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Arch Clin Neuropsychol. Nov 2010; 25(7): 656–670.
Published online Jul 16, 2010. doi:  10.1093/arclin/acq050
PMCID: PMC2957961
Neuropsychological Profile of Executive Function in Girls with Attention-Deficit/Hyperactivity Disorder
Jessica W. O'Brien, Lauren R. Dowell, Stewart H. Mostofsky, Martha B. Denckla, and E. Mark Mahone*
Department of Neuropsychology, Kennedy Krieger Institute and Johns Hopkins University School of Medicine, Baltimore, MD, USA
*Corresponding author at: Department of Neuropsychology, Kennedy Krieger Institute and Johns Hopkins University School of Medicine, 1750 East Fairmount Avenue, Baltimore, MD 21231, USA. Tel.: Phone: +1-443-923-4446; fax: +1-443-923-4425. E-mail address:mahone/at/kennedykrieger.org (E.M. Mahone).
Accepted June 15, 2010.
The majority of research on neurobehavioral functioning among children with Attention-Deficit/Hyperactivity Disorder (ADHD) is based on samples comprised primarily (or exclusively) of boys. Although functional impairment is well established, available research has yet to specify a neuropsychological profile distinct to girls with ADHD. The purpose of this study was to examine performance within four components of executive function (EF) in contemporaneously recruited samples of girls and boys with ADHD. Fifty-six children with ADHD (26 girls) and 90 controls (42 girls), ages 8–13, were administered neuropsychological tests emphasizing response inhibition, response preparation, working memory, and planning/shifting. There were no significant differences in age or SES between boys or girls with ADHD or their sex-matched controls; ADHD subtype distribution did not differ by sex. Compared with controls, children with ADHD showed significant deficits on all four EF components. Girls and boys with ADHD showed similar patterns of deficit on tasks involving response preparation and working memory; however, they manifested different patterns of executive dysfunction on tasks related to response inhibition and planning. Girls with ADHD showed elevated motor overflow, while boys with ADHD showed greater impairment during conscious, effortful response inhibition. Girls, but not boys with ADHD, showed impairment in planning. There were no differences between ADHD subtypes on any EF component. These findings highlight the importance of studying boys and girls separately (as well as together) when considering manifestations of executive dysfunction in ADHD.
Keywords: Attention, Response control, Working memory, Inhibition, Planning, Childhood, Development
Components of Executive Function
Executive function (EF) refers to a set of cognitive processes utilized in the management of goal-directed behaviors and in the development and implementation of an approach to completing tasks that have not been habitually performed (Mahone et al., 2002). It is a multidimensional construct, separable from (but dependent on) core “ingredient” skills such as vocabulary, visuospatial skills, and intelligence. EF includes the ability to inhibit inappropriate responses, resist distraction and interference, sustain behavior for prolonged periods, simultaneously attend to multiple sources of information, grasp the gist of a complex situation, and plan and sequence complex behaviors (Denckla, 1996). EF is central to performance and remediation of skill deficits, and includes “intentional” skills, such as the ability to initiate, sustain, inhibit, and shift attention (Heilman, Watson, & Valenstein, 1993). Mediated at least in part by frontostriatal circuitry, EF has a protracted period of development in childhood (Diamond, 2000). As a result, executive dysfunction has been observed in a variety of childhood disorders, especially those involving anomalous frontostriatal development, including Attention-Deficit/Hyperactivity Disorder (ADHD), Autism Spectrum Disorders, Obsessive Compulsive Disorder, and Tourette syndrome (Mahone & Slomine, 2007).
Executive Control in ADHD
In the past 20 years, research on neurobehavioral functioning in ADHD has shifted away from examining attention problems to the broader category of EF deficiencies (Barkley, 1997). A meta-analysis of 83 studies examining ADHD and EF found that children with ADHD performed worse than typically developing controls on 13 measures of EF assessing the aforementioned components. Effect sizes for relative impairment on all EF measures fell in the range typically considered a medium effect, but the strongest and most consistent effects were obtained on measures of response inhibition, vigilance, spatial working memory, and planning (Willcutt, Doyle, Nigg, Faraone, & Pennington, 2005). Neuroimaging studies lend further support for the model of frontostriatal dysfunction in ADHD; abnormalities in frontostriatal circuitry, thought to mediate task-relevant response selection, are commonly reported in studies of children with ADHD (Bush, 2008; Dickstein, Bannon, Castellanos, & Milham, 2006; Mostofsky, Cooper, Kates, Denckla, & Kaufmann, 2002; Qiu et al., 2009; Ranta et al., 2009; Suskauer et al., 2008). It is now recognized, however, that children with ADHD display a wide range of neuropsychological deficits (which may or may not be subsumed under the EF construct), including problems with motivation (Carlson & Tamm, 2000), delay aversion (Sonuga-Barke, 2005), motor speed and coordination (Cole, Mostofsky, Larson, Denckla, & Mahone, 2008; Mostofsky, Newschaffer, & Denckla, 2003; Watemberg, Waiserberg, Zuk, & Lerman-Sagie, 2007), processing speed (Clarke et al., 2003; Willcutt, Sonuga-Barke, Nigg, & Sergeant, 2008), and variability of responding (Castellanos et al., 2005; Suskauer et al., 2008; Vaurio, Simmonds, & Mostofsky, 2009).
Sexual Dimorphism in Development
Like many disorders affecting central nervous system development, the incidence and nature of ADHD differs in boys and girls (Rucklidge, 2010). This finding is not surprising in light of differences in behavioral, cognitive, and biological development in typically developing boys and girls (Kimura, 2002). Several general categories of behavior show consistent sex differences in typically developing children, including patterns of cognitive strengths, motor skills, and neural development (Gidley Larson et al., 2007; Giedd et al., 1999; Mann, Sasanuma, Sakuma, & Masaki, 1990). Biologically based differences in frontal and temporal lobe function appear in infancy; animal studies in controlled conditions point to biological rather than social bases of differences (De Bellis et al., 2001). There is growing evidence that boys' and girls' brains develop and mature at different rates (Giedd et al., 1999; Lenroot et al., 2007; Thompson et al., 2005). Sex differences exist in every lobe of the brain and are accompanied by global differences, such as the ratio of gray to white matter (Lenroot et al., 2007). Age-related changes in gray matter are nonlinear, region specific, and differ between boys and girls; girls' frontal lobes, parietal lobes, temporal lobes, and total cerebral gray matter volume mature 1–3 years earlier than their male peers (Giedd et al., 2009).
Sex Differences in ADHD
By school age, boys are diagnosed with ADHD three to four times as often as girls (Pastor & Reuben, 2008). Diagnosis of ADHD in girls is more complicated than in boys, due to later age of onset, more subtle clinical manifestation, and limitations associated with the DSM diagnostic nomenclature (Keltner & Taylor, 2002). Further, girls present more commonly with the inattentive subtype than do boys (Hinshaw, Owens, Sami, & Fargeon, 2006; Weiler, Bellinger, Marmor, Rancier, & Waber, 1999). Symptoms of ADHD tend to decrease in severity with age in parallel with cerebral maturation, such that by late elementary school, the disruptive behavioral symptoms are more pronounced in boys (compared with girls) with ADHD (Gaub & Carlson, 1997). The more rapid decline in symptoms of hyperactivity/impulsivity (compared with inattentive symptoms) in girls with ADHD appears to parallel the performance on neuropsychological measures of EF (Hinshaw et al., 2006). The gender paradox, however, posits that the sex in which a given disorder is less prevalent should show greater levels of impairment than the sex in which the disorder is more prevalent (Eme, 1992). Indeed, ADHD is associated with considerable functional and psychosocial impairment in girls, including academic deficits and interpersonal problems (Biederman et al., 1999), and an increased risk of internalizing disorders (eating disorders, depression, suicide, anxiety disorders, addictions) in adolescence and young adulthood (Biederman et al., 2006; Gaub & Carlson, 1997; Gershon, 2002; Makris et al., 2008; Mikami, Hinshaw, Patterson, & Lee, 2008; Owens, Hinshaw, Lee, & Lahey, 2009). Unfortunately, the functional difficulties among girls with ADHD may go unrecognized and untreated (Gershon, 2002; Staller & Faraone, 2006). For example, teachers are more likely to refer boys than girls for treatment for ADHD, even when all other information is equal (Sciutto, Nolfi, & Bluhm, 2004). Girls are also more likely than boys to be rated with higher than average parent and teacher ratings of ADHD symptoms (compared with sex-based norms) while still not meeting DSM-IV symptom count criteria (Waschbusch & King, 2006).
Previous research examining profiles of executive dysfunction among girls with ADHD has yielded conflicting results (Gaub & Carlson, 1997). The inconsistencies may be because most prior research has examined girls with ADHD only in comparison to sex-matched peers or have included children who were either medicated for ADHD at the time of assessment and/or had multiple comorbid psychiatric disorders (making interpretation of ADHD-specific deficits more difficult). One of the first studies examining profiles of EF in girls with ADHD failed to identify differences between girls with and without ADHD (Seidman et al., 1997); however, 84% of the girls in the ADHD group in this study were on stimulant medication at the time of testing. Stimulant medications have been shown to enhance performance on a variety of neuropsychological measures (Aman, Roberts, & Pennington, 1998) and improve working memory (Mehta et al., 2000), perhaps masking deficits in the group with ADHD. More recent studies have found that compared with typically developing age- and sex-matched controls, girls with ADHD are deficient on several neuropsychological measures, including planning, vigilance, inhibitory control, working memory, set-shifting, visual-spatial skills, processing speed, sustained attention, and motor skills (Biederman, Krishnan, Zhang, McGough, & Findling, 2007; Hinshaw, Carte, Sami, Treuting, & Zupan, 2002; Hinshaw, Carte, Fan, Jassy, & Owens, 2007; Seidman et al., 2005).
Research comparing girls with ADHD to both sex-matched controls and boys with ADHD have found more similarities than differences between the two groups, with girls and boys with ADHD manifesting similar impairments on auditory working memory, inhibition, flexibility (card sorting), and sustained attention (continuous performance) tasks (DeHaas, 1986; Houghton et al., 1999; Sharp et al., 1999). Others, however, identify more subtle EF difficulties in girls. Rucklidge and Tannock (2002) found that boys with ADHD showed slower processing speed than girls with ADHD, while Newcorn and colleagues (2001) found that girls with ADHD made fewer impulsivity errors than boys with ADHD on a continuous performance task. Of note, many previous studies did not control for ADHD subtype (deHaas, 1986), stimulant medication use (Sharp et al., 1999), comorbid diagnoses (Newcorn et al., 2001; Rucklidge & Tannock, 2002) or compare the ADHD groups to adequate samples of sex-matched peers (Houghton et al., 1999).
Summary
Girls and boys have different trajectories of brain development (Lenroot et al., 2007); thus, research combining samples of boys and girls with ADHD can be suspect because girls are at a different stage in their development of cognitive and neurological maturity than boys of the same age. Given that girls' brains mature as much as 1–3 years earlier in regions identified as anomalous in boys with ADHD (Thompson et al., 2005), it may be necessary to examine behavioral development in boys and girls separately in order to appreciate the deficits that may be unique to girls with ADHD. Further, when comparing boys and girls with ADHD, sex differences in ADHD subtype and comorbidities should be controlled.
The purpose of the present study was to examine profiles of EF in contemporaneously recruited samples of boys and girls with ADHD, emphasizing multiple components of EF as well as multiple methods and modalities of assessment. The components of EF include those considered more “basic” or earlier-developing skills (e.g., response inhibition, response preparation, working memory) as well as “higher-order” or later-developing (e.g., planning/shifting) skills (Best, Miller, & Jones, 2009), and are considered from a developmental perspective, with response inhibition developing first and planning and shifting developing last (Barkley, 2007; Diamond, 1991). Specifically, we hypothesized that (compared with male controls) boys with ADHD would manifest significant deficits across all components of EF, whereas (relative to female controls) girls with ADHD would have more subtle patterns of deficit, predominantly among tasks emphasizing more higher order cognitive (as opposed to basic response control-related) components of EF.
Participants
Following approval from the Johns Hopkins Medicine Institutional Review Board, participants were recruited from outpatient clinics at the Kennedy Krieger Institute and from local area pediatricians, local chapters of Children and Adults with ADHD (CHADD), schools, social/service organizations, and advertisements in the community. This study is part of a project examining brain-behavior relationships in children; therefore, participants were screened for most comorbidities commonly seen in ADHD (detailed below). All participants in the study met the following criteria: (a) between 8 years, 0 months and 13 years, 0 months; (b) Full Scale IQ (FSIQ) of 80 or higher on the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV; Wechsler, 2003); (c) no history of language disorder or a Reading Disability (RD) either screened out before a visit or based on school assessment completed within 1 year of participation. RD was based on a statistically significant discrepancy between a child's FSIQ score and his/her Word Reading subtest score from the Wechsler Individual Achievement Test-II (Wechsler, 2002), or a standard score below 85 on the Word Reading subtest, regardless of IQ score; and (d) no evidence of visual or hearing impairment, or history of other neurological or psychiatric disorder.
A total of 56 children were included in the ADHD group. Diagnosis of ADHD was determined by a structured parent interview based on DSM-IV criteria (Diagnostic Interview for Children and Adolescents, Fourth Edition [DICA-IV; Reich, Welner, & Herjanic, 1997]), the Conners' Parent Rating Scale-Revised, Long Form (CPRS-R; Conners, 1997), and the ADHD Rating Scale-IV (DuPaul, Power, Anastopoulos, & Reid, 1998). Children assigned to the ADHD group met criteria for ADHD on the DICA-IV and either had a T-score of 65 or greater on the Conners' Parent Rating Scale L (DSM-IV Inattentive) and/or M (DSM-IV Hyperactive/Impulsive) or met criteria on the DuPaul ADHD Rating Scale IV (six out of nine items scored 2 or 3 from Inattention items and/or six out of nine scored 2 or 3 from the Hyperactivity/Impulsivity items). Children with DSM-IV diagnoses other than Oppositional Defiant Disorder (ODD; n = 23) or Specific Phobias (n = 15) were excluded. Subjects participated in a larger study with a neuroimaging component; therefore, children with comorbidities that may have presented imaging confounds (e.g., Conduct Disorder, Learning Disabilities) were excluded. DSM-IV criteria and the aforementioned rating scales were also used to evaluate the three ADHD subtypes (Inattentive: ADHD-I; Hyperactive/Impulsive: ADHD-HI; Combined: ADHD-C). Children with ADHD were assigned to the ADHD-I group (n = 21) if they met criteria for inattentiveness but not hyperactivity/impulsivity on the DICA-IV, and a T-score of 65 or greater on the CPRS Scale L (DSM-IV criteria for Predominantly Inattentive Type), and a T-score of 60 or less on the CPRS Scale M (DSM-IV criteria for Predominantly Hyperactive-Impulsive Type) OR had a rating of 2 or 3 on six out of nine Inattention items on the ADHD Rating Scale IV and a rating of 2 or 3 on four or fewer items on the Hyperactivity/Impulsivity scale. Children were assigned to the ADHD-HI (n = 2) if they met criteria for hyperactivity/impulsivity but not inattention on the DICA-IV, and a T-score of 65 or greater on the CPRS Scale M and a T-score of 60 or less on the CPRS Scale L (DSM criteria for Predominantly Inattentive Type) OR had a rating of 2 or 3 on six out of nine Hyperactivity/Impulsivity items on the ADHD Rating Scale IV and a rating of 2 or 3 on four or fewer items on the Inattention scale. All other children who met criteria for ADHD were assigned to the ADHD-C (Combined subtype) group (n = 33). Since only two children were diagnosed with ADHD-HI, the ADHD-C and ADHD-HI groups were combined for analyses. Children with ADHD taking psychoactive medications other than stimulants were excluded. Children who were taking stimulant medication (n = 35) were removed from these medications the day before and the day of testing.
A total of 90 children were included in the typically developing control group. Control participants were required to have T-scores of 60 or below on the DSM-IV Inattention (L) and DSM-IV Hyperactivity (M) subscales of CPRS-R and no history of behavioral, emotional, or serious medical problems. Additionally, controls were not included if there was a history of school-based intervention services as established by parent interview, or if they met DSM-IV psychiatric disorder except specific phobia (n = 3) as reported on the DICA-IV.
Prior to scheduling, parents of participants were interviewed by telephone to obtain demographic information and school and developmental history. If the child was deemed eligible, the DICA-IV was administered to parents by phone. Data were collected over 2 days of testing, less than 1 month apart. The overall sample was 77% Caucasian, 14% African-American, 7% Biracial, 1% Asian, and 1% Hispanic.
Procedures
Demographic and Screening Measures
Hollingshead Index (Hollingshead, 1975). Socioeconomic status (SES) for each participant was estimated by a widely used four-factor index (i.e., gender, marital status, education, and occupation).
Diagnostic Interview for Children, Fourth Edition (DICA-IV; Reich et al., 1997). Parents of children deemed eligible via telephone screen were administered the DICA-IV, which is based on the DSM-IV (American Psychiatric Association, 1994). This is a semi-structured interview that is designed for determining selected current and retrospective psychiatric diagnoses including ADHD (past and present), Conduct Disorder, ODD, Major Depressive Disorder, Dysthymia, Separation Anxiety Disorder, Panic Disorder, Generalized Anxiety Disorder, Specific Phobia, and Obsessive Compulsive Disorder.
Conners' Parent Rating Scale-Revised, Long Form (CPRS) (Conners et al., 1996). This is an 80-item scale assessing inattention, hyperactivity, impulsivity, conduct problems, learning problems, psychosomatic problems, anxiety, and social competence. The scales correspond with ADHD symptoms in the DSM-IV. Separate norms are provided for boys and girls.
ADHD Rating Scale-IV (DuPaul et al., 1998). This is an 18-item scale (nine inattention items and nine hyperactivity/impulsivity items) directly corresponding to DSM-IV diagnostic criteria for ADHD, completed by parents describing the child's behavior over the past 6 months. Responses are coded on a four-step Likert scale from “not at all” to “very much.” Separate norms are provided for boys and girls.
Executive Function Measures
Performance-based EF measures used in the current study are listed in Table 1. The measures were chosen to represent a broad sampling of EF skills (response inhibition, response preparation, working memory, and planning/switching), using multiple measures for each sub-component of EF. Multiple response modalities (e.g., spoken, written, hand movement, button press) were used, and when possible, tests emphasizing verbal and nonverbal skills were included within each EF component.
Table 1.
Table 1.
Executive function (EF) measures examined in the study
Response Inhibition
PANESS Total Overflow (Denckla, 1985). Each participant completed the Physical and Neurological Assessment of Subtle Signs (PANESS), a motor examination standardized for age, sex, and handedness. Detailed information on administration and scoring is outlined in Gidley Larson and colleagues (2007). Children with ADHD have been shown to have significantly more overflow movements than typically developing children (Cole et al., 2008) and PANESS Total Overflow has been found to correlate with other measures of conscious response inhibition (Cole et al., 2008; Mostofsky et al., 2003).
Conflicting Motor Response. This measure was adapted from the Luria-Christensen battery (Christensen, 1975). Participants were instructed to close their eyes as the examiner sat across from them. When the examiner touched their hand, they were instructed to raise the opposite hand. Twenty-four trials were administered for each hand (48 in total) in a pseudo-random sequence. Raising the same hand that was tapped was coded as an error. Children with ADHD have been shown to have increased errors of commission on this measure compared with controls (Mahone et al., 2006; Mostofsky et al., 2003).
Go/No-go Percent Commissions. Participants were seated in front of a computer that flashed green and red spaceships and were told to press the spacebar in response to green ships only. Cues appeared on the screen for 300 ms and were presented once every 1,800 ms (fixed 1,500-ms interstimulus interval). Cues were weighted towards green spaceships at a ratio of 3:1 and the task lasted 8 min. Commissions were defined as pressing the space bar after the presentation of a red ship. Children with ADHD have been shown to produce significantly more commission errors than controls (Wodka et al., 2007).
D-KEFS Color–Word Interference Test, Condition 3: Inhibition (Delis, Kaplan, & Kramer, 2001). Based on the Stoop test (Stroop, 1935), participants were given a list of color names printed in a different-colored ink and asked to say the color of the ink and not read the word. Scores were based on errors and total time to complete. Children with ADHD have been shown to have more inhibition errors than controls on this measure (Wodka, Loftis, et al., 2008).
Response Preparation
PANESS Total Timed Score. Total timed score is based on six sets of repetitive and sequential movements of hands and feet including foot tapping (20 taps), heel/toe tapping (10 sets), hand patting (20 taps), hand pronation/supination (10 sets), repetitive finger tapping (20 taps), and finger sequencing (5 sets) with both the right and left hands and feet. Children with ADHD have been shown to perform more slowly than controls on these timed measures (Cole et al., 2008).
D-KEFS Color–Word Interference, Condition 1: Color Naming. Participants named patches of color on a page as quickly as possible. Children with ADHD have been shown to have impaired performance on this measure compared with typically developing controls (Wodka, Loftis, et al., 2008).
D-KEFS Trail Making Test Condition 1: Visual Scanning. Participants were instructed to mark all of the number threes on a page as quickly as possible. Children with ADHD have been shown to perform more slowly on measures of visual scanning than controls (Koschack, Kunert, Derichs, Weniger, & Irle, 2003).
Go/No-go Coefficient of Variability. Each participant's reaction time variability was calculated as ([standard deviation “go” reaction time]/[mean “go” reaction time]) × 100. Children with ADHD have been previously shown to have significantly greater intra-individual variability on this task than controls (Ryan, Martin, Denckla, Mostofsky, & Mahone, 2010; Vaurio et al., 2009; Wodka et al., 2007).
Working Memory
Digit Span Backwards (WISC-IV; Wechsler, 2003). Scaled scores for backwards trial were used. Children with ADHD have been shown to have reduced performance on this measure compared with controls (Karatekin & Asarnow, 1998).
CANTAB Spatial Working Memory, Between-Search Errors (Cognition, 1996). This self-ordered pointing task utilizes a touch-screen monitor. Participants were shown colored boxes on a computer screen and instructed to search through an array of boxes looking for a blue token in order to “collect” enough blue tokens to fill up a container on the right side of the screen. Participants were told that once a blue token had been found within a particular box, that box would never be used again to hide a token. Participants completed four test trials with four, six, and eight boxes. “Between-search errors” were defined as returning to a box in which a token had already been found. Children with ADHD have been found to commit more between-search errors on this measure than controls (Goldberg et al., 2005).
D-KEFS Color–Word Interference Test Condition 4: Inhibition/Switching. This trial added a condition in which some colors were boxed, for which the rule was reversed—thus adding an additional working memory demand. Children with ADHD have been shown to have poorer performance than controls on this measure (Wodka, Loftis, et al., 2008).
Spatial Span (WISC-III–Process Instrument; Wechsler, 1991). Scaled scores for backward span were used in analyses. Children with ADHD have been shown to have reduced performance on similar visuospatial working memory tasks (Karatekin & Asarnow, 1998; Westerberg, Hirvikoski, Forssberg, & Klingberg, 2004).
Planning/Shifting
CANTAB Spatial Working Memory Strategy Score: The strategy score was derived from the number of searches for blue tokens that started from the same location. Lower strategy scores reflect better performance and are given for search sequences that consistently start from the same box.
D-KEFS Tower: Total Achievement Score. The Total Achievement Score was used in analyses and was based on the number of moves to build the tower, rule violations, completion time, and final tower correctness. Children with ADHD have been shown to have impaired performance on this measure compared with typically developing controls (Wodka, Loftis, et al., 2008).
D-KEFS Trail Making Test Condition 4: Number/Letter Switching. Participants were instructed to connect items on a page, switching between numbers and letters beginning with 1 and A, and connecting them in numerical and alphabetical order, respectively. Children and adolescents with ADHD have been shown to perform significantly worse on number/letter switching than controls (Martel, Nikolas, & Nigg, 2007; Oades & Christiansen, 2008).
Data Analyses
Group and sex differences on demographic variables were examined using ANOVA (for continuous variables) and chi-square analyses (for categorical variables). The EF variables were grouped together for analyses based on a priori hypotheses about their contribution to the EF construct (Table 1). Four components of the EF construct were obtained: response inhibition (Conflicting Motor Response, PANESS Total Overflow, Go/No-go Percent Commissions, D-KEFS CWI Inhibition), response preparation (D-KEFS CWI Color Naming, D-KEFS Trails Visual Scanning, PANESS Total Time, Go/No-go Coefficient of Variability), working memory (Digit Span Backwards, CANTAB Spatial Working Memory Between-Trial Errors, D-KEFS CWI Inhibition/Switching, Spatial Span Backwards), and planning/shifting (CANTAB Spatial Working Memory Strategy Score, D-KEFS Tower Total Achievement, D-KEFS Trails Number/Letter Switching).
Group and sex differences on each of the four EF components were examined using a series of 2 (ADHD vs. control) × 2 (boys vs. girls) factorial MANOVAs. Significant main effects for MANOVAs were followed by separate ANOVAs for the variables comprising that EF component. Those EF components showing significant interaction effects were followed by sex-specific MANOVAs, and (as appropriate) univariate (sex-specific) between-group comparisons. A similar procedure was used to examine subtype differences (Combined vs. Inattentive) within the ADHD group as a whole.
Demographic Information
Demographic information for the sample is provided in Table 2. For the entire sample, there were no significant differences between ADHD and control groups in age: F(1,145) = 0.05, p = .82; sex ratio: χ2 = 0.001, p = .98; racial distribution: χ2 = 5.24, p = .39; handedness: χ2 = 3.45, p = .18; or SES: F(1,133) = 0.09, p = .76. The control group had significantly higher FSIQ, F(1,145) = 9.06, p = .003, which included significant reductions on the Working Memory, F(1,145) = 5.76, p = .02, Processing Speed, F(1,145) = 6.22, p = .01, and Verbal Comprehension, F(1,145) = 5.21, p = .02, indexes, but not on Perceptual Reasoning (PRI). Given the overlap between components of IQ and EF (especially involving working memory and response preparation/processing speed), it was felt that covarying for FSIQ was not appropriate when measuring group differences on executive functioning (Dennis et al., 2009). Additionally, a recent meta-analysis of the effects of attention deficits on IQ assessment noted that children with ADHD taking short-acting stimulant medications had a mean increase of 6 to 7 IQ points compared with stimulant-naïve children who had been tested, suggesting that reduced IQ scores relative to typically developing peers may be driven by attentional problems and suboptimal test taking behavior rather than reduced intelligence (Jepsen, Fagerlund, & Mortensen, 2009).
Table 2.
Table 2.
Demographic information
As expected, there were significant group differences between ADHD and control groups on the Conners' Parent Rating Scale (DSM-IV Total Scale), F(1,137) = 513.67, p < .00001, and a significant main effect for sex, F(1,137) = 6.16, p = .014. Both boys and girls with ADHD were rated as significantly more impaired than sex-matched controls (both p < .00001); however, there were no significant differences in parent ratings of boys and girls with ADHD, F(1,49) = 2.58, p = .12.
Among boys, there were no significant differences between the ADHD (n = 30) and control group (n = 48) in age, SES, handedness, or racial distribution; however, boys with ADHD had significantly lower FSIQ, F(1,76) = 8.52, p = .005, with reductions on VCI, F(1,76) = 5.84, p = .02, and trends on PRI, F(1,76) = 3.76, p = .06, and PSI, F(1,76) = 3.60, p = .06. There were no significant differences on WMI, F(1,76) = 1.76, p = .19. The sample of boys with ADHD included 20 with Combined subtype and 10 with Inattentive subtype. Within this sample of boys with ADHD, there were no significant differences between the two subtypes in age, FSIQ, SES, handedness, or racial distribution.
Among girls, there were no significant differences between those with ADHD (n = 26) and controls (n = 42) in FSIQ, age, SES, handedness, or racial distribution. The sample of girls with ADHD included 15 with Combined subtype and 11 with Inattentive subtype. Within this sample of girls with ADHD, there were no significant differences between the two subtypes in age, FSIQ, SES, handedness, or racial distribution. Among children with ADHD, the subtype distribution was not different between boys and girls (χ2 = 0.48, p = .49).
Group Differences on EF Components
Response Inhibition. Means and standard deviations for response inhibition variables are listed in Table 3. The MANOVA revealed a significant main effect for group (Pillai's V = 0.17, p = .00005, An external file that holds a picture, illustration, etc.
Object name is acq050IL0001.jpg = 0.17), such that children with ADHD had significantly poorer response inhibition than controls. Univariate tests revealed significant ADHD-related reductions on all four response inhibition measures (all p ≤ .05). There was a multivariate main effect for sex (Pillai's V = 0.06, p = .05, An external file that holds a picture, illustration, etc.
Object name is acq050IL0002.jpg = 0.06), boys showing poorer performance than girls; however, the only significant univariate effect for sex was on go/no-go commission rate (p = .009), for which boys committed more errors than girls. There was also a significant multivariate group-by-sex interaction (Pillai's V = 0.06, p = .05, An external file that holds a picture, illustration, etc.
Object name is acq050IL0003.jpg = 0.06). Sex-specific MANOVAs revealed that both boys (Pillai's V = 0.17; p = .009, An external file that holds a picture, illustration, etc.
Object name is acq050IL0004.jpg = 0.17) and girls with ADHD (Pillai's V = 0.26; p = .0008, An external file that holds a picture, illustration, etc.
Object name is acq050IL0005.jpg = 0.26) showed poorer response inhibition, compared with sex-matched controls. Univariate comparisons within sex revealed that boys with ADHD performed worse than sex-matched controls on Conflicting Motor Response, F(1,77) = 9.78, p = .002, An external file that holds a picture, illustration, etc.
Object name is acq050IL0006.jpg =.11, D-KEFS CWI Inhibition, F(1,77) = 4.40, p = .04, An external file that holds a picture, illustration, etc.
Object name is acq050IL0007.jpg =.06, and Go/No-go commission rate, F(1,77) = 4.63, p = .04, An external file that holds a picture, illustration, etc.
Object name is acq050IL0008.jpg =.06, but not PANESS total overflow, F(1,77) = 0.006, p = .94, An external file that holds a picture, illustration, etc.
Object name is acq050IL0009.jpg =.00008. In contrast, girls with ADHD showed the most striking reduction, compared with sex-matched controls, on PANESS total overflow, F(1,67) = 14.77, p = .0003, An external file that holds a picture, illustration, etc.
Object name is acq050IL0010.jpg =.18, with significant impairment also noted on Conflicting Motor Response, F(1,87) = 12.05, p = .001, An external file that holds a picture, illustration, etc.
Object name is acq050IL0011.jpg =.15, but not D-KEFS CWI Inhibition or Go/No-go commission rate. Boys and girls with ADHD did not differ on PANESS overflow, F(1,55) = 1.22, p = .28, An external file that holds a picture, illustration, etc.
Object name is acq050IL0012.jpg =.02; however, control boys had significantly greater overflow than control girls, F(1,89) = 9.10, p = .003, An external file that holds a picture, illustration, etc.
Object name is acq050IL0013.jpg =.09 (Fig. 1).
Table 3.
Table 3.
Group differences on executive function measures
Fig. 1.
Fig. 1.
PANESS Total Overflow mean scores in boys and girls with and without ADHD.
Response Preparation. Means and standard deviations for response preparation variables are listed in Table 3. The MANOVA revealed a significant main effect for group (Pillai's V = 0.13, p = .001, An external file that holds a picture, illustration, etc.
Object name is acq050IL0014.jpg = 0.13), such that children with ADHD demonstrated impaired response preparation performance, compared with controls; however, the main effect for sex (Pillai's V = 0.02, p = .59, An external file that holds a picture, illustration, etc.
Object name is acq050IL0015.jpg = 0.02) and the sex-by-group interactions (Pillai's V = 0.03, p = .34, An external file that holds a picture, illustration, etc.
Object name is acq050IL0016.jpg = 0.03) were not significant. Univariate group comparisons revealed significant group differences (ADHD < control) on two of the four variables: PANESS Total Time and Go/No-go Coefficient of Variability (both p < .01; Fig. 2).
Fig. 2.
Fig. 2.
Go/No-Go Variability means in boys and girls with and without ADHD.
Working Memory. Means and standard deviations for working memory variables are listed in Table 3. The MANOVA revealed a significant main effect for group (Pillai's V = 0.10, p = .004, An external file that holds a picture, illustration, etc.
Object name is acq050IL0017.jpg = 0.10), such that children with ADHD had reduced working memory performance, compared with controls. The main effects for sex (Pillai's V = 0.008, p = .89, An external file that holds a picture, illustration, etc.
Object name is acq050IL0018.jpg = 0.008) and the sex-by-group interaction (Pillai's V = 0.01, p = .84, An external file that holds a picture, illustration, etc.
Object name is acq050IL0019.jpg = 0.01) were not significant. Univariate group comparisons revealed significantly reduced working memory performance among children with ADHD on all four tests (all p < .05; Fig. 3).
Fig. 3.
Fig. 3.
D-KEFS CWI Inhibition/Switching means in boys and girls with and without ADHD.
Planning/Switching. Means and standard deviations for planning/switching variables are listed in Table 3. The MANOVA revealed a significant main effect for group (Pillai's V = 0.10, p = .002, An external file that holds a picture, illustration, etc.
Object name is acq050IL0020.jpg = 0.10), such that children with ADHD demonstrated impaired performance compared with controls. Follow-up univariate group comparisons revealed significantly poorer performance on two of the three planning/switching tests in the ADHD group, including CANTAB SWM Strategy Score, F(1,145) = 12.15, p = .001, An external file that holds a picture, illustration, etc.
Object name is acq050IL0021.jpg = 0.08, and D-KEFS Tower Total Score, F(1,145) = 5.27, p = .02, An external file that holds a picture, illustration, etc.
Object name is acq050IL0022.jpg = 0.04. There was also a significant sex-by-group interaction (Pillai's V = 0.07, p = .02, An external file that holds a picture, illustration, etc.
Object name is acq050IL0023.jpg = 0.07); however, the main effect for sex was not significant (Pillai's V = 0.02, p = .33, An external file that holds a picture, illustration, etc.
Object name is acq050IL0024.jpg = 0.02).
To investigate the basis of the interaction effect, group comparisons were made separately for boys and girls. Sex-specific MANOVAs revealed that girls with ADHD (Pillai's V = 0.25; p = .0004, An external file that holds a picture, illustration, etc.
Object name is acq050IL0025.jpg = 0.25), but not boys with ADHD (Pillai's V = 0.02; p = .77, An external file that holds a picture, illustration, etc.
Object name is acq050IL0026.jpg = 0.02), showed impaired planning/switching performance. Univariate group comparisons among the girls revealed significantly reduced performance on two of the three tests: CANTAB Spatial Working Memory Strategy, F(1,155) = 18.23, p = .00006, An external file that holds a picture, illustration, etc.
Object name is acq050IL0027.jpg = 0.22 (Fig. 4), D-KEFS Tower Total Achievement, F(1,155) = 4.61, p = .04, An external file that holds a picture, illustration, etc.
Object name is acq050IL0028.jpg = 0.07, and a strong trend on D-KEFS Trails Number/Letter Switching, F(1,155) = 3.33, p = .07, An external file that holds a picture, illustration, etc.
Object name is acq050IL0029.jpg = 0.05.
Fig. 4.
Fig. 4.
CANTAB Strategy Score means in boys and girls with and without ADHD.
ADHD Subtype Differences on Executive Control Measures
Within the ADHD group, there were no significant differences between children with the Combined subtype (n = 35) and Inattentive subtype (n = 21) in age, SES, FSIQ, handedness, sex ratio, or racial distribution. There were no significant multivariate differences between ADHD subtypes in response inhibition (Pillai's V = 0.02, p = .89, An external file that holds a picture, illustration, etc.
Object name is acq050IL0030.jpg = 0.02), working memory (Pillai's V = 0.11, p = .18, An external file that holds a picture, illustration, etc.
Object name is acq050IL0031.jpg = 0.11), planning/switching (Pillai's V = 0.09, p = .17, An external file that holds a picture, illustration, etc.
Object name is acq050IL0032.jpg = 0.09), or response preparation (Pillai's V = 0.04, p = .74, An external file that holds a picture, illustration, etc.
Object name is acq050IL0033.jpg = 0.04) variables.
Compared with age-, sex-, and SES-matched controls, children with ADHD manifested consistent and broad executive dysfunction across a wide variety of measures emphasizing four EF components: Response inhibition, response preparation (including efficiency and consistency of response speed), verbal and spatial working memory, and planning. The present results are consistent with prior studies and meta-analyses of executive control skills in ADHD (Willcutt et al., 2005, 2008). Girls and boys with ADHD showed similar patterns of deficit on tasks involving working memory and response preparation; however, they manifested different patterns of executive dysfunction on tasks related to response inhibition and planning. These sex differences in performance cannot be explained by sex differences in comorbidities (which were controlled), ADHD subtypes (which were proportionate among boys and girls), or differential medication use.
These results were not fully consistent with our hypotheses, in which we expected boys with ADHD to be impaired on all components of EF and girls to be impaired only on “higher order” EFs (but not on the more “basic,” earlier-developing EFs). The data suggest that, after controlling for comorbidities and sex differences in ADHD subtype among children ages 8–13, girls with ADHD were impaired (relative to control girls) across all EF components—including basic and higher order skills. In contrast, boys with ADHD were impaired on the more basic functions (response inhibition, response preparation), as well as working memory, but not on planning/shifting. Thus, the outstanding deficit among girls with ADHD in this age range involves strategic planning. This planning deficit was also observed when comparing girls with ADHD directly to age-matched boys with ADHD. Additionally, within response inhibition, girls with ADHD showed elevated motor overflow, while boys with ADHD showed greater impairment during conscious, effortful response inhibition. This dissociation may be related to the pattern of anomalous supplementary motor complex (reduced in boys and girls) and prefrontal (reduced in boys but not girls) development.
While the present findings are consistent with past literature highlighting deficits in response inhibition among children with ADHD (Barkley, 1997; Willcutt et al., 2005; Wodka et al., 2007), they suggest that impaired inhibitory control manifests differently in boys and girls with the disorder. Compared with age- sex-, and SES-matched controls, both girls and boys with ADHD showed deficits in response inhibition; however, among boys, the deficits were consistently observed on tasks requiring the ability to consciously withhold an incorrect response (i.e., boys, but not girls with ADHD were more impaired than sex-matched controls on go/no-go commission rate and Color Word Interference Inhibition). Conversely, girls (but not boys) with ADHD showed significantly increased motor overflow (relative to sex-matched controls) on a structured motor examination. Of note, this relative difference in overflow rate (relative to sex-matched controls) between boys and girls with ADHD was driven by sex differences in overflow among controls (i.e., control boys having significantly more overflow than control girls), whereas boys and girls with ADHD did not differ in total overflow.
Three prior studies from our research group have highlighted earlier development of motor skills among girls. Using the PANESS (Denckla, 1985) in typically developing children ages 7–14, Gidley Larson and colleagues (2007) reported that girls were faster and more proficient than age-matched boys on timed movements and showed fewer subtle signs, including overflow and dysrhythmia, accompanying gaits and stations. Roeder and colleagues (2008) examined age-related changes in right (vs. left) hand superiority among 144 right-handed children. While right-hand superiority (right-left gap) decreased significantly with age on four of six timed tasks, two tasks also showed gender differences; thus, girls demonstrated a more rapid “equalization” of speed than boys, suggesting that diminishing right-left speed differences may indicate cerebral and corpus callosum maturation. Cole and colleagues (2008) examined effects of age and sex on motor performance in children ages 7–15 with and without ADHD. Typically developing girls and boys, and girls with ADHD showed age-related reductions in motor subtle signs, whereas boys with ADHD did not. Together, these findings suggest that girls with and without ADHD may have different trajectories of development than boys—arguing for examination of sex-specific patterns of motor development in children with ADHD. In this regard, the results are consistent with prior studies highlighting the relative superiority of typically developing girls in this age range on tasks of motor skill development (Gidley Larson et al., 2007; Roeder et al., 2008). The present findings are in contrast, however, with prior studies showing greater overflow among boys (compared with girls) with ADHD (Cole et al., 2008), perhaps due to the reduced age range in the present study or to oversampling for subtypes less common for gender to obtain subtype equalization in the present study. The current data, which are more balanced with regard to sex distribution, also contrast with previous findings from our research unit (in a sample of primarily boys with and without ADHD) in which overflow movement was found to predict impairment on response inhibition on tasks in which conscious inhibition of an incorrect response is required (Mostofsky et al., 2003).
Unlike the patterns observed on tasks of response inhibition, the observed deficits on tasks of planning/switching among children with ADHD were driven by notably impaired performance among girls with ADHD. That is, girls (but not boys) with ADHD showed robust deficits (compared with sex-matched controls) on tasks of planning/switching. Further, girls with ADHD were also impaired (relative to boys with ADHD) on spontaneous strategy use. This specific (relative) deficit in strategic planning among girls with ADHD may have emerged because we oversampled for girls with ADHD Combined subtype (and for boys with ADHD Inattentive subtype) in order to eliminate the subtype confound in sex comparisons within the participants with ADHD. This emphasis on matching for subtype distribution in boys and girls with ADHD may have also contributed to the striking absence of differences between ADHD subtypes on any component of EF, and may have contributed to the different pattern of findings than has been observed in previous studies that found girls and boys with ADHD to have similar profiles of executive dysfunction in preteen and teen years (Seidman et al., 2005).
Taken together, these findings highlight the need to examine sex as a potential moderating variable when considering executive control “deficits” in children with ADHD. Because boys and girls are at different points in their biological development during the elementary school years, absolute skill difference between boys and girls with ADHD may not be the most salient variable (Mahone and Wodka, 2008). Rather, skill deficits are most salient when considered relative to one's age- and sex-matched peers. Because typically developing girls are more neurobiologically mature than typically developing boys prior to adolescence, girls with ADHD may not need to perform as poorly as boys with ADHD in order to be deficient (relative to their sex-matched peers). This consideration is important for clinicians when making decisions about diagnosis and treatment among girls with ADHD.
The current study also suggests that core elements of executive control (response inhibition, response preparation, and working memory) are affected in children with ADHD, regardless of sex. Both boys and girls with ADHD performed poorly (compared with sex-matched controls) on EF components involving response preparation and working memory, and had similar profiles of dysfunction on the tasks used to assess each component. Overall, girls and boys with ADHD were equally impaired on response inhibition, though their profiles of dysfunction on the individual tasks were different. Research in both girls and boys with ADHD has highlighted deficits in these areas (de Jong et al., 2009; Rommelse et al., 2008; Wodka, Mostofsky, et al., 2008), and problems with response inhibition, working memory, and response preparation appear to be core deficits in both girls and boys with ADHD. Additionally, the failure to identify deficits among boys with ADHD on higher order planning/shifting components of EF may be due, in part, to the age range of our sample (8–13 years). Taking into account the later development among boys, it may be that boys with ADHD will continue to “grow into” their planning/shifting deficits later in their teenage years and beyond, highlighting the need for continued assessment of these skills throughout adolescence. A related question is whether the earlier developing girls with ADHD “grow out” of some of their deficits in later adolescence, or whether these difficulties remain into young adulthood.
Strengths of the current study include multiple measures of different EF components, strict diagnostic procedures for ADHD, and control of subtypes and comorbidities. Nevertheless, these methods of controlling extraneous variance in the sample may also have contributed to the slightly above average IQ level of the sample. The increased IQ range may have attenuated some of the deficits on these performance-based measures of EF (Mahone et al., 2002). Additionally, the current findings may also be less robust than might be observed among samples of children with ADHD who present with more comorbidities or in larger sample sizes. In particular, the absence of subtype effects in children with ADHD may partially reflect limited power due to sample size. Finally, different patterns of EF deficits in boys and girls with ADHD may be evident when other EF measures are utilized, such as rating scales of adaptive functioning.
The current findings highlight the multidimensional nature of EF and the need to use multiple, diverse methods of assessment when considering the construct. Our approach, which relied on a priori assumptions of these components in determining EF structure, assumed a degree of separability and independence among response inhibition, working memory, planning, and response preparation. In fact, these component skills are likely inter-related, and many tests “load” on several EF factors. For example, in a confirmatory factor analysis, Miyake, Friedman, Rettinger, Shah, & Hegarty, 2001 evaluated the extent to which three components of EF, shifting, working memory, and inhibition, represented unitary or separable constructs. Correlations among the three variables were moderate, suggesting they are separable, but related.
Future research should continue the use of multiple measures of each EF component, allowing for the clarification of latent variables underlying the construct in both boys and girls with ADHD. The use of fMRI may be particularly fruitful in helping to understand how girls with ADHD (who have relatively spared prefrontal cortex development) recruit prefrontal regions for “top-down” control of behavior, including the inhibition of hyperactivity and more conscious response control; and whether this recruitment occurs at the expense of higher-order planning skills, by draining resources away from the cognitive tasks.
Funding
Supported by HD-24061 (Developmental Disabilities Research Center), R01 NS043480, R01 NS047781, R01 NS050153, and the Johns Hopkins University School of Medicine Institute for Clinical and Translational Research, an NIH/NCRR CTSA Program, UL1-RR025005.
Conflict of Interest
None declared.
Acknowledgements
Portions of this manuscript presented as a paper at the 37th Annual Meeting of the International Neuropsychological Society in Atlanta, Georgia, February 9, 2009. Appreciation is expressed to Becca Martin, Camille Davis, and Lisa Ferenc for their assistance with data collection and manuscript preparation.
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