

t ( 2 3 2 ) = 1 . 4 , p = . 1 6 2

t ( 2 3 1 ) = – 1 . 2 , p = . 2 2 9

r e i t h

r g a n i z a t i o n

9 . 0

3 . 3

1 0 . 5

3 . 3

8 . 5

3 . 8

8 . 3

3 . 8

—

— e

t ( 2 2 0 ) = – 2 . 2 , p = . 0 2 7 *

t a l a c c u r a c y

6 4 . 2

2 . 5

6 4 . 2

2 . 8

6 3 . 8

1 . 8

6 2 . 9

7 . 2

t ( 2 2 1 ) = – 0 . 5 , p = . 6 0 5

t ( 2 2 1 ) = – 1 . 0 , p = . 3 3 5

t ( 2 2 0 ) = – 0 . 7 , p = . 4 7 2

r g a n i z a

t i o n

7 . 6

4 . 2

8 . 9

4 . 2

6 . 0

3 . 8

8 . 2

4 . 1

t ( 2 1 4 ) = 2 . 8 , p = . 0 0 7

t ( 2 1 4 ) = – 1 . 5 , p = . 1 2 9

t ( 2 1 3 ) = 0 . 7 , p = . 4 8 9

o t a l a c c

u r a c y

4 6 . 2

9 . 6

5 2 . 0

8 . 2

4 5 . 2

1 0 . 6

5 1 . 2

9 . 0

t ( 2 1 4 ) = 4 . 0 , p = . 0 0 0 *

t ( 2 1 4 ) = – 0 . 8 , p = . 4 4 7

t ( 2 1 3 ) = 0 . 0 , p = . 9 7 4

P v a l u

e s a r e b a s e d o n t h e p r i m a r y r e g r e s s i o n a n a l y s e s c o n t r o l l i n g s i m u l t a n

e o u s l y f o r a g e , s o c i o e c o n o m i c s t a

t u s , p s y c h i a t r i c c o m o r b i d i t y , a n d l e a r n i n g d i s a b l i l i t y ;

k i n d i c a t e s a s i g n i f i c a n t e f f e c t c o n t r o l l i n g f o r t h e s e v a r i a b l e s a n d I Q s . G e n d e r a n d s t a t u s c o l u m n s a r e d e r i v e d f r o m m o d e l s r u n i n d e p e n d e n t l y o f t h e i n t e r a c t i o n

D H D = a t t e n t i o n d e f i c i t h y p e r a c t i v i t y d i s o

r d e r ; W R A M L = W i d e R a n g e A c h i e v e m e n t T e s t o f M e m o r y a n d L e a r n i n g A d a m s & S h e s l o w , 1 9 9 0 ) ;

C P T = C o n t i n u o u s

n c e T e s t .

8 – 1 0 9 . S a m p l e s i z e s v a r y f o r d i f f e r e n t t e s t s d u e t o m i s s i n g d a t a . b n = 6 1 – 7 0 . c n = 3 5 . d n = 3 4 . e A D H D e f f e c t f o

r b o y s , t ( 9 5 ) = – 3 . 4 , p = . 0 0 1 ; A D H D e f f e c t f o r g i r l s ,

1 . 2 , p =

. 2 4 8 .

0 5 .



T A B L E 4

D e m o g r a p h i c C h a r a c t e r i s t i c s S

t r a t i f i e d b y A g e a n d G e n d e r

g r a p h i c

F e a t u r e b y A g e G r o u p

A D H D

C o n t r o l s

G i r l s b

B o y s

G i r l s

B o y s

M

M

M

M

– 1 2 a

e

1 0 . 4 ± 1 . 2

1 1 . 3 ± 0 . 9

1 0 . 6 ± 1 . 2

1 0

. 7 ± 0 . 8

a d e

4 . 9 ± 1 . 3

5 . 6 ± 1 . 0

5 . 2 ± 1 . 3

5

. 2 ± 0 . 8

S

1 . 9 ± 0 . 9

1 . 8 ± 0 . 9

1 . 7 ± 0 . 8

1

. 6 ± 0 . 8

c h i a t r i c c o m o r b i d i t y

4 4 % ( n = 2 4 )

6 1 % ( n = 2 5 )

5 % ( n = 3 )

1 0 % ( n = 3 )

a r n i n g d

i s a b i l i t y

1 3 % ( n = 7 )

4 7 % ( n = 1 7 )

0 % ( n = 0 )

1 6 % ( n = 4 )

d i c a t i o n s t a t u s

7 0 % ( n = 3 8

6 6 % ( n = 2 7 )

0 % ( n = 0 )

0 %

( n = 0 )

H D s y m p t o m s c

1 1 . 3 ± 1 . 8

9 . 5 ± 3 . 9

0 . 8 ± 1 . 7

1

. 4 ± 2 . 3

e s t i m a t e

1 0 4 . 6 ± 1 0 . 8

1 0 6 . 7 ± 1 4 . 5

1 0 9 . 4 ± 1 1 . 6

1 1 7

. 7 ± 1 1 . 5

R A T A r i t h m e t i c

9 6 . 8 ± 1 3 . 8

9 2 . 3 ± 1 9 . 7

1 0 6 . 6 ± 1 7 . 1

1 1 3

. 2 ± 1 8 . 4

R A T R e a d i n g

1 0 0 . 3 ± 1 5 . 8

1 0 3 . 0 ± 1 8 . 3

1 0 9 . 9 ± 1 0 . 2

1 1 1

. 1 ± 1 0 . 0

3 – 1 7 d

e

1 4 . 9 ± 1 . 4

1 4 . 9 ± 1 . 5

1 5 . 0 ± 1 . 4

1 5

. 2 ± 1 . 3

a d e

9 . 3 ± 1 . 4

9 . 2 ± 1 . 5

9 . 6 ± 1 . 6

1 0

. 0 ± 1 . 4

S

1 . 7 ± 0 . 9

2 . 0 ± 1 . 0

1 . 7 ± 0 . 8

1

. 4 ± 0 . 7

c h i a t r i c c o m o r b i d i t y

5 7 % ( n = 2 7 )

6 5 % ( n = 4 0 )

8 % ( n = 4 )

1 7 % ( n = 7 )

a r n i n g d

i s a b i l i t y

2 3 % ( n = 1 1 )

4 5 % ( n = 2 8 )

1 0 % ( n = 5 )

1 2 % ( n = 5 )

d i c a t i o n s t a t u s

6 0 % ( n = 2 8 )

6 1 % ( n = 3 8 )

0 % ( n = 0 )

0 %

( n = 0 )

H D s y m p t o m s c

1 2 . 1 ± 1 . 9

9 . 1 ± 3 . 4

2 . 0 ± 2 . 5

2

. 2 ± 2 . 9

e s t i m a t e

1 0 7 . 1 ± 1 2 . 2

1 0 5 . 2 ± 1 2 . 9

1 1 0 . 3 ± 1 0 . 4

1 1 4

. 3 ± 1 0 . 0

R A T A r i t h m e t i c

9 4 . 9 ± 1 3 . 9

9 3 . 4 ± 1 7 . 3

1 0 6 . 5 ± 1 4 . 1

1 0 7

. 5 ± 1 2 . 4

R A T R e a d i n g

1 0 1 . 1 ± 1 5 . 4

1 0 0 . 1 ± 1 4 . 9

1 1 0 . 0 ± 1 0 . 6

1 1 1

. 8 ± 1 0 . 4

o t e . A

D H D = a t t e n t i o n d e f i c i t h y p e r a c t i v i t y d i s o r d e r ; S E S = s o c i o e c o n o m

i c s t a t u s ; W R A T = W i d e R a n g e A

c h i e v e m e n t T e s t .

o r A D H

D g i r l s , n = 5 4 ; b o y s , n = 3 6 – 4 1 . F

o r C o n t r o l s g i r l s , n = 5 6 – 5 7 ; b o y s n = 2 5 – 2 9 . b S a m p l e s i z e s v a r y f o r d i f f e r e n t t e s t s d u e t o m i s s i n g d a t a . c R e f e r s t o

n t A D H

D s y m p t o m s e x p e r i e n c e d w i t h i n t h e p a s t m o n t h . d F o r A D H D g i r l s ,

n = 4 7 ; b o y s , n = 5 5 – 6 2 . F o r C o n t r o l s g i r l s , n = 5 2 ; b o y s n = 4 1 .



T A B L E 5

N e

u r o p s y c h o l o g i c a l P e r f o r m a n c e

S t r a t i f i e d b y A g e a n d G e n d e r

A D

H D

C o n t r o l

p s y c h o l o g i c a l T a s k s b y A g e G r o u p

G i r l s b

B o y s

G i r l s

B o y s

– 1 2 a

o o p T e s

t


7 1 . 5 ± 1 3 . 1

7 3 . 9 ± 1 5 . 1

8 4 . 7 ± 1 2 . 3

7 8

. 5 ± 1 2 . 8

C o l o r r a

w s c o r e

4 6 . 9 ± 1 1 . 4

4 7 . 8 ± 1 1 . 1

5 4 . 1 ± 1 0 . 7

5 1

. 2 ± 9 . 4

C o l o r – w

o r d r a w s c o r e

2 2 . 9 ± 7 . 8

2 4 . 3 ± 8 . 1

3 0 . 2 ± 7 . 9

2 8

. 4 ± 9 . 3

n t e r f e r e n c e t s c o r e

4 6 . 9 ± 6 . 9

4 6 . 6 ± 6 . 3

4 9 . 3 ± 6 . 2

4 8

. 7 ± 5 . 9

s c o n s i n

C a r d S o r t T e s t

C a t e g o r i e s

4 . 6 ± 1 . 9

4 . 9 ± 1 . 5

5 . 2 ± 1 . 4

5

. 3 ± 1 . 3

F a i l u r e t o m a i n t a i n s e t

1 . 2 ± 1 . 4

1 . 2 ± 1 . 2

1 . 4 ± 1 . 3

1

. 4 ± 1 . 6

P e r s e v e r a t i v e e r r o r s

2 0 . 0 ± 1 3 . 3

1 7 . 3 ± 1 1 . 7

1 7 . 1 ± 1 0 . 0

1 2

. 5 ± 8 . 9

N o n p e r s e v e r a t i v e e r r o r s

1 8 . 9 ± 1 4 . 8

1 7 . 6 ± 1 0 . 7

1 7 . 3 ± 8 . 4

1 4

. 9 ± 8 . 8

W R A M

L t o t a l w o r d s l e a r n e d o n 5 t r i a l s

4 5 . 1 ± 1 1 . 3

4 4 . 9 ± 1 0 . 7

4 8 . 5 ± 8 . 2

4 8

. 6 ± 1 0 . 9

d i t o r y C

P T

O m i s s i o

n s

3 . 3 ± 3 . 5

3 . 6 ± 3 . 3

2 . 7 ± 2 . 9

2

. 8 ± 2 . 8

C o m m i s s i o n s

0 . 3 ± 0 . 6

0 . 3 ± 0 . 7

0 . 1 ± 0 . 3

0

. 2 ± 0 . 4

L a t e r e s p o n s e s

3 . 8 ± 3 . 4

2 . 8 ± 1 . 9

3 . 1 ± 2 . 5

3

. 5 ± 2 . 4

T o t a l e r r o r s

7 . 4 ± 5 . 1

6 . 7 ± 4 . 3

6 . 0 ± 4 . 4

6

. 5 ± 3 . 5

y O s t e r r e i t h

C o p y o r

g a n i z a t i o n

6 . 8 ± 3 . 5

6 . 3 ± 3 . 4

7 . 8 ± 3 . 1

8

. 8 ± 3 . 6

C o p y t o t a l a c c u r a c y

6 2 . 3 ± 5 . 0

6 2 . 3 ± 6 . 2

6 4 . 0 ± 3 . 0

6 3

. 3 ± 4 . 2

D e l a y o r g a n i z a t i o n

5 . 3 ± 3 . 4

5 . 4 ± 3 . 6

6 . 6 ± 4 . 0

7

. 1 ± 4 . 5

D e l a y t o


4 3 . 4 ± 1 1 . 8

4 6 . 9 ± 1 1 . 5

4 5 . 2 ± 9 . 1

5 1

. 6 ± 9 . 5



3 – 1 7 c

o o p T e s

t


8 9 . 1 ± 1 3 . 8

8 7 . 0 ± 1 5 . 1

9 2 . 9 ± 1 4 . 0

9 5

. 3 ± 1 6 . 0

C o l o r r a

w s c o r e

6 4 . 1 ± 1 2 . 8

6 0 . 9 ± 1 1 . 1

6 9 . 2 ± 1 1 . 4

6 5

. 4 ± 1 1 . 8

C o l o r – w

o r d r a w s c o r e

3 7 . 0 ± 1 0 . 5

3 5 . 0 ± 1 0 . 2

4 1 . 3 ± 8 . 1

4 1

. 0 ± 8 . 3

n t e r f e r e n c e t s c o r e

4 9 . 8 ± 7 . 3

4 9 . 7 ± 8 . 3

5 2 . 7 ± 6 . 1

5 2

. 6 ± 6 . 6

s c o n s i n

C a r d S o r t T e s t

C a t e g o r i e s

5 . 4 ± 1 . 4

4 . 7 ± 2 . 0

5 . 4 ± 1 . 5

5

. 7 ± 0 . 7

F a i l u r e t o m a i n t a i n s e t

1 . 1 ± 1 . 5

1 . 1 ± 1 . 1

0 . 7 ± 1 . 0

0

. 9 ± 1 . 0

P e r s e v e r a t i v e e r r o r s

1 3 . 5 ± 1 1 . 2

1 6 . 3 ± 1 1 . 8

1 3 . 1 ± 1 0 . 1

1 0

. 6 ± 7 . 2

N o n p e r s e v e r a t i v e e r r o r s

1 4 . 0 ± 1 0 . 3

1 8 . 9 ± 1 5 . 7

1 3 . 5 ± 1 0 . 1

9

. 6 ± 6 . 6

W R A M

L t o t a l w o r d s l e a r n e d o n 5 t r i a l s

5 0 . 8 ± 9 . 8

4 7 . 4 ± 1 1 . 6

5 2 . 9 ± 7 . 5

5 2

. 3 ± 9 . 3

d i t o r y C

P T

O m i s s i o

n s

1 . 7 ± 2 . 5

2 . 0 ± 2 . 5

1 . 0 ± 1 . 2

1

. 0 ± 1 . 4

C o m m i s s i o n s

0 . 0 ± 0 . 2

0 . 4 ± 1 . 4

0 . 0 ± 0 . 1

0

. 1 ± 0 . 3

L a t e r e s p o n s e s

2 . 0 ± 2 . 4

1 . 7 ± 1 . 8

1 . 4 ± 1 . 5

1

. 3 ± 1 . 6

T o t a l e r r o r s

3 . 7 ± 4 . 0

4 . 0 ± 4 . 2

2 . 4 ± 1 . 9

2

. 4 ± 2 . 4

y O s t e r r e i t h

C o p y o r

g a n i z a t i o n

1 0 . 6 ± 3 . 0

1 0 . 0 ± 3 . 6

1 0 . 3 ± 3 . 0

1 1

. 8 ± 2 . 3

C o p y t o t a l a c c u r a c y

6 4 . 5 ± 1 . 2

6 3 . 3 ± 6 . 0

6 4 . 5 ± 1 . 7

6 4

. 8 ± 0 . 4

D e l a y o r g a n i z a t i o n

9 . 0 ± 3 . 5

8 . 5 ± 4 . 6

8 . 7 ± 4 . 2

1 0

. 3 ± 3 . 3

D e l a y t o


5 2 . 1 ± 7 . 6

5 1 . 6 ± 1 1 . 4

4 7 . 2 ± 1 0 . 2

5 2

. 4 ± 7 . 2

o t e . A

D H D = a t t e n t i o n d e f i c i t h y p e r a c t i v i t y d i s o r d e r ; W R A M L = W i d e R

a n g e A c h i e v e m e n t T e s t o f M e m o

r y a n d L e a r n i n g ; C P T = C o n t i n u o u s P e r f o r -

e T e s t .

o r A D H

D g i r l s , n = 4 2 – 5 4 ; f o r b o y s , n = 3 6 – 3 9 . F o r C o n t r o l s g i r l s , n = 4 4 – 5 7

; f o r b o y s , n = 2 8 – 2 9 . b S a m p l e s i z e

s v a r y f o r d i f f e r e n t t e s t s d u e t o m i s

s i n g d a t a .

A D H D g i r l s , n = 3 4 – 4 6 ; f o r b o y s , n = 4 7 –

5 9 . F o r C o n t r o l s g i r l s , n = 4 2 – 5 2 ; f o r b o y s , n = 3 2 – 4 1 .



.03). In the sample restricted to girls with and without ADHD, only 2 of 17 vari-

ables measured had a significant interaction (Stroop Word Raw Score: t (207) =

2.4, p = .02; ROCF Delayed Recall Total Accuracy: t (195) = 2.1, p =.04).We looked further at these three variables to determine the effect of ADHD on

the different age groups in the full sample and in the sample of girls only. There

were no significant effects of ADHD in the younger or older group in the full sam-

ple on the WCST Failure to Maintain Set and ROCF Delayed Recall Total Accu-

racy. There was a significant effect of ADHD in the younger group of the girls sam-

ple on the Stroop Word Raw Score, t (109)= –4.0, p = .001). No significant effects

were noted in the older sample on either variable or in the younger group of the

girls sample using the ROCF Delay Total Accuracy.

DISCUSSION

Boys and girls with ADHD were significantly more impaired on some EFs than

were normal comparison participants, reflected in worse performance on the

Stroop and WCST. Effects were very similar when analyzing data in the smaller

sample of unmedicated boys and girls with ADHD, with additional impairments

observed on the ROCF organization score for the ADHD participants. The neuro-

psychological deficits are not accounted for by psychiatric comorbidity or LD.This overall pattern is not surprising because in previous separate analyses of sam-

ples of boys and girls with ADHD compared to sex-matched controls, we demon-

strated that children and teenagers with ADHD are impaired in these domains

(Seidman, Biederman, Faraone, Weber, & Ouellette, 1997; Seidman et al., 2004).

This is also consistent with a large and growing literature demonstrating EF defi-

cits in girls and boys with ADHD. Of importance, Sex × Diagnosis interactions

were found in only 10% to 15% of the variables tested, suggesting that males and

females with ADHD have largely comparable neuropsychological deficits. More-

over, consistent with an earlier report on boys with ADHD and comparisons(Seidman, Biederman, Faraone, Weber, & Ouellette, 1997), there were very few

interactions of age with diagnosis in the total sample or in the girls’ sample alone,

suggesting that neuropsychological deficits are comparable at ages 9 to 12 and 13

to 17. This is important because very few studies of ADHD have neuropsycho-

logically evaluated the teenage years. These results suggest that neuropsycho-

logical deficits in ADHD are quite similar across both age and sex, at least through

17 years of age.

Other investigators have shown that girls have attention and EF deficits (Arcia

& Conners, 1998; Breen, 1989; Castellanos et al., 2000; DeHaas, 1986; Horn et al.,1989; Houghton et al., 1999; Nigg, 1999; Rucklidge & Tannock, 2001; Schuerholz

98 SEIDMAN ET AL.



sample sizes, absence of both male and female controls to address normal sex dif-

ferences (Arnold, 1996), relatively limited sets of EF measures, and failure to con-

trol for psychiatric comorbidities and LDs. In this study we addressed these meth-odological concerns using a large sample of more than 200 children with ADHD

and a like number of controls, by having controls of both genders selected in com-

parable study designs, and by using a wide range of well-accepted measures of EF.

Our analyses controlled for psychiatric comorbidity and LD simultaneously. The

neuropsychological impairments on some measures were present even after these

important factors were controlled. These stringent statistical adjustments enable us

to conclude more definitively that neuropsychological deficits are a robust compo-

nent of ADHD in males and females.

The presence of very similar levels of executive deficits in girls and boys withADHD adds to an emerging body of literature that many of the clinical and

neurobiological correlates are similar in the two genders (Biederman et al., 2002).

Moreover, the existing data, albeit limited, tends to support relatively similar struc-

tural brain abnormalities. For example, Castellanos et al. (2001, 2002) demon-

strated that girls with ADHD, like boys, had smaller total brain volumes, and repli-

cated previous findings for boys in the posterior–inferior lobules of the cerebellar

vermis, compared to controls. Moreover, Castellanos et al. (2002) demonstrated

stable structural brain abnormalities across ages 4 to 18 for most of the brain re-

gions tested (with the exception of the caudate). Those data, which were derivedfrom a combination of cross-sectional and longitudinal evaluations, are consistent

with our neuropsychological data, pointing to relatively stable brain differences

and neuropsychological dysfunctions at least until the late teenage years.

The question as to whether attention, EF, and memory deficits observed in

ADHD (or in other neurocognitive disorders) are a function of IQ is a general issue

for neuropsychological studies. In previous research, we (Faraone et al., 1993),

and others (Werry, Reeves, & Elkind, 1987), have shown that IQ is associated with

ADHD. Caution must be exercised in matching for IQ (Meehl, 1970), because

controlling for IQ may remove a portion of the variance directly attributable to theindependent variable of interest (e.g., ADHD). Moreover, results should be viewed

very cautiously, when, as in this case (of IQ), the covariate shares variance with

both independent and dependent variables (Miller & Chapman, 2001). Nonethe-

less, we chose to use IQ as a covariate to provide as complete a picture as possible

of the cognitive and neuropsychological deficits in ADHD children. When we

used IQ as a covariate to determine if executive deficits are present over and above

IQ differences, although there was some attenuation of results, most impairments

on the Stroop remained significant. These results support the conclusion that some

of the executive impairments in ADHD children go beyond intellectual deficits as-sessed by IQ.




fect by comparing boys and girls with ADHD, in which girls had higher symptom

levels. However, only 2 of 17 variables differed significantly between boys and

girls with ADHD. Small differences in the overall number of symptoms do not ap-pear to have a significant effect on the neuropsychological functioning in ADHD

children.

Although the overall picture did not support a Gender × Group interaction (only

1 of 17 tests was significant), the significant finding on the ROCF organization

score is intriguing. It is possible that the effect (which was confined to males with

ADHD vs. male controls) was a chance finding. Alternatively, this variable may be

more sensitive than the other tests for the age groups studied. This latter hypothesis

requires independent confirmation by evaluating the developmental sensitivity for

each of the EF measures. Given the age range studied, from 9 to 17, the effects of puberty may impact on these measures and would be important to study.

Our results must be viewed in the light of some methodological limitations.

First, the boys’and girls’ samples differed in that the boys had only White partici-

pants and the girls had a small number of non-White participants. However, the

pattern of results was virtually identical to that observed in the complete sample

when the non-White participants were excluded from the analysis. Second, as the

results are cross-sectional, we cannot test the longitudinal impact of age or gender

on ADHD or the relative effect of treatment on executive functioning. Also, the

groups were ascertained 5 years apart from each other, so cohort effects could po-tentially be misconstrued as gender effects. Nevertheless, participants were

equated on a host of variables, were drawn from the same age epoch, from the

same geographic area, and acquired using virtually identical methods from the

same group of investigators. These design features minimize the possibility that

cohort effects are operating. In addition, improved performance in the older group,

regardless of ADHD status, was documented for both the boys and girls samples.

This pattern of improvement is also consistent with the limited number of studies

that have addressed developmental issues with regard to EFs (Bedardet al., 2002).

Because the boys’ sample was originally ascertained during the era of DSM–III–R, wecompared the girls toboys using DSM–III–Rcriteria. These results

will need to be tested with participants ascertained with DSM–IV criteria to deter-

mine if the results generalize. However, there is evidence that the overlap between

cases defined by DSM–III–R and DSM–IV criteria is extensive (Biederman et al.,

1997), which suggests that our results may generalize to DSM–IV ADHD samples

with limited differences. Further studies of the DSM–IV subtypes may also be re-

vealing in relation to gender and neurocognitive function (Nigg, Blaskey,

Huang-Pollock, & Rappley, 2002). Finally, we did not explore test order effects.

However, some tests in the beginning, middle, and end of the battery discriminatedgroups, and there did not seem to be any obvious effects. Moreover, because our re-

100 SEIDMAN ET AL.



In summary, we found that girls with ADHD have a very similar profile of exec-

utive dysfunctions compared to boys with the disorder, and this was true in youn-

ger and older age groups. The results of this study are consistent with the idea thatthe neurobiology of ADHD is largely independent of gender and age, at least

through the late teen years. The effects of sex on neurocognition in ADHD should

be further studied in adults to determine if the pattern observed through age 17

continues throughout the life span.

ACKNOWLEDGMENTS

This work was supported, in part, by United States Public Health Service (National

Institute of Mental Health) Grants R01MH–41314 and R01MH–50657 (to Joseph

Biederman).

We thank Katherine Crum for her assistance with this study.

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Seidman, LJ- Impact of Gender and Age on Executive Functioning (2005)

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