Current Psychiatry Reports          (2019) 21:34


Autism Spectrum Disorders and ADHD: Overlapping                           Phenomenology, Diagnostic Issues, and Treatment Considerations


Kevin M. Antshel1 • Natalie Russo1



Ⓒ Springer Science+Business Media, LLC, part of Springer Nature 2019



Purpose of Review Autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD) are both increasing in prevalence and commonly co-occur with each other. The goal of this review is to outline what has been published recently on the topics of ASD, ADHD, and the comorbid state (ASD+ADHD) with a particular focus on shared phenomenology, differential diagnosis, and treatment considerations.

Recent Findings ASD and ADHD have shared genetic heritability and are both associated with shared impairments in social functioning and executive functioning. Quantitative and qualitative differences exist, however, in the phenotypic presentations of the impairments which characterize ASD and ADHD. For ASD interventions to be maximally efficacious, comorbid ADHD needs to be considered (and vice versa).

Summary The research on ASD and ADHD suggests some overlap between the two disorders yet enough differences to indicate that these conditions are sufficiently distinct to warrant separate diagnostic categories.

Keywords ADHD . Autism . Autism spectrum disorder . Neurodevelopmental disorder . Comorbidity . Diagnosis . DSM-5






Attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are both neurodevelopmental disor- ders which typically onset in childhood. ADHD is defined by the presence of impairing symptoms of inattention and/or hyperactivity–impulsivity that onset before age 12, is present across two or more settings, and cannot be better explained by another condition [1]. ASD is characterized by enduring and impairing social communication and interaction deficits that occur across multiple contexts along with the presence of re- stricted, repetitive behaviors, interests or activities, or sensory symptoms [1].

Prior to the Diagnostic and Statistical Manual for Mental Disorders 5th edition (DSM-5) [1] in 2013, clinicians were unable to make an ADHD diagnosis in the context of ASD. It

was presumed that any symptoms of inattention and/or hyperactivity–impulsivity were secondary to ASD and not due to an additional ADHD diagnosis [2]. With this exclusion- ary criterion lifted in the DSM-5, it is not surprising that a vast literature has been published within the past several years on the topic of ADHD, ASD, and ASD+ADHD. (Please see Fig. 1 for graphical representation of this increase in research activity.)

Both ADHD [3] and ASD [4] are increasing in prevalence and the symptoms and impairments of both conditions often persist into adulthood [5•]. When considered in the context of the substantial impairments and societal costs (e.g., reduced parental quality of life [6]) associated with ADHD [7], ASD [8], and the amplification of those negative outcomes in the comorbid condition (ASD+ADHD) [914], it is clear that ADHD, ASD, and ASD+ADHD represent a public health problem. For example, children with ASD constitute 8% and


                                                                                                                  children with ADHD represent 13% of all youth receiving


This article is part of the Topical Collection on Attention-Deficit Disorder



* Kevin M. Antshel



1     Department of Psychology, Syracuse University, 800 University Avenue, Syracuse, NY 13244, USA

school-based services under the Individuals with Disabilities Education Act [15]. Thus, these two conditions alone account for nearly one-fourth of all children receiving school-based services.

ASD and ADHD often co-occur [16]; 13% of youth in a large epidemiological ADHD study were diagnosed with







Fig. 1 Number of PubMed citations for ASD, ADHD, and ASD+ADHD




comorbid ASD [17]. Others have similarly reported that ap- proximately 1 in 8 youth with ADHD have ASD [18]. Conversely, ADHD is the most common comorbidity in chil- dren with ASD with comorbidity rates in the 40–70% range [1922]. The substantial overlap between ADHD and ASD presents clinicians with difficult differential diagnostic [23] and treatment [24•] considerations. For example, youth with ADHD are diagnosed with ASD approximately 2 years later than children with ASD without a pre-existing ADHD diag- nosis [25, 26]. Similarly, youth with ADHD who do not have an ASD diagnosis still have elevated levels of ASD symptoms

[27] and vice versa [28••]. Given all of the above, understand- ing the phenotypic expression of ADHD, ASD, and ASD+ ADHD is an important clinical goal [29].

In this review, we consider the recent empirical literature that has been published on ASD, ADHD, and, when applica- ble, ASD+ADHD. Our goal is to cover the overlapping phe- nomenology b e tween ASD a nd ADHD from a biopsychosocial perspective. We then consider issues and complexities associated with diagnosing ASD and ADHD

and conclude with treatment considerations relevant to ASD and ADHD.



Overlapping Phenomenology


Biology Both ADHD and ASD are considered to be neurodevelopmental disorders that onset in childhood, and although causal links are currently unknown, both disorders are highly heritable with approximately 70–80% of both phe- notypes being accounted for by genetics [30, 31]. Further, when one dyad of a twin pair has ASD, there is a much higher likelihood that the unaffected twin will have symptoms of ADHD [32]. Hyperactive–impulsive symptoms correlate strongly (r = .56) with restricted and repetitive behaviors in ASD [33] and family members of individuals with ASD have elevated rates of ADHD diagnoses [32, 34, 35] and vice versa [36]. For example, siblings of probands with ASD have nearly a 4-fold increased risk for ADHD compared to matched con- trols [37•].




All of the above has led to the speculation that ASD and ADHD have shared genetic heritability [32]. As of yet, no specific gene variations have been identified that link these disorders together, but current research examining genome- wide copy number variations (CNV’s) have identified in- creases in rare CNV’s at similar loci among those with ADHD, ASD, intellectual disability, and schizophrenia, pro- viding preliminary evidence of shared genetic pathways be- tween these disorders [38, 39].

Beyond genetics, there is also little overlap in findings from neuroimaging studies between those with ADHD and those with ASD with respect to either resting state connectivity or functional network activations. However, methodological complications and limitations might account for a large pro- portion of the lack of consistency. These limitations include, among others, the heterogeneity of symptom presentations both within and across disorders, the small sample sizes of these often expensive and intensive studies, differences in methodologies across studies, and the wide range of ages used within and across studies that complicate the interpretation of findings given the developmental nature of both disorders.

In spite of these limitations, several research groups have been at the forefront of this work in the last decade or so. The findings from their studies [40••, 41], which are corroborated by recent meta-analyses [42, 43], suggest that ADHD and ASD are char- acterized as disorders of large-scale connectivity but with little overlap in the specific regions that are under or over connected, with one exception. Children with ADHD and those with ASD and ADHD symptoms, but not those with ASD without ADHD symptoms, showed connectome-wide dysconnectivity in the precuneus, an area considered to be a hub of the default mode network, involved in mind-wandering [40••]. The findings from this study suggest a shared neural atypicality in the impact of ADHD symptoms among those with and without a comorbid ASD diagnosis, and support the importance of future research in this area.


Social Function in ADHD and ASD Social difficulties are a hallmark of ASD and are required for a diagnosis. Although deficits in social function are not explicitly required for a diagnosis of ADHD, they factor into several diagnostic criteria that include the following: “often has difficulty waiting in line,” “often blurts out answers,” and “often interrupts or in- trudes on others,” and these are commonly reported by parents of youth with ADHD as causing social impairment [44]. The social impairments of ADHD seem to reflect impulsivity or hyperactivity, but might also reflect more general social dys- function. Recent work has provided some clues as to the na- ture of these impairments by focusing on the mechanisms underlying their expression in ASD and ADHD.


Social Cognition Determining the mechanisms underlying so- cial impairment may provide important clues to the nature of

the overlap between those with ADHD and those with ASD. For example, social perception abilities, as measured by the reading of the Eyes Test, in which participants determine an individual’s mental state on the basis of black and white pic- tures of eyes, varied upon a continuum among those with neurodevelopmental disorders that included ASD, ADHD, and obsessive-compulsive disorder (OCD) in relation to typi- cally developing comparison participants. Those with OCD trended towards having better social perception than even the typically developing groups, while those with ASD had the greatest deficits, with the performance of those with ADHD being intermediate [45]. In addition to examining group differences, the authors also examined the contribution of ADHD and social communication symptoms to task per- formance across diagnostic groups. They found that across groups, hyperactivity, but not inattention exerted a negative effect on social perception scores, and that when controlling for social communication scores, all group differences disap- peared. Together, these findings suggest that social communi- cation skills/deficits appear to impact social perception simi- larly, irrespective of diagnostic labels, underscoring it as an important transdiagnostic mechanism underlying levels of so- cial impairment.


Social Interactions Low levels of reciprocal friendships are another shared feature between ADHD and ASD [46]. The magnitude of the effect between typically developing peers and those with ADHD on measures of peer regard (r = .27) is larger than the effect sizes for other social domains such as social cognition and social behavior [44]. Youth with ASD likewise have significantly low levels of reciprocated friend- ship [47] and typically developing peers across multiple age groups are less willing to engage with individuals with ASD, often making a decision within 10 seconds of exposure to an individual with ASD [48]. Children with ADHD have intact social knowledge yet impaired social interactions, suggestive of a performance deficit [49]. Conversely, youth with ASD have knowledge deficits [50] and are more likely than those with ADHD to respond to clinic-based social skills training interventions that often teach social skills [51].

The social difficulties of individuals with ASD appear more due to the absence of positive behaviors (e.g., social approach, eye contact) rather than the presence of negative behaviors [52]. Conversely, the social difficulties of individ- uals with ADHD are more likely due to the presence of neg- ative behaviors such as interrupting and intruding on conver- sations [53] suggesting differences in the nature of social im- pairment across diagnosis.

Although social impairment is clearly implicated in both diagnoses, it is not the only domain that has been considered key to understanding the overlap between both disorders. Several studies have compared the cognitive, linguistic, and executive function profiles of both groups, in an attempt to




characterize similarities and differences, as well as search for shared underlying mechanisms between these disorders.


Psychological The psychological profiles of both ADHD and ASD are complex, and comparisons between disorders are complicated by the large heterogeneity of cognitive abilities among those with ASD. Comparisons between ADHD, who generally show average cognitive function, and ASD are often focused on those with ASD and higher cognitive abilities. As such, it is important to note that commonalities between the two groups cannot be generalized to the entire autism spec- trum. Nonetheless, interesting patterns emerge with respect to one broad psychological function, executive function.


Executive Functions Executive function (EF) is broad term that encompasses multiple domains of function including inhibition, cognitive shifting, planning, working memory, and concept for- mation. Once transdiagnostic executive function impairments are controlled for, ADHD and ASD have their own specific profile of executive dysfunction. While ASD is generally con- sidered a more severe condition, executive dysfunction is more pervasive and severe in ADHD [54]. Others have recently sug- gested that ADHD and ASD share overlapping, yet unique, executive function profiles [55]. Furthermore, the association between EF and ADHD symptoms remains after controlling for ASD symptoms. This suggests an additive nature for the co- morbid condition (ASD+ADHD) [56].

Executive function has been studied extensively in both ADHD and ASD, with consistent findings of deficits relative to both age- and IQ-matched typically developing participants in both groups [5759]. However, there appears to some dif- ferentiation between the two diagnostic categories. Specifically, individuals with ADHD appear to struggle most clearly with inhibition, the ability to withhold a pre-potent response, and planning/problem solving, while those with ASD struggle most with cognitive flexibility, which requires holding and switching between multiple perspectives rapidly [58]. Further, age-related improvements are less clear for those with ADHD than ASD, and task performance is positively correlated with parent-reported social and communication abilities, and negatively correlated with hyperactivity for TD and ASD groups, but not those with ADHD [58]. These find- ings suggest that EF is more impaired in ADHD than in ASD, that those with ADHD tend not to improve with age, and further corroborates the notion that profiles of performance do not overlap considerably between the groups.

Studies examining the shared EF profiles of co-occurring ADHD and ASD have found that those with an ASD and ASD+ADHD both have cognitive flexibility and planning impairments while those with ADHD and ASD+ADHD have response inhibition difficulties. Compared to youth with ASD, those with ASD+ADHD are more impaired in working mem- ory on emotional recognition tasks and have higher levels of

parent-reported anxiety [60], suggesting an additive nature to the comorbid condition.

Given the consistent findings of social impairments and executive dysfunction in both ASD and ADHD, it is not sur- prising that the diagnostic overlap between ADHD and ASD peaks in adolescence, possibly due to the increased demands for social adaptation and executive functioning that is present during this developmental period [5•]. Overall psychological profiles of individuals with ADHD, ASD, and co-occurring ADHD an ASD suggest some overlap between the two disor- ders yet enough differences to suggest that these conditions are sufficiently distinct to warrant separate diagnostic categories.



Diagnostic Issues


Gold standard diagnostic measures have been developed for both ASD and ADHD and include the Autism Diagnostic Interview-Revised [61] and the Autism Diagnostic Observation Schedule – 2nd edition [62] for ASD and the use of standardized ADHD rating scales, structured interviews such as the KSADS-PL [63], global impairment measures, and behavioral observations for ADHD [64].


ADHD in ASD One aspect that is critically and clinically relevant is the validity of using diagnostic scales that are considered best practices for ASD or ADHD to diagnose comorbidities be- tween disorders. Although 40–70% of individuals with ASD have clinically significant ADHD symptoms [1922], and 20– 60% of those with ADHD experience social impairments sim- ilar to those reported in ASD [44], the diagnoses could not, prior to this iteration of the DSM, be provided comorbidly. This recent change has prompted a closer examination of inat- tention, hyperactivity/impulsivity, and social function in these two diagnoses, but several complications have arisen.

The most diagnostically relevant of these is that although individuals with ASD may indeed meet the diagnostic criteria for ADHD as outlined in the DSM-5, the presence or absence of specific symptoms is usually based on parent (and teacher) reports. It is unclear, however, whether parent and teacher reports of symptom endorsement truly represents the presence of both disorders in an individual, which disorder parents are attributing specific symptoms to, as well as whether the con- structs measured on ADHD scales measure the same con- structs among those with ASD and vice versa. For example, the use of a popular ADHD symptom measure, the ADHD Rating Scale-IV failed to separate inattention and hyperactivity/impulsivity in ASD in a sample of 386 youth with ASD (with normal intellectual function) [65]. The au- thors recommended that clinical interviewing follows the use of the ADHD Rating Scale-IV to separate ASD symptoms from hyperactivity/impulsivity and inattention [65].




Clinician report of psychiatric comorbidity diagnoses in ASD, especially ADHD, is lower than diagnoses generated by a structured parent interview. For example, mental health clini- cians reported that 36% of the youth with ASD that they were treating had comorbid ADHD compared to the 78% of these same youth who met diagnostic criteria based upon a structured interview with a parent [66]. No child characteristics predicted ADHD diagnostic agreement between clinician and parent.


ASD in ADHD Both the ADI-R and ADOS-2 have gone through extensive psychometric testing and have adequate sensitivity and specificity. Since ADHD could not be diag- nosed in individuals with ADHD, the validation samples of the ADI-R and ADOS-2 did not include participants with ADHD, and as such the discriminant validity of the instru- ments was not assessed. More recent work suggest that clini- cians need to be cautious when using the ADOS-2 and the ADI-R in individuals with ADHD [23]. Although few indi- viduals with ADHD (approximately 11%) met the diagnostic cutoff on both the ADOS-2 and the ADI, 21% of these chil- dren met cutoff on the ADOS-2, and 30% met on the basis of the ADI-R. Further, only four items on the ADOS-2 and only a single item on the ADI-R adequately differentiated between those with ADHD and those with ASD. These findings are troubling, even more so given that few clinicians are trained in either the ADOS-2 or the ADI-R, let alone both.

While not a gold standard ASD assessment tool, the Social Communication Questionnaire (SCQ) has been used to differ- entiate ASD from ADHD and ASD+ADHD. Both ASD groups had higher SCQ total and domain scores than youth with ADHD only. A cut score of 13 on the SCQ differentiated between ADHD and ASD [67]. The Autism Mental Status Examination (AMSE) has demonstrated adequate abilities to detect ASD in children with ADHD. Using a cut score of 5 on the brief, clinician-rated instrument (which correlates highly r = .67 with the ADOS-2) resulted in sensitivity (.83) and specificity (.90) for detecting ASD in youth with ADHD [68].


ASD+ADHD Three separate pathways explaining the comor- bidity between ADHD and ASD have been demonstrated using structural equation modeling. These pathways are from impulsivity to social information processing difficulties, from hyperactivity to restricted and repetitive behaviors and a pairwise pathway between inattention, verbal IQ, and social information processing difficulties [69].

A latent class analysis study reported that 77.5% of a com- bined clinical and population-based sample could be placed into a concordant category (low ASD, low ADHD; 10.1%), (medium ASD, medium ADHD; 54.2%), and (high ASD, high ADHD; 13.2%). Conversely, two discordant classes emerged, one with higher scores on the ADHD traits (ADHD > ASD; 18.3%), and one with higher scores on the ASD trait (ASD > ADHD; 4.2%) [70]. These data and others

have led some to opine that it is not possible to determine if ADHD symptoms in ASD represent ASD, comorbid ADHD, or a separate condition entirely [71]. At this point, clinical judgment remains the deciding factor in determining which diagnosis is/are the most appropriate for a given individual.

The base rate of ADHD symptoms for children, adoles- cents, and adults with ASD has never been firmly established. Without base rate data on ADHD symptoms in ASD, we still do not know which ADHD symptoms and thresholds may enhance the predictive and discriminant validity of our ADHD diagnostic instruments.



Treatment Considerations


There are well-researched and effective interventions that are available for both ASD and ADHD and vary according to the age of the child. For school-aged children with ASD, a focus on social, adaptive, and academic skills acquisition is recom- mended while in adulthood, the developmental of vocational and adaptive living skills becomes more integral to ASD man- agement [72]. For school-aged children with ADHD, organi- zational interventions and parent/teacher training in contin- gency management is recommended while in adolescents and adults, the use of cognitive behavioral treatment is effec- tive [73]. While no medications are FDA-approved for treating the core symptoms of ASD, the use of stimulants, atomoxetine, and alpha-2 agonist medications has FDA ap- proval for managing ADHD [74]. Thus, there exists a wide range of effective treatment options for individuals with ASD and ADHD.

Despite these evidence-based options, we know far less about what constitutes an effective intervention for individuals with ASD+ADHD. This is surprising given the significant overlap between the two conditions as well as the increased impairment associated with the comorbid condition. The pres- ence of ADHD in ASD is associated with increased ASD severity and a significantly increased risk for a third condition, especially anxiety and mood disorders [75]. Likewise, in- creasing ADHD severity, yet not increasing ASD severity, is associated with the number of additional comorbid psychiatric diagnoses in children with ASD [76••]. Below, we review what has been recently published about treating the comorbid condition, ASD+ADHD.


Pharmacological Eighty-six percent of youth with ASD+ ADHD have been prescribed a medication for ADHD symp- toms [77]. The presence of ADHD increases the risk for poly- pharmacy in ASD, an outcome observed in roughly one in four individuals with ASD treated with medications [78]. Psychiatrically referred youth with ASD often receive poly- pharmacy regimens (mean number of psychotropic medica- tions = 3 ± 1.5) [79]. Other population-based data have




indicated that psychotropic medication use (especially stimu- lants) in ASD occurs in just under 70% of the ASD population (40% are prescribed two or more psychotropic medications concurrently) and poly-pharmacy is associated strongly with age [80]. Over 85% of prescribers treating youth with ASD+ ADHD routinely prescribed psychotropic medications for their patients. The most common target for psychotropic med- ication was aggression reduction with hyperactivity- impulsivity being second most frequently targeted [81].

The British Association for Psychopharmacology consen- sus guidelines do not recommend routine use of medications for managing core ASD symptoms. However, the group rec- ommended the use of methylphenidate, atomoxetine, and guanfacine (in that order) for ADHD management in individ- uals with ASD [82]. A Cochrane review similarly concluded that methylphenidate reduces hyperactivity-impulsivity symp- toms in youth with ASD (less robustly impacting inattention) yet has no impact upon core ASD symptoms [24•]. Compared to those prescribed a low dose, those prescribed a medium dose demonstrate more clinically significant improvements in ADHD symptoms [83].

While effective for managing ADHD symptoms in ASD, a meta-analysis [84] reported effect sizes associated with meth- ylphenidate in ASD (ES = .67) are lower than those reported for treating ADHD (without ASD) (ES = 1.03) [85]. Moreover, methylphenidate is associated with higher rates of side effects such as social withdrawal, depression, and irrita- bility when used in ASD [84]. Nonetheless, stimulants such as methylphenidate remain the front-line intervention for manag- ing ADHD symptoms in ASD.

While the stimulants are recommended as a front-line phar- macological therapy for ADHD in ASD, atomoxetine and guanfacine also have demonstrated efficacy. For example, in individuals with ASD and an intellectual disability, atomoxetine was efficacious for reducing ADHD symptoms in 43% of the children [86]. Atomoxetine is sleep neutral in youth with ASD, neither negatively nor positively impacting parent-reported sleep levels in their child [87]. An 8-week trial of extended-release guanfacine in youth with ASD+ADHD resulted in significant reductions in parent-reported oppositional behaviors compared to placebo. Nonetheless, no differences were found between the placebo and extended-release guanfacine groups for parent- reported anxiety and sleep problems [88].


Non-pharmacological While some data suggest that the addi- tion of a psychosocial intervention to medication treatment does not add incremental benefit [89], most professional prac- tice parameters recommend a combination of medication and psychosocial interventions for managing ADHD in the con- text of ASD (see Clinical Practice Pathways for Evaluation and Medication Choice for ADHD symptoms in ASD [90]). Likewise, in addition to the use of medication, the British Association for Psychopharmacology consensus guidelines

recommended social communication interventions for chil- dren and adolescents with ASD and social skills training for adolescents with ASD [82]. While efficacious in ASD [51], social skills training has not proven efficacious or effective in children and adolescents with ADHD [91]. Similarly, the ef- fects of parent training in children with ASD is moderated by the presence of ADHD with effects being observed more read- ily in children without ADHD [92]. Thus, it remains unclear the extent to which these ASD evidence-based interventions are efficacious in individuals with ASD+ADHD.


Future Treatment Directions Unlike depression and anxiety, digital health interventions (e.g., computer-assisted therapy, smartphone apps) are largely ineffective for ADHD and ASD [93]. Conversely, exercise has small to moderate effects on several aspects of cognition in individuals with ADHD and ASD, especially simple learning tasks and response inhibition; approximately 62% of individuals with ADHD and ASD re- spond favorably to exercise interventions [94]. Others have concluded that dietary inventions such as food additive exclu- sion diet, gluten-free/casein-free diet, and oligoantigenic diet are worthwhile to investigate and proposed microbiome–gut– brain axis as the putative mechanism [95]. Future research should continue to investigate dietary, exercise, and digital health interventions.

The presence of ASD symptoms in children with ADHD is associated with negative impacts upon the family quality of life including more negative emotional impacts and impacts upon the family and time. Parents of youth with ADHD and elevated ASD symptoms reported lower parenting self- efficacy than parents of youth with ADHD alone [96]. Similarly, a large population-based study in Denmark reported that having a child with ADHD, ASD+ADHD, and to a lesser


Table 1 Suggested future research directions


  1. How best to support the transition to adulthood
  2. Including stakeholders more centrally in research topics
  3. Analyzing moderators and mediators of treatment outcomes for ASD+ ADHD
  4. Girls with ASD, ADHD, and ASD+ADHD
  5. Understanding subthreshold manifestations of ASD and ADHD
  6. Understanding the sensory features in ASD and ADHD
  7. Understanding developmental changes and trajectories underlying both phenotypes
  8. Research Domain Criteria (RDoC) initiatives and dimensionality of ASD and ADHD
  9. Early identification and intervention
  10. Improving ecologically valid assessment (use of ecological momentary assessments)
  11. Integrating technology into intervention designs


ASD autism spectrum disorder, ADHD attention deficit/hyperactivity disorder




Table 2 Frameworks for understanding ASD and ADHD comorbidity

Model                                                                                                     Support    Recent citations


Comorbid ASD and ADHD is due to chance (random)                             –               [1622, 27, 28••]

Comorbid ASD and ADHD reflects sampling biases                                 –               [16, 18, 20, 28••] One syndrome is an early manifestation of the other (precursor)                                                                                     –               [16, 17, 27, 28••]


ASD and ADHD are not distinct entities but represent phenotypic variability of the same disorder (lumper)

ASD and ADHD share common vulnerabilities (e.g., genotype, environmental) (multifinality)

~               [43, 52, 53]


~               [3136, 37•, 103]


ASD and ADHD are distinct and separate entities (splitter)                        +               [914, 43, 52, 53, 56,

60, 103]


Comorbid ASD and ADHD represents a distinct subtype within a heterogeneous disorder (subgroup)

Development of one syndrome increases the risk for the other (potentiation)

+               [6971]


+               [2527, 28••, 44]



ASD autism spectrum disorder, ADHD attention deficit/hyperactivity disorder. Support levels (-, no support; ~, some support; +, support)



extent ASD is associated with increased risk for parental separation/divorce compared to typically developing children. By the age of 11, 50% of the ADHD families had separated, compared with 37% of ASD families and 25% of control families. Most marital dissolutions occurred when the proband was between ages 3 and 5 years old [97]. In children with ASD, having an older sibling is associated with a lower risk for ADHD, anxiety, and depression [98]. All of the above suggest that while family-level interventions have not been investigated in ASD+ADHD, it seems important to consider the family unit as a mechanism of change.

A large Medicaid claims study reported that significantly higher percentage of children with ASD (52%) received school-based mental health services compared to children with ADHD (8%) [99]. Nonetheless, children with ASD are perceived by their parents to have greater unmet occupational, physical, and speech therapy service needs than those with ADHD [100]. Future research should continue to investigate school-based interventions. (Please see Table 1 for additional research considerations which seem important to pursue in the next several years.)





There are a variety of models that have been developed to explain the comorbidity of psychiatric disorders [101]. (Please see Table 2 for a list of several explanatory models and our opinions about how comorbid ASD and ADHD might be understood within each framework.) At this time, we be- lieve that the accumulated knowledge base suggests that ASD and ADHD are related conditions yet sufficiently distinct to be considered separate disorders. Using an analogy, we consider ASD and ADHD to be “cousins” to each other, possibly even siblings. However, we do not believe that ASD and ADHD should be considered twins.

The comorbid state represents an “additive” profile of two conditions in our view. There are both quantitative and qual- itative differences between the two conditions. Nonetheless, we agree with the call to investigate transdiagnostic, more dimensional considerations which might explain the etiologi- cal overlap and shared impairments and outcomes [102]. As indexed in Fig. 1, research interest in ASD, ADHD, and ASD+ADHD has grown exponentially over the past 20 years. We know far more about both ASD and ADHD yet continue to know less about the comorbid condition. Increases in prev- alence for both conditions suggest that understanding the co- morbid state will be a particularly important agenda for future researchers and clinicians.


Compliance with Ethical Standards


Conflict of Interest Kevin M. Antshel reports a grant from Shire Pharmaceutical Company and personal fees from Arbor Pharmaceutical Company. Natalie Russo declares no potential conflicts of interest.


Human and Animal Rights and Informed Consent This article does not contain any studies with human or animal subjects performed by any of the authors.






Papers of particular interest, published recently, have been highlighted as:

  • Of importance
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Within an inclusive education system, the learner with a diagnosis of ADHD is educated in the least restrictive environment, along with typically developing peers.
The South African Schools Act of 1996 states that schools must admit learners and serve their educational requirements without unfairly discriminating in any way.
The Constitution of South Africa guarantees everyone the right to basic education. Accommodating children with severe disabilities through an inclusive education framework is constitutionally mandated.
Inclusive Education is also discussed in Education White Paper 6. The aim of this paper was to dismantle separate special education systems and promote access and participation in regular classes for children with ADHD, disabilities, or other special needs.
Children with ADHD or special learning needs, have a legal right to be included in mainstream school irrespective of any physical or intellectual disability. When a child with ADHD is ready for a school placement there should be no hesitation to demand access to a mainstream school.
Over the last decade, Catch up Kids has partnered with numerous mainstream schools, to make inclusive education possible and successful. Our trained facilitators, support learners with ADHD in the mainstream classroom, drawing on the principles of Applied Behaviour Analysis. Giving children with a learning difference access to a typical classroom environment is integral to their long-term success.
All we need is teachers who are open-minded and willing to partner with us to secure true inclusive education.

Journal of Attention Disorders OnlineFirst, published on April 20, 2009 as doi:10.1177/1087054708326261

Attention Deficit/Hyperactivity Disorder in Children and Adolescents With Autism Spectrum Disorder

Symptom or Syndrome?

Judith Sinzig Daniel Walter Manfred Doepfner University of Cologne

Journal of Attention Disorders Volume XX Number X Month XXXX xx-xx

© 2009 SAGE Publications 10.1177/1087054708326261

hosted at

Objective: This study aims to evaluate ADHD-like symptoms in children with autism spectrum disorder (ASD) based on single-item analysis, as well as the comparison of two ASD subsamples of children with ADHD (ASD+) and without ADHD (ASD-). Methods: Participants are 83 children with ASD. Dimensional and categorical aspects of ADHD are evaluated using a diagnostic symptom checklist according to DSM-IV. Results: Of the sample, 53% fulfill DSM-IV criteria for ADHD. The comparison of the ASD+ and the ASD- samples reveals differences in age and IQ. Correlations of ADHD and PDD show sig- nificant results for symptoms of hyperactivity with impairment in communication and for inattention with stereotyped behav- ior. Item profiles of ADHD symptoms in the ASD+ sample are similar to those in a pure ADHD sample. Conclusion: The results of our study reveal a high phenotypical overlap between ASD and ADHD. The two identified subtypes, inattentive- stereotyped and hyperactive-communication impaired, reflect the DSM classification and may theoretically be a sign of two different neurochemical pathways, a dopaminergic and a serotonergic. J. of Att. Dis. XXXX; XX(X) xx-xx)


Keywords: ADHD; Asperger syndrome; autism; comorbidity; diagnosis


Although autism spectrum disorders (ASD) can be accompanied by increased inattention, hyperactivity, and impulsivity, the diagnosis of ADHD continues to remain in the exclusionary criteria for pervasive devel- opmental disorder (PDD) (APA, 2000). Currently, shared candidate regions as well as overlaps in neu- roimaging studies, in particular with regard to cerebellar and frontostriatal structures, are being discussed for ADHD and for ASD (Bakker et al., 2003; Brieber et al., 2007; Ogdie et al., 2003). Neuropsychological examina- tions comparing both groups show similar results espe- cially with regard to performance in inhibition tasks (Geurts, Verte, Oosterlaan, Roeyers, & Sergeant, 2004; Goldberg et al., 2005; Happé, Booth, Charlton, & Hughes, 2006; Ozonoff & Jensen, 1999; Sinzig, Morsch, Bruning, Schmidt, & Lehmkuhl, 2008).

The coexistence of ADHD symptoms and ASD was described as early as the 70s and 80s (Campbell et al., 1972; Geller et al., 1981). In an early investigation by

Gillberg (1989), 21% of the children and adolescents with ASD were found to meet both the diagnostic crite- ria for an ADHD and an Asperger syndrome, and autis- tic traits were apparent in 36%. In 1997, Wozniak and Biederman reported that 74% of an ASD sample showed ADHD symptoms. Ghaziuddin, Weidmer-Mikhail, and Ghaziuddin (1998) described that children with Asperger syndrome most likely suffer from ADHD whereas depression was the most common diagnosis in adoles- cents and adults. Frazier et al. (2001) suggested in a com- parative analysis that the two syndromes be considered independent of each other. They further demonstrated that the comorbid presentation of ADHD with ASD (83% in their study) led to higher rates of hospitalization,


Authors’ Note: Address correspondence to Dr. Judith Sinzig, Clinic for Child and Adolescent Psychiatry, University of Cologne, Robert- Koch-Str. 10, 50931 Cologne, Germany. Phone: ++49 221 478 4370;

fax: ++49 221 478 6104; e-mail:


2 Journal of Attention Disorders


Table 1

Results of Recent Systematic Studies of ADHD Symptoms in Autistic Populations


Goldstein et al. (2004) (n = 27)Yoshida et al. (2004) (n = 53)Gadow et al. (2006) (n = 483)Lee et al. (2006) (n = 83)
No. (%)
– male?4839866
– female?58517
ASD diagnosis
– Autistic disorder9 (24.3)
– High-Functioning syndrome33 (62.2)170 (35.0)58 (70.0)
– Asperger-Syndrome3 (5.6)104 (21.5)12 (14.0)
– PDD-NOS28 (75.6)17 (32.0)209 (43.2)13 (16.0)
ADHD diagnosis

ASD Total sample/ ASD + sample (in%)

16 (59)36 (68)251 (52)54 (65)
– 0 Combined subtype26/4423/3316/3149/63
– 1 Inattentive only subtype33/5638/5629/5623/29
– 2 Hyperactive/Impulsive subtype8/116/126/8

Age at testing (years)











86.1 (?)87.3 (>70)83.5 (?)?


medication treatment, and combined psychotherapy. More recently, a study by Holtmann, Bolte, and Poustka (2007) found that 65% of children and adolescents with high functioning autism (HFA) or Asperger syndrome scored above the clinical cutoff on attention problems scale of the Child Behavior Checklist. ADHD subtypes in ASD were first specified by Yoshida and Uchiyama (2004). In their study, 68% of children with an autistic disorder, either Asperger syndrome or pervasive devel- opmental disorder not otherwise specified (PDDNOS), met the diagnostic criteria for ADHD subtypes. These numbers are in line with results by Goldstein and Schwebach (2004) who found in a retrospective chart review that in a sample of children with autism or PDDNOS, 59% of the children suffered from ADHD. These results were recently confirmed by Gadow et al. (2006) who described almost equal ADHD subtypes for children with PDDNOS. Categorical aspects of ADHD diagnosis have also been reported in 2006 in a chart review of 83 children with ASD, where 78% fulfilled DSM-IV criteria for ADHD and exceeded the 93rd per- centile norm for the ADHD rating scale (Lee & Ousley, 2006). Table 1 summarizes the results of recent system- atic studies of ADHD symptoms in autistic populations. In total, the reported studies show that children with ASD may display a significant degree of ADHD-like symptoms as well as ADHD subtypes. Because there is considerable controversy concerning the diagnosis of

ADHD in children with ASD (Ghaziuddin, 1998; Perry, 1998; Tsai, 1996), especially ADHD symptoms being “true” ADHD or part of the ASD diathesis, we decided to look separately at both types of children, those with a categorical diagnosis of ADHD and those without.

As previous studies dealing with the prevalence of ADHD in ASD used rather heterogeneous samples con- cerning gender, age, ASD diagnosis, and IQ, we wanted to assess the association of these variables with the severity of ADHD symptomatology within the ASD sample affected by ADHD symptoms.

Associations of ADHD with PDD-symptoms had also never been investigated before. This is an important topic as one might assume that an autistic child is, for example, inattentive because that is a stereotypical behavior.

Until now, little attention has been given to investigate the detailed description of ADHD-like symptoms in ASD children based on single-item profiles. This was done only by Clark, Feehan, Tinline, and Vostanis (1999) the other way around in a sample of children with ADHD and comorbid autistic symptoms.

In summary, the objectives of our study were fourfold:

(a) to compare an ASD sample with a categorical diagno- sis of ADHD and one without such a diagnosis; (b) to assess the associations of gender, ASD diagnosis, age, and IQ with ADHD severity; (c) to investigate associations of ADHD with PDD symptoms; and (d) to perform a single- item analysis of ADHD symptoms in an ASD sample.


Sinzig et al. / Profile of ADHD-Like Symptoms in Autism 3

Because previous studies have described almost equal numbers for ADHD prevalence in ASD samples, we hypothesize that ADHD displays a genuine diagnosis in ASD. Therefore, we expected no differences between the two samples except for gender, as the ratio between males and females with ADHD diagnosis is approxi- mately 3:1 (Szatmari, Offord, & Boyle, 1989). We also hypothesized that boys would be more severely impaired. Furthermore, we expected children with an autistic disorder and a lower IQ would show more hyper- activity symptoms whereas those with HFA or Asperger syndrome would be more inattentive. With regard to the 4th part of our study, we hypothesized that ASD children would have similar ADHD item profiles comprising the factors of hyperactivity, impulsivity, and inattention. Even though two factors describing inattention and hyperactivity-impulsivity according to DSM-IV classifi- cation were extracted in exploratory factor analysis of parent ratings of field samples of children with pure ADHD (Doepfner et al., 2006), we explicitly decided to use a 3-factor solution as we wanted to gain specific information about each subscale.


Child and Adolescent Psychiatric Assessments

All dependent measures are components of the Diagnostic System for Mental Disorders in Childhood and Adolescence (DISYPS-2) based on ICD-10 and DSM-IV components.


Diagnostic Checklist for Attention Deficit/ Hyperactivity Disorder (Diagnostik Checkliste für Aufmerksamkeitsdefizit-/Hyperaktivitätsstörung, DCL-ADHD); ADHD rating scale for teachers and for parents (Fremdbeurteilungsbogen für Aufmerksamkeitsdefizit-/Hyperaktivitätsstörung, FBB-ADHD). The DCL-ADHD and the FBB-

ADHD provide the number of DSM-IV and ICD-10 criteria. The severity score for each item ranges from 0 to 3 (see also Herpertz et al., 2001; Konrad, Gunther, Hanisch, & Herpertz-Dahlman, 2004). It consists of 20 items describing the symptom criteria of ICD-10 and DSM-IV. The internal consistencies (Cronbach’s alpha) for the parent rating versions are from á=.78 to á=.93. Similar rating scales have been developed in the United States, based solely on DSM-IV criteria for ADHD (DuPaul, Ervin, Hook, & McGoey, 1998).

Diagnostic Checklist for Pervasive Developmental Disorders (Diagnostik Checkliste fr Tiefgreifende

Entwicklungsstörungen, DCL-TES); PDD-rating scale for teachers and for parents (Fremdbeurtei- lungsbogen für Tiefgreifende Entwicklungs- störungen, FBB-TES). The DCL-PDD and the FBB-PDD are also part of the Diagnostic System for Mental Disorders in Childhood and Adolescence (DISYPS-2). Both rating scales cover all DSM-IV criteria for autistic disorders. The 14 items are scored on a 4-point scale. The checklist was mainly used to exclude PDD in the ADHD children and to differentiate between HFA and Asperger syndrome within the ASD group.

Diagnostic Checklist for Oppositional Defiant or Conduct Disorders (Diagnostik Checkliste für Störungen des Sozialverhaltens, DCL-SSV); ODD/CD rating scale for teachers and parents (Fremdbeurteilungsbogen für Störungen des Sozialverhaltens, FBB-SSV). These rating scales are also part of the Diagnostic System for Mental Disorders in Childhood and Adolescence (DISYPS- 2). They contain the ODD and CD scales composed of the DSM-IV items. The rating scale has been proven to be reliable and valid in several psychome- tric studies (Doepfner et al., 2007). For the present study, only the first two parts of the checklist were used in assessing the symptoms of ODD (9 items, part A) as well as aggression toward people and ani- mals, and deceitfulness and theft (6 items, part B).


All three checklists/questionnaires allow the assessment of a dimensional score and a categorical diagnosis. The scores for ASD+ and ASD- are illustrated separately in Figure 1.

Selection and Sample Description

From all outpatients presented at the Department for Child and Adolescent Psychiatry of the University of Cologne, we consecutively selected individuals with known ASD. Parents were asked to complete rating scales. Rating scales included ADHD, PDD, and ODD/CD rating scales for parents. In addition, ADHD symptoms within each child were observed and reported on by a child and adolescent psychiatrist during explo- ration of the parents and the child. The presence or absence of an ADHD diagnosis according to DSM-IV criteria was determined by the Diagnostic Checklist for ADHD, which is part of the Diagnostic System for Mental Disorders in Childhood and Adolescence (DISYPS-2, Doepfner et al., 2007).The checklist was used in a diagnostic interview with parents and teachers. The diagnosis of autistic disorder was clarified using the


4 Journal of Attention Disorders

Figure 1

Mean Subscale and Total Score of ADHD-Symptoms (FBB-ADHD, DISYPS-2) for the two Different Clinical Groups



ADHD symptom checklist


Autism Diagnostic Interview-Revised (ADI-R, German translation: Boelte et al., 2006) and the Autism Diagnostic Observation Scale (ADOS, German translation: Ruehl, Boelte, Feineis-Matthews, & Poustka, 2004).

In total, 83 patients with ASD were selected. The sam- ple comprised boys and girls with a diagnosis of either an autistic disorder (n=9; 10.8%), HFA (n=30; 36.1%) or an Asperger syndrome (n=44; 53.1%).

Of the autistic participants, 44 (53%) demonstrated a sufficient number of ADHD symptoms to warrant a comorbid diagnosis of ADHD according to the DSM-IV. In the following, the ASD group with ADHD is referred to as ASD+ and the group without ADHD as ASD-. Overall, 25 (30.1%) of the total sample had a comorbid diagnosis of oppositional defiant disorder (ODD), and 26 partici- pants (31.3%) were treated with medication (methylphenidate, 50%; risperidone, 35.7%; SSRI, 7.2%; anticonvulsants, 7.2%). Parents and teachers were asked to make their ratings on an off-medication basis. Additionally, age, IQ, and gender were recorded based on the patients’ charts. Table 2 summarizes the clinical and demographic features of the total sample of the ASD chil- dren divided into ADHD and non-ADHD participants.


Statistical Analysis

Chi-square tests (categorical variables) and ANOVAs (continuous variables) were used for group comparisons between the ASD+ and the ASD-.

Based on the ASD+ sample, the following analyses were conducted:


Descriptive statistics (means and standard deviations) for the subscales inattention, hyperactivity, and impulsivity of the symptom checklists separated for gender, type of ASD diagnosis, age, and IQ were calculated. To evaluate the impact of these four vari- ables on ADHD scores, a MANOVA was applied.

For precise examination of the relationship between PDD and ADHD symptoms, additional Pearson product-moment correlations were applied for mean scores of impairment of social interaction/ communication, mean stereotype behavior; mean PDD total score from the PDD symptom checklist, and mean ADHD total score; mean hyperactivity score, mean inattention score as well as mean impulsivity score from the ADHD symptom check- list (DISYPS-2). Additionally, Pearson correlations were applied for mean scores of ADHD and PDD single items and vice versa.

An explorative factor analysis (varimax rotation) with three factors, comprising the items of the ADHD symptom scale for the ASD + sample were applied.

All tests are based on a significance level of p<0.05.



Comparison: ASD+ Versus ASD- Samples

The comparison of the ASD+ and the ASD- samples applying a MANOVA with group as the between-subject factor revealed significant group differences for age (F=21.73, p<.000), IQ (F=5.97, p=.01), medication (F=15.17, p<.000) and, as expected, for all scores of the ADHD symptom scale (inattention: F=19.72, p<.000; hyperactivity: F=11.36, p=.001; impulsivity: F=7.65, p=.007, total score: F=25.12, p<.000). Children in the ASD+ sample had a lower mean age and IQ and took med- ication more often. There were no significant differences for gender: F=0.28, p=.59; type of ASD diagnosis: F=2.65, p=.11. These results are also seen as part of Table 2. Table 3 summarizes the group comparison of the ADHD total score for gender, type of ASD diagnosis, age-groups, and IQ-groups separated for the two samples ASD+ and ASD-.


Impact of Gender, Type of ASD

Diagnosis, Age, and IQ on ADHD-Symptoms in the ASD+ Sample

Neither the variable gender (F=0.02; p=.88), type of ASD diagnosis (F=1.97; p=.15), age (F=0.94; p=.54),


Sinzig et al. / Profile of ADHD-Like Symptoms in Autism 5


Table 2

Clinical and Demographic Features of the Total, the ADHD, and the Non-ADHD Sample


Total (n = 83)ADHD (n = 44)Non-ADHD (n = 39)EffectGroupEffect
No (%)




p 0.76a 


– male70 (84.4)38 (86.4)32 (82.1)
– female13 (15.6)6 (13.4)7 (17.9)
ASD diagnosis
– Autistic disorder9 (10.8)8 (18.2)1 (2.6)0.070.05bn.s.
– High-Functioning autism30 (36.1)15 (34.1)15 (38.5)
– Asperger-Syndrome44 (33.7)21 (47.7)23 (59.0)
ADHD diagnosis53%100%
– Combined subtype14 (16.8)14 (31.8)–                              –                  –                  –
– Predominantly Inattentive subtype20 (24.1)20 (45.5)
– Hyperactive/Impulsive subtype10 (12.1)10 (22.7)
Comorbid ODD yes25 (30.1)15 (34.1)10 (25.6)0.414.76an.s.
Mean (SD)

Age at testing (years)


11.7 (3.3)


10.2 (2.8)


13.3 (3.1)







Min-Max(5.0 -17.9)(5.0-17.9)(7.0-17.9)
IQ96.1 (19.1)91.3 (17.2)101.3 (19.9)5.97.01NA>A

Note: n.s. = Not significant; a Fisher’s exact test, b. Likelihood quotient; ADHD = attention-deficit/hyperactivity disorder; A= ADHD-sample, NA=non-ADHD sample, ODD = oppositional defiant disorder.

nor IQ (F=10.86; p=.63) had an impact on the severity of ADHD total score. However, with regard to ADHD sub- scales, an ANOVA with post hoc Scheffé tests revealed a significant result for hyperactivity with type of ASD

diagnosis (F=5.53; p=.007), with differences between the variable “autistic disorder” and “HFA” (p=.02) as well as Asperger syndrome (p=.01).


Association of PDD and ADHD Symptom Scores in the ASD + Sample

Results revealed only one significant correlation for mean hyperactivity and mean impairment of communication (r=0.4; p=.01).

The correlation of mean PDD scores and single ADHD symptoms showed significant results for “qualitative impairments in communication” and single hyper- activity items as “often fidgets with hands or feet or squirms in seat” (r=0.4; p=005), “often gets up from seat when remaining in seat is expected” (r=0.4; p=01), “often runs about or climbs when and where it is not appropriate” (r=0.5; p<000). Significant results were also seen for mean stereotyped behavior and inattention items such as “often does not seem to listen when spoken to directly” (r=0.3; p=.02) and “often loses things needed for tasks and activities” (r=0.3; p=.03); and for mean total score PDD and items of all three ADHD subscales.


Item Profiles of ADHD Symptoms in the ASD+ Sample

To identify potential item profiles of ADHD symptoms within the autistic children having an ADHD diagnosis,


6 Journal of Attention Disorders


Table 4

Factor Analysis for Items of ADHD Symptom Checklist (ASD+ Sample)


Factors with variables123
(Eigenvalues and percentages)6.4492.6282.004
32.25 %13.13 %10.02 %
Factor 1 – Hyperactivity
Fidgeting with hands or squirming in seat0.801
Gets up when remaining is expected0.716
Trouble playing quietly0.767
Often runs or climbs0.780
Often “on the go”0.799
Factor 2 – Impulsivity/Inattention Blurts out answers 


Interrupts others0.802
Often talks excessively0.656
Often loses things0.739
Easily distracted0.370
Often forgetful0.3880.588
Factor 3 – Inattention
No close attention to details0.435
Trouble keeping attention0.752
Does not follow instructions0.2980.325
Trouble organizing activities0.596
Avoids things that take a lot of mental effort0.806


an explorative factor analysis with three factors was per- formed. Within an analysis of the ADHD symptom checklist, all three extracted factors had eigenvalues greater than 2 and explained almost 55% of the variance (Factor scores>.32-.86). Factor 1 (32.25%) comprises symptoms of hyperactivity; Factor 2 (13.13%) includes symptoms of impulsivity and inattention; and Factor 3 (10.02%) symptoms of inattention.

Table 4 lists all items of the different factors extracted in the factor analyses.



Of the autistic participants in our study, 53% demon- strated a sufficient number of ADHD symptoms to war- rant a comorbid diagnosis of ADHD according to the DSM-IV. Of these children, 46% met the diagnostic cri- teria for the inattentive type of ADHD, 32% met the cri- teria for the combined subtype, and 22% for the hyperactive/impulsive subtype. Therefore, our results are in line with previous studies describing rates between 54% and 68% for comorbid ADHD diagnosis and between 30% and 44% for the combined type in children with ASD. However, the rate of the inattentive type is lower, whereas the rate of the hyperactive/impulsive type is higher. A reason for that might be that in our sample, the ASD + group comprises almost 25% of children

younger than 8 years. Higher rates of the hyperac- tive/impulsive subtype in younger children were also found by Gadow et al. (2006), Lee and Ousley (2006), and Yoshida and Uchiyama (2004).

Systematic studies investigating ADHD symptoms in samples with PDD (Gadow, DeVincent, Pmoeroy, & Azizian, 2004; Goldstein & Schwebach, 2004; Yoshida & Uchiyama, 2004) did not compare sample characteris- tics and the severity of ADHD symptoms between chil- dren with and without ASD and a categorical ADHD diagnosis. Our results show that these two groups differ in the severity of either total and subscale ADHD scores. Interestingly, the children in the ASD group with an ADHD diagnosis were significantly younger, with chil- dren between 5 and 7 years presenting more symptoms of hyperactivity. Whereas 30% in the ASD+ group were younger than 8 years, almost 60% in the ASD- group were older than 13 years. However, inattention symptom scores did not change with age. Lee and Ousley (2006) also found, in a large study, significantly higher scores of hyperactivity in younger children of their sample and only a slight decrease of inattention symptoms with age. The phenomenon of decreasing hyperactivity and persis- tence of inattention problems with growing age is fur- thermore consistent with the broader ADHD literature involving clinical populations (Biedermann et al., 2000) and cross-sectional assessment (DuPaul et al., 1998). To replicate these consistencies, it is necessary to incorpo-


Sinzig et al. / Profile of ADHD-Like Symptoms in Autism 7

rate adolescents in studies assessing ADHD symptoms in ASD. Previous studies mostly included children not older than 12 years.

The comparison of the affected and non-affected sub- samples also revealed that ASD participants with ADHD had lower mean IQ. Nevertheless, IQ was not statistically associated with the severity of ADHD symptoms within these children. However, in the ASD+ sample, lower-func- tioning ASD children, in comparison with higher-func- tioning ASD children, had more hyperactivity problems. These findings are in line with a study by Lee et al. (2006) but are in contrast to previous studies dealing with the same topic. Incorporating cognitive assessment is highly important as ADHD symptoms can vary inversely with IQ (Rapport et al., 1999). Furthermore, when applying the ICD-10, the differential diagnosis “overactive disorder associated with mental retardation and stereotyped move- ments” (F 84.4) for a child with moderate to severe men- tal retardation (IQ below 50) who exhibits major problems in hyperactivity, inattention, and stereotyped behaviors, has to be considered. As in previous studies as well as in our study, the assessed samples were very heterogeneous concerning the ASD diagnosis. Therefore, it seems very favorable to refer to the full range of IQ when interpreting ADHD-like symptoms in ASD children.

A study by Dietz et al. (2007) found indications of both stability and change of IQ scores in preschool chil- dren with ASD and a catch-up of intellectual develop- ment in at least one third of the assessed sample. Interestingly, in our study, age was not correlated with IQ in the ASD+ sample but in the ASD- sample, which could mean that ADHD symptoms are neither an effect of the higher proportion of young nor the involvement of mentally disabled children in the ASD+ group. This was additionally emphasized by the result that age and IQ had no effect in an applied MANOVA.

The occurrence of ADHD symptoms in ASD children was not associated with gender or comorbid ODD. In contrast to that, Holtmann et al. (2007) found more delinquent symptoms for girls with ASD. Furthermore, girls have been described to be more severely impaired with regard to executive functioning (Nydén, Gillberg, Hjelmquist, & Heimann, 2000).

Interestingly, comorbid ODD/CD was not signifi- cantly higher in the ASD+ group compared with the ASD- group. Within this group, the severity of inatten- tion and impulsivity was only slightly increased. However, Leyfer et al. (2006) did not report such a high number (7%) of comorbid ODD. These inconsistent findings underscore the necessity of systematically studying comorbid ODD and CD symptoms to get a broader understanding of overlapping symptoms in

ODD/CD and ADHD in ASD, as previously done by Leyfer et al. (2006) either under a dimensional or a cat- egorical aspect. However, evaluations in a larger sample would be helpful to draw any conclusion that ODD/CD is a relevant factor when comparing autistic children with and without ADHD.

The question as to whether PDD symptoms are associ- ated with ADHD symptoms and vice versa in autistic chil- dren with a categorical ADHD diagnosis revealed that PDD is more associated with ADHD than the other way around and reflects the fact that ADHD is more common in ASD (Clark et al., 1999; Santosh et al., 2004). Items of inattention are highly associated with stereotyped behavior. This might be because autistic children displaying high degrees of stereotypes cannot be attentive to other things. Pliszka, Carlson, and Swanson (2003), for example, state that it is not adequate to give an autistic child the diagnosis ADHD inattentive type. Furthermore, items of hyperactiv- ity were associated with mean scores of communication impairment. This finding is in line with results by Clark et al. (1999) who assessed autistic symptoms in children with ADHD. This underscores that hyperactive behavior seems to be predominant in children with language delay. However, hyperactive behavior is often difficult to differ- entiate from stereotyped movements.

The fact that within an ASD sample with comorbid ADHD symptoms the two subtypes (inatten- tive/stereotyped versus hyperactive/communication impaired) can be described leads to the hypothesis that these two subtypes may reflect two different neurochem- ical systems: (a) serotonergic + inattentive/stereotyped versus (b) dopaminergic + hyperactive/communication. Inattention and stereotypes are reported to be frequently associated with the serotonergic system (Cook et al., 1997; McDougle et al., 1997). The association of hyper- activity and the dopaminergic system was, for example, described by Gainetdinov et al. (1999). Pharmacological studies have shown that psychostimulants, elevating dopamine in the presynaptic cleft, and medications tar- geting the serotonergic system (i.e., serotonin-reuptake inhibitors and selective noradrenergic reuptake inhibitors; i.e., atomoxetine), are expected to afford some benefit to children with ASD (Hazell, 2007). However, response rates may be lower than those seen in children with pure ADHD, although the occurrence of adverse events seems to be higher in some children. Thus, it might be more important in ASD children to understand the type of predominant ADHD sub-sympto- matology to achieve better first-line treatments.

Basically, the findings also underline that the categorical DSM-diagnosis of ADHD inattentive and hyperactive/ impulsive type can be well described in ASD children.


8 Journal of Attention Disorders



Figure 2

Five-Group-Model on the Integration of the Disorders ADHD and ASD


Thus, a categorical approach in the controversy about ADHD in ASD is adequate.

The applied factor analysis clearly extracted three fac- tors describing the subscales inattention, hyperactivity, and impulsivity. This is in line with results of factor analysis performed with the same German rating scale in an ADHD sample (Görtz et al., 2007). This underlines the phenotypical overlap between the two disorders.



One limitation of the study is the unequal sample size with less participants with a lower-functioning autism and a higher rate of high-functioning children and ado- lescents. Furthermore, it should be noted that teacher rat- ings are not presented, which are, however, part of an ongoing study. A third problem is that more participants must be assessed to finally get reliable data of the corre- lations between PDD and ADHD symptoms and to be able to statistically integrate ODD and CD symptoms in the factorial analysis.



ASD and ADHD show a high phenotypical overlap. The results of our study reveal two subtypes, the inatten- tive-stereotyped and the hyperactive-communication impaired. These two subtypes reflect well the DSM clas- sification for ADHD and may theoretically hint at two different neurochemical pathways, a dopaminergic and a serotonergic, as also described for pure ADHD. The fact that children with ASD show lower response rates to

typical psychopharmacological treatments might be explained by five different groups that must be consid- ered in the discussion about ADHD and ASD, as shown in Figure 2. This five-group-model integrates ADHD and ASD as pure disorders without any comorbid symp- toms; ASD with a categorical diagnosis of ADHD; ADHD with ASD symptoms that do not reach the thresh- old for a categorical diagnosis; and an ASD group with symptoms as part of the autistic disorder itself, as an epiphenomena, for example, with increased stereotyped movements or behavior.

A very detailed examination of the child with ASD would help determine whether the reported ADHD-like symptoms support the notion of an ADHD behavioral syndrome or an increased rate of single behavior as stereotyped movements or excessive talking, to select appropriate treatment.



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10 Journal of Attention Disorders



Judith Sinzig, MD, specializes in child and adolescent psychia- try and works as assistant professor in the Department of Child and Adolescent Psychiatry at the University of Cologne. This study is part of her professorial thesis. Her research interests include neuropsychology and neuroimaging of ADHD and autism as well as the overlaps in childhood psychiatric disorders.


Daniel Walter, PhD, is currently a psychologist in the Department of Child and Adolescent Psychiatry at the


University of Cologne. His research interests include ADHD and cognitive behavioral  therapy  of school refusal.

Manfred Doepfner, PhD, is a professor of psychology in the Department of Child and Adolescent Psychiatry at the University of Cologne. Current research projects include epidemiology of ADHD and cognitive-behavioral therapy of childhood psychiatric disorders.


Published in final edited form as:

Autism Res. 2009 December ; 2(6): 322–333. doi:10.1002/aur.103.



Attention deficit/hyperactivity disorder symptoms moderate cognition and behavior in children with autism spectrum disorders

Benjamin E. Yerys1,2, Gregory L. Wallace3, Jennifer L. Sokoloff1,2, Devon A. Shook4, Joette D. James1,2, and Lauren Kenworthy1,2

1Children’s Research Institute – Neuroscience, Children’s National Medical Center, Washington, DC

2Center for Autism Spectrum Disorders – Children’s National Medical Center, Washington, DC 3Laboratory of Brain and Cognition – National Institute of Mental Health, Bethesda, MD 4Department of Psychology – Georgetown University, Washington, DC


Recent estimates suggest that over 30% of children with autism spectrum disorders (ASD) meet diagnostic criteria for attention deficit/hyperactivity disorder (ADHD), and another 20% of children with ASD exhibit subthreshold clinical ADHD symptoms. Presence of ADHD symptoms in the context of ASD could have a variety of effects on cognition, autistic traits, and adaptive/ maladaptive behaviors including: exacerbating core ASD impairments; adding unique impairments specific to ADHD; producing new problems unreported in ASD or ADHD; having no clear impact; or producing some combination of these scenarios. Children with ASD and co- morbid ADHD symptoms (ASD+ADHD; n=21), children with ASD without ADHD (ASD; n=28), and a typically developing control group (n=21) were included in the study; all groups were matched on age, gender-ratio, IQ, and socioeconomic status. Data were collected on verbal and spatial working memory, response inhibition, global executive control, autistic traits, adaptive functioning, and maladaptive behavior problems. In this sample, the presence of ADHD symptoms in ASD exacerbated impairments in executive control and adaptive behavior and resulted in higher autistic trait, and externalizing behavior ratings. ADHD symptoms were also associated with greater impairments on a lab measure of verbal working memory. These findings suggest that children with ASD+ADHD symptoms present with exacerbated impairments in some but not all domains of functioning relative to children with ASD, most notably in adaptive behavior and working memory. Therefore, ADHD may moderate the expression of components of the ASD cognitive and behavioral phenotype, but ASD+ADHD may not represent an etiologically distinct phenotype from ASD alone.

Autism spectrum disorders (ASD) and attention deficit hyperactivity disorders (ADHD) are diagnosed based upon behavioral symptoms (APA, 2000). ASD is characterized by impairments in social functioning, communication, and restricted, repetitive behaviors/ interests, while ADHD is characterized by inattention and hyperactivity/impulsivity.


Address Correspondence to: Benjamin E. Yerys, PhD, Children’s Research Institute – Neuroscience, Children’s National Medical Center, 111 Michigan Ave, NW, Washington, DC 20010, Phone: (202) 476-5358, Fax: (301) 765-5497. 2When spatial working memory data is combined for the ASD and ASD+ADHD groups and then compared to the TYP group we find a significant difference in total between errors, t(56)=2.81, p<0.05, Cohen’s d=0.61).

There are no conflicts of interest, financial or otherwise, for the remaining authors involved directly or indirectly with this manuscript.

Although the Diagnostic and Statistical Manual of Mental Disorders–Fourth Edition Text Revision (DSM-IV-TR; APA, 2000) precludes a co-morbid diagnosis of ASD and ADHD, a recent study examining co-morbidity revealed that over 30% of children with high- functioning ASD met diagnostic criteria for ADHD and an additional 25% of them exhibited elevated ADHD symptoms (Leyfer et al., 2006; see Bradley & Isaacs, 2006 for descriptions in a low-functioning adolescent sample). Additionally, research at the genetic (e.g., Smalley et al., 2002; Ogdie et al., 2003; Reiersen et al., 2007; Gadow, Roohi, DeVincent, & Hatchwell, 2008; Ronald et al., 2008), structural (Brieber et al., 2007) and functional (e.g., Durston et al., 2003; Schmitz et al., 2006) neuroanatomic levels of analysis suggest shared genetic risk loci and brain regions impacted in individuals with ASD and ADHD. Furthermore, similar associated behavioral features (e.g., executive control (EC) and aggression; Clark et al., 1999; Leyfer et al., 2006; Matsushima et al., 2008) indicate shared variance at the behavioral level.


This overlap raises the larger question of whether behavioral and cognitive phenotypes for children with ASD and clinically significant ADHD symptoms (hereafter referred to as ASD

+ADHD) differ from children with ASD without significant ADHD symptoms. Several studies have probed EC, autistic symptoms and traits, or other (non-social) maladaptive behaviors in low- and high-functioning children with ASD+ADHD and children with ASD alone (Luteijn et al., 2000; Matsushima et al., 2008; Sinzig et al., 2008a; 2008b; Gomarus et al., 2009). Adaptive functioning (i.e., independent skills in everyday settings) has not been investigated in an ASD+ADHD group. It remains unclear whether a homogeneous sample of high-functioning children with ASD+ADHD shares similar impairments (and to the same degree) as an ASD sample across multiple domains of functioning. In what follows, we summarize the current literature on EC, autistic symptoms and behaviors, adaptive, and other maladaptive behavior in children with ASD, ADHD, and ASD+ADHD.


Current evidence suggests EC impairments in ASD, ADHD, and ASD+ADHD groups, although meaningful differences may exist between the groups regarding the affected EC processes. Consistent findings in ASD include weaknesses on parent ratings of cognitive flexibility (with moderate support in performance measures; for review see, Geurts, Corbett, & Solomon, 2009), as well as planning, organization, and to a lesser extent spatial working memory, whereas inhibition and verbal working memory task performance are relatively intact (for review, see Hill, 2004; Kenworthy et al., 2008). Consistent findings for ADHD include impaired performance on tasks of response inhibition, vigilance, verbal and spatial working memory, and planning (for review, see Willcutt et al., 2005).


Studies directly comparing EC in ASD and ADHD (Ozonoff & Jensen, 1999; Gioia et al., 2002; Geurts et al., 2004; Goldberg et al., 2005; Tsuchyia et al., 2005; Happé et al., 2006; Johnson et al., 2007; Geurts et al., 2008; Gomarus et al., 2009; Corbett et al., 2009) reveal a fairly consistent ADHD-specific weakness in response inhibition (but see Johnson et al., 2007; Corbett et al., 2009) and spatial working memory deficits (but see Goldberg et al., 2005), and an ASD-specific EC weakness in flexibility (but see Goldberg et al., 2005; Tsuchyia et al., 2005). Two of three studies directly comparing EC processes in an ASD

+ADHD group versus an ASD group reveal a unique deficit in inhibitory control in ASD

+ADHD, but no differences in cognitive flexibility or working memory (Sinzig et al., 2008b; Goramus et al., 2009; but see Sinzig et al., 2008a).


Recent studies have examined the presence of autistic symptoms, defined as social and communicative impairments as well as restricted/repetitive behaviors and autistic traits in ADHD populations. We focus on autistic traits as measured dimensionally using the Social Responsiveness Scale (SRS; Constantino & Gruber, 2005). While several studies have validated the SRS as a measure of autistic traits in ASD samples (Constantino et al., 2000;


Constantino et al., 2003; Constantino et al., 2004), studies with ADHD samples have documented greater autistic traits than found in neurotypical populations (e.g., Reiersen et al., 2007). A handful of studies used the Childhood Social Behavior Questionnaire (CSBQ; Luteijn et al., 1998) to compare autistic symptoms measured dimensionally in ASD and ADHD samples. One study reported greater social and communication impairments for the ASD group based on broad domain CSBQ scores (Luteijn et al., 2000); while another reported group differences only on ASD-specific subscales (e.g., Reduced Social Contacts and Resistance to Change; Geurts et al., 2008). Taken together, these studies suggest that while individuals with ADHD do not meet diagnostic criteria for ASD, they exhibit elevated ASD traits/symptoms when using these dimensional measures. However, the symptoms may not be additive; similar ASD symptom (CSBQ) ratings were found for ASD+ADHD and ASD samples (Luteijn et al., 2000; Goramus et al., 2009).


Adaptive functioning is generally impaired in both ASD and ADHD, but individuals with ASD show more severe impairments. The large discrepancy between adaptive functioning and IQ is one of the most well established impairments in individuals with ASD (Volkmar et al., 1987; 1993; Carter et al., 1998; Constantino et al., 2004; Saulnier & Klin, 2008). Several cross-sectional studies in children and adults demonstrate impairments in all three domains of the Vineland Adaptive Behavior Scale (VABS) for high- and low-functioning individuals on the autism spectrum (Volkmar et al., 1987; 1993; Saulnier & Klin, 2008). In one study, VABS profiles correctly identified over 90% of individuals with ASD versus a developmentally-delayed group matched on age and IQ (Volkmar et al., 1993). Individuals with ADHD also exhibit reduced adaptive functioning relative to their own IQ and to typically developing matched controls (Barkley et al., 1990; Roizen et al., 1994; Stein et al., 1995; Happé et al., 2006; Stavro et al., 2007). The few studies examining both groups together show greater impairments for the ASD group (Stein et al., 1995; Happé et al., 2006). To date, no published study has examined adaptive functioning in an ASD+ADHD group relative to an ASD group.


Maladaptive behaviors are increased in high-functioning individuals with ASD and those with ADHD, but more often include internalizing behavior problems in ASD and externalizing behavior problems in ADHD. There are increased internalizing problems, and to a lesser degree, externalizing behavior problems, such as withdrawal, social problems, anxiety/depression, and thought disorders in high-functioning ASD groups (Sturm et al., 2004; Matsushima et al., 2008). Parent reports reveal significant externalizing, and to a lesser degree, internalizing, behavior problems, such as aggression, hyperactivity, and inattention in ADHD groups (Stein et al., 1995; Hudziak et al., 2004; Matsushima et al., 2008); however, many ADHD symptoms overlap with externalizing maladaptive behaviors, as well as symptoms of commonly associated co-morbid disorders (e.g., oppositional defiant disorder and conduct disorder) (Hudziak et al., 2004). The one study that examined a high- functioning group of children with ASD+ADHD1 reported increased externalizing behavior problems, aggression, delinquent behaviors, and thought problems in the ASD+ADHD group relative to an ASD group which exhibited subthreshold externalizing problems (Matsushima et al., 2008), suggesting that ADHD symptoms exacerbated externalizing problems in ASD. This study was limited, however, by a relatively small number of children in the ASD group (n=9).


1Matsushima and colleagues refer to their sample as “PDD” for Pervasive Developmental Disorders, however upon closer inspection of the sample (49/54 children recruited for the study received a diagnosis of autism) it appears that the PDD reference is akin to our use of “ASD” and not a specific diagnosis of pervasive developmental disorder – not otherwise specified. Therefore, we will refer to their sample as an ASD sample to reduce confusion.


In light of the evidence reported above for both continuities and discontinuities in the cognitive and behavioral profiles in ASD and ADHD, we examined whether the co- occurrence of ASD and ADHD symptoms marks a meaningful phenotype within ASD at the cognitive and behavioral levels. While some previous investigations are limited by small samples (e.g., Matsushima et al., 2008) or no information on cognitive functioning (Luteijn et al., 2000), the current study compares cognitive and behavioral profiles across several domains among children with ASD+ADHD, children with ASD, and typically developing controls (TYP) matched on age, IQ, gender ratio, and socioeconomic status. Based on the reviewed literature, we predict that in comparison to TYP, both ASD groups will exhibit similar difficulties in spatial working memory, cognitive flexibility, and internalizing behavior. We further expect that ASD+ADHD will exacerbate global EC deficits, autistic traits and symptoms, adaptive functioning deficits, and externalizing behavior, and produce new deficits in inhibition and verbal working memory.




Twenty-eight children with an ASD without elevated symptoms of ADHD (ASD); 21 children with an ASD and elevated symptoms of ADHD (ASD+ADHD); and 21 typically developing (TYP) children participated in the study. The first two groups were recruited through a hospital clinic specializing in ASD and neuropsychological assessment. Both clinical groups were diagnosed with a high-functioning ASD (ASD group: Autism n=13, Asperger’s Syndrome n=11, Pervasive Developmental Disorder-Not Otherwise Specified [PDD-NOS] n=4; ASD+ADHD: Autism n=9, Asperger’s Syndrome n=6, PDD-NOS n=6) using DSM-IV criteria (APA, 1994). All participants in the two clinical groups also qualified for a ‘broad ASD’ on the ADI/ADI-R (LeCouteur et al., 1989; Lord et al., 1994) and/or the ADOS (Lord et al., 1999) following the criteria established by the NICHD/ NIDCD Collaborative Programs for Excellence in Autism (Lainhart et al., 2006); all but four children received both diagnostic instruments. The broad ASD criteria include meeting the ADI cutoff for autism in the social domain and at least one other domain or meeting the ADOS cutoff for the combined social and communication score. In addition, all children in the ASD+ADHD group met criteria for either ADHD Combined Type or Predominantly Inattentive Type on the DSM-IV ADHD parent rating scale. Given their relevance to the domains assessed here, stimulant medications were withheld 36 hours prior to testing (ASD group n=5; ASD+ADHD group n=5). Children in the ASD group were taking the following other medications: selective serotonin reuptake inhibitors (n=2); antipsychotics (n=1) while children in the ASD+ADHD group were taking the following medications: selective serotonin reuptake inhibitors (n=2); antipsychotics (n=2). The TYP group was recruited from the community via advertisements. All participants were required to have a Full Scale IQ≥80 as measured by one of three Wechsler Intelligence scales (Wechsler Intelligence Scale for Children–3rd Edition, Wechsler Intelligence Scale for Children–4th Edition, Wechsler Abbreviated Scale of Intelligence; Wechsler 1991; 1999; 2003), which resulted in excluding four participants from the ASD+ADHD group (original n=25). We excluded participants in the clinical groups if they had any parent reported history of comorbid genetic or neurological disorders (e.g., Fragile X syndrome, Tourette’s syndrome). TYP participants were screened and excluded if they or a first-degree relative were found to have developmental, language, learning, neurological, or psychiatric disorders or psychiatric medication usage, which resulted in the exclusion of three participants (original n=24).

Groups did not differ in terms of age (F(2,67)=0.83, p=0.44), Hollingshead’s (1975) Four- Factor index for socioeconomic status (F(2,63)=0.39, p=0.68), gender ratio (χ2(n=70)=3.06, p=0.22), or IQ (F(2,66)=1.14, p=0.33; See Table 1)


Diagnostic Measures

Autism Diagnostic Interview/Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule (ADI/ADI-R; ADOS)—The ADI/ADI-R (LeCouteur et al., 1989; Lord et al., 1994) is a detailed parent or primary caregiver interview of developmental history and autism symptoms. Scores are aggregated into symptom clusters that correspond to DSM-IV criteria for a diagnosis of autism. The ADOS (Lord, et al., 1999) is a structured play and conversational interview that includes a series of social presses and other opportunities to elicit symptoms of an ASD.


Diagnostic and Statistical Manual of Mental Disorders-IV Attention Deficit Hyperactivity Disorder Rating Scale-Parent Edition (DSM-IV; ADHD rating scale)—The ADHD Rating Scale (DuPaul, Power, Anastopoulos, & Reid, 1998) assesses severity in inattention and hyperactivity/impulsivity symptoms. This 18-question scale yields two domains: inattention and hyperactivity/impulsivity. For each question, parents use a 0-3 scale to rate the participant. A higher score indicates more symptom severity, and a score of 2 or 3 is considered a significant symptom; six or more significant symptoms in either the inattention or hyperactivity/impulsivity domains meet criteria for an ADHD diagnosis.


Executive Control (EC)

Behavior Rating Inventory of Executive Functions–Parent Form (BRIEF)—The BRIEF (Gioia et al., 2000) is an informant report of EC in everyday situations comprised of eight scales which are collapsed into two broad indices: the Behavioral Regulation Index (BRI) and the Metacognition Index (MCI). Results are reported as T-scores. Higher scores indicate greater impairment; T-scores≥65 (i.e., 1.5 SDs≥the mean) indicate clinically significant ratings. Dependent variables include the two broad indices, as well as the Inhibition and Shift sub-scales.


Wechsler Intelligence Scale for Children-IV–Digit Span (DS)—DS (Wechsler, 2003) measures auditory attention and verbal working memory. Participants must repeat number sets back to the administrator in both forward and reverse order (i.e., backwards). Number sequences increase from two to nine digits as the task advances. Dependent variables include a standard score (mean=10, SD=3) of the child’s accuracy during forward administration, backwards administration, and a total score; however, the current study used the backwards standard scores as this allows isolation of manipulation (i.e., working memory) from short-term storage of information.


Spatial Working Memory–Cambridge Neuropsychological Tests Automated Battery—For Spatial Working Memory (Cambridge Cognition, 1996), children are initially presented with three boxes displayed on the computer screen. Children are then instructed to find a target (i.e., a blue token) hidden inside one of an array of boxes by using a touch- screen to search the boxes. The boxes are baited with a target one at a time, and once the target is found it does not appear in that location again. The task begins with three boxes and increases up to eight boxes, and the target is hidden in every location. The task does not move to the next level until all targets are found. Dependent variables include between errors, which are the total number of times a child returns to a previously baited location.


Walk Don’t Walk-Test of Everyday Attention for Children—Walk Don’t Walk (Manly et al., 1999) is a measure of sustained attention and pre-potent response inhibition. Respondents must attend to two auditory stimuli (i.e., beeps and beeps plus crashing noise); the former prompts respondents to mark the corresponding tile of a path, while the latter cues them to stop marking the corresponding tile of the path. To receive credit, children must correctly mark the number of beeps heard. The temporal interval between the auditory stimuli decreases as the task proceeds. The dependent variable is a scaled score (mean=10, SD=3) of accuracy across 20 trials.


Autistic Traits

Social Responsiveness Scale (SRS): The SRS (Constantino & Gruber, 2005) is a 65-item informant report of autistic traits rated on a 4-point Likert Scale (0 to 3 points). Higher scores indicate more autistic traits; T-scores≥65 (i.e., 1.5 SDs≥the mean) suggest clinically significant autistic traits. Based on factor analysis, these traits fall on a single dimension (Constantino & Gruber, 2005), so the SRS Total T-score was the dependent variable of interest.


Adaptive Functioning

Vineland Adaptive Behavior Scales–Interview Edition (VABS): The VABS–Interview Edition (Sparrow et al., 1984) is a standardized, structured parent interview of adaptive behaviors across the following domains: Communication, Daily Living Skills, and Socialization using standard scores (mean=100; SD=15), and the domains can be combined into an Adaptive Behavior Composite. Dependent variables include the three domain standard scores.


Maladaptive Behavior

Behavior Assessment System for Children (BASC): The BASC (Reynolds & Kamphaus, 1992) is an informant measure of both adaptive and problematic behaviors in everyday settings. It is comprised of 14 clinical scales and two broad domains: Externalizing Problems, Internalizing Problems. T-scores≥65 (i.e., 1.5 SDs≥the mean) indicate clinically significant symptoms. Dependent variables include the two broad domains and the following clinical scales: Attention Problems, Hyperactivity, Withdrawal, and Atypicality.


Procedures: This battery of tests and informant measures was administered over two sessions lasting two to three hours as part of a larger, study examining the neuropsychological profile of children with ASD. Parental or legal guardian consent and child assent were obtained prior to testing, families were compensated for their time, and the protocol was approved by the institutional review board.


Analyses: To compare the EC, autistic traits, adaptive functioning, and maladaptive behaviors of all three groups, group by task univariate (ANOVA) and multivariate analyses of variance (MANOVA) were completed. MANOVAs were used when a measure provided more than one dependent variable of interest. A False Discovery Rate of q<.05 (Benjamini & Hochberg, 1995) was used to control for the number of ANOVAs and MANOVAs conducted (i.e., 19 F-tests). When ANOVA and/or MANOVA analyses survived the False Discovery Rate then a Tukey’s hsd of p<0.05 was used for post-hoc comparisons.


Executive Control

Parent ratings of EC on the BRIEF’s broad indices (BRI; MCI) and two selected subscales (Inhibition; Shift) revealed a consistent pattern: the ASD+ADHD group received higher (more impaired) ratings than the ASD and TYP groups, Wilk’s Lambda: F(8,122)=13.86, p<0.001 (Tukey’s hsd p<0.05 for ASD+ADHD vs. ASD and ASD+ADHD vs. TYP for all four measures) and the ASD group was rated higher than the TYP group (Tukey’s hsd p<0.05 for ASD vs. TYP for all four measures; see Table 2). Lab measures of verbal working memory, F(2,62)=5.56, p<0.05, revealed the ASD+ADHD group scoring significantly lower than the TYP group (Tukey’s hsd p<0.05) but not the ASD group, even though there was a medium effect size for the latter comparison. No significant differences were found between groups on spatial working memory, F(2,56)=1.85, p=0.17, and response inhibition measures, F(2,56)=1.51, p=0.23; although, as shown in Table 2, there were medium effect sizes for worse performance by the ASD+ADHD group relative to the other groups.


Autistic Traits and Symptoms and ADHD Symptoms

Overall, the ASD and ASD+ADHD groups received significantly higher autistic trait ratings on the SRS relative to the TYP group, F(2,64)=91.09, p<0.001 (Tukey’s hsd p<0.05 for ASD vs. TYP and ASD+ADHD vs. TYP; see Table 3), and the ASD+ADHD group received higher autistic trait ratings on the SRS compared to the ASD group (Tukey’s hsd p<0.05). However, the ASD and ASD+ADHD groups did not differ in the number of autism symptoms as reported on the ADI Social, ADI Communication, ADI Repetitive Behavior, and the ADOS Social+Communication scales (all ts(43)≤1.58, all ps≥0.12). For ADHD symptoms, the ASD+ADHD group was rated as having more Total symptoms, Inattention symptoms, and Hyperactivity/Impulsivity symptoms compared to the ASD and TYP groups, F(2,67)=36.80, p<0.001 (Tukey’s hsd p<0.05 for all comparisons). The ASD group was rated as having more Total and Inattention symptoms, but not Hyperactivity/Impulsivity symptoms, compared to the TYP group. The differences between the ASD+ADHD group and the ASD group were expected as the ADHD Rating scale was the measure used to distinguish the ASD from the ASD+ADHD group.


Adaptive Functioning

Overall, both ASD and ASD+ADHD groups received significantly lower adaptive functioning ratings on the Communication, Daily Living Skills, and Socialization domains relative to the TYP group, F(6,100)=10.26, p<0.001 (Tukey’s hsd p<0.05 for ASD vs. TYP and ASD+ADHD vs. TYP for all three measures), but the ASD+ADHD group exhibited a more severe impairment in Daily Living Skills compared to the ASD group, F(2,52)=23.76, p<0.001 (Tukey’s hsd p<0.05; see Table 4).


Maladaptive Behaviors

Overall, both ASD and ASD+ADHD groups received higher maladaptive behavior ratings on the broad indices of Externalizing Problems and Internalizing Problems, as well as the clinical scales of Atypicality, Attention Problems, Hyperactivity, and Withdrawal compared to the TYP group, F(12,102)=8.67, p<0.001 (Tukey’s hsd p<0.05 for ASD vs. TYP and ASD+ADHD vs. TYP for all six measures; see Table 3). Furthermore, the ASD+ADHD group received significantly higher ratings for Externalizing Problems, Attention Problems, and Hyperactivity, than the ASD group (Tukey’s hsd p<0.05).


Age and Gender Effects

As a secondary analysis, age and gender effects were examined. As a first pass analysis for age, all dependent variables were correlated with age, and an FDR (q<.05) was applied. Not one of the correlations survived this correction and further analyses were not conducted. To examine gender effects, all females were removed and analyses were re-run. The pattern of results remained the same save one finding: group differences between Controls and ASD on the Communication Domain of the Vineland were no longer significant (Control: mean=102.75, SD=7.38; ASD mean=98.8 SD=14.33, Tukey’s HSD p=.83).



The current study probed the impact of ADHD symptoms on the ASD phenotype relative to children with ASD without significantly elevated ADHD symptoms and TYP children.

Consistent with our predictions, we found that children with ASD+ADHD exhibited significantly exacerbated problems in verbal working memory, global EC, autistic traits, adaptive function, and externalizing behaviors. Contrary to our predictions, the ASD

+ADHD group also exhibited exacerbated cognitive flexibility deficits in everyday settings, but no significant inhibition deficits on our lab measure, and we failed to find spatial working memory impairments in either clinical group. Of note, both EC lab measures showed a pattern in which Controls scored higher than the ASD group which in turn scored higher than the ASD+ADHD group.


Executive Control

Our finding of exacerbated global EC deficits in children with ASD+ADHD compared to both TYP and ASD groups is consistent with our hypothesis that combining two disorders with distinct EC deficit profiles would have an additive effect overall. Past research on the BRIEF has shown unique EC profiles for ASD and ADHD samples (Gioia et al., 2002), but no previous study has examined profiles for an ASD+ADHD sample. Our findings of impaired EC behaviors in the ASD group are consistent with several previous BRIEF studies (Gilotty et al., 2002; Gioia et al., 2002; Kenworthy et al., 2009) and other informant-based measures of cognitive flexibility (Green et al., 2006; Didden et al., 2008; Peters-Scheffer et al., 2008). The current study’s findings of greater impairments in EC for the ASD+ADHD group are consistent with prior findings of greater global impairments in ADHD (Gioia et al., 2002); however, our finding of greater cognitive flexibility impairments in the ASD

+ADHD group was unexpected. One potential interpretation is that the ASD+ADHD group has greater EC impairments (as suggested from the verbal working memory lab measure and a prior report of inhibitory control: Sinzig et al., 2008b) and these processes produce an additive effect, increasing global EC deficits.


Our reported verbal working memory deficit in the ASD+ADHD group relative to TYP (and a medium effect size compared to the ASD group) is in contrast with a previous study showing similar levels of impairment in ASD and ASD+ADHD samples during a verbal working memory task (Goramus et al., 2009). Differences in task design may explain the discrepant findings. The task used here, backwards Digit Span, required manipulation of stored information, while the task from the earlier study required only storage of verbal stimuli across a delay. This suggests that manipulation of verbal information in working memory may be a unique deficit for the ASD+ADHD sample. A recent meta-analysis (Willcutt et al., 2005) examined verbal working memory manipulation in ADHD and found evidence for an impairment with a medium weighted effect size (Cohen’s d=.55). A significant impairment in working memory was found in 55% of studies. While this was not the largest effect reported for ADHD, the working memory manipulation does appear to be an area of weakness in ADHD and our findings for the ASD+ADHD group converge with the ADHD literature. Our failure to find spatial working memory deficits in the ASD

+ADHD group relative to the TYP or ASD groups is consistent with a prior study (Sinzig et al, 2008b); however, this conflicts with the emerging literature of a subtle ASD-related impairment in spatial working memory that requires larger sample sizes to reach statistical significance (see Kenworthy et al., 2008 for review). Our results also highlight a potential distinction between spatial and non-spatial working memory weaknesses in these children, although the findings in this area remain complex and somewhat contradictory; future studies should examine these potential working memory distinctions in children with ASD



Our finding of no group differences in the response inhibition measure corroborates one previous study (Sinzig et al., 2008a), but conflicts with another (Sinzig et al., 2008b).

However, recent theoretical arguments suggest that the response inhibition task used here, Walk Don’t Walk, may be confounded with processing speed demands (Bishop & Norbury, 2005). In addition, the mean of the TYP group was slightly below average relative to the Walk Don’t Walk standardization sample and out of line with the TYP group’s high average IQ and minimal ADHD symptoms. This raises the broader question of Walk Don’t Walk’s sensitivity to accurately tap attention/impulsivity in this sample. Therefore, this measure may not have been the most sensitive for detecting response inhibition impairments prototypically associated with ADHD; future studies should focus on well-replicated and purer measures of inhibition, such as the Go/No-Go and Stop-Signal tasks (Willcutt et al., 2005).


Of note, many of the ASD and even the ASD+ADHD groups’ EC means fall within 1 SD of the published norms, and this may lead to some concern regarding the meaningfulness of the group differences. However, the age-, IQ-, gender-ratio-, socioeconomic-matched Control group performs better than either of the ASD or ASD+ADHD groups on the BRIEF and Digit Span, demonstrating that these EC areas are a relative weakness for high-functioning children with ASD and ASD+ADHD. Indeed, a significant portion of children with ASD (19%-50% across the subscales and indices) score in the borderline or clinical range on the BRIEF (T-score ≥65).


Autistic Traits and Symptoms

We found exacerbated autistic traits in the ASD+ADHD group, although findings in this and previous reports diverge depending on whether traits or symptoms were measured. We found the ASD+ADHD group received higher autistic trait ratings on the SRS, but not significantly more autism symptoms on the ADI and ADOS. Prior investigations also did not find differences when using another symptom based measure, the CSBQ (Luteijn et al., 2000; Goramus et al., 2009). One potential explanation for the divergent findings is that the SRS was designed to measure autistic traits on a broad spectrum from typical to clinically significant; whereas the CSBQ (Luteijn et al., 2000) and ADI/ADOS are designed to measure clinically elevated ASD symptoms (Gotham, Risi, Pickles, & Lord, 2006). Thus, the CSBQ may have been insensitive to differences between ASD and ASD+ADHD groups, consistent with our lack of group differences on ADI and ADOS scales. Another explanation may be that the SRS assesses more than autism-specific traits, and therefore ratings of broader social problems may explain the higher ratings in our ASD+ADHD sample as well as previous ADHD samples (e.g., Reiersen et al., 2007). Placed within this context, the present study indicates that ADHD exacerbates the social disabilities of children with ASD.


Adaptive Functioning

Our finding of significant impairments across various adaptive function domains in both ASD groups relative to TYP controls is in line with past studies (e.g., Volkmar et al., 1987; 1993; Saulnier & Klin, 2008); however, the finding of greater impairments in Daily Living Skills for the ASD+ADHD group relative to the ASD group is novel. The exacerbated impairments in the Daily Living Skills domain may result from increased global EC deficits in the ASD+ADHD group and associated difficulties in organization and planning, which are key cognitive skills that aid codification of everyday routines, such as eating, dressing, showering, and brushing one’s teeth. Disorganization is one of the inattention symptoms for an ADHD diagnosis (APA, 2000), and previous research has documented impaired organization and planning in ASD (Kenworthy et al., 2005) and in ADHD (Willcutt et al., 2005). Regardless, the presence of ADHD exacerbates daily living skills in ASD.


Although adaptive Communication scores are depressed in both ASD groups compared to the TYP group, the difference between the pure ASD and TYP group scores becomes non- significant when girls (n=8) are removed from the sample, a finding that converges with recent evidence of more severe communication deficits in females with ASD than males at an early age (Hartley & Sikora, 2009). Further work is needed to map out potential gender differences in the behavioral presentation of ASD.


Maladaptive Behaviors

Our findings that the ASD+ADHD group has significantly elevated externalizing maladaptive behaviors, Hyperactivity and Attention Problems, relative to the ASD and TYP groups, but has similar Withdrawal and Atypicality scores to the ASD group, supports several prior studies (Luteijn et al., 2000; Matsushima et al., 2008; but see Goramus et al., 2009), and confirms our hypothesis that ADHD exacerbates the externalizing behavior problems in the ASD profile. Many of the items in the clinical scales and the Externalizing Problems index rated higher in the ASD+ADHD group overlap with core ADHD symptoms. While to some degree this may reflect intra-rater reliability across similar questions on these measures, it is also notable that the two clinical groups were rated similarly for Internalizing Problems. Indeed, this finding suggests that parents of children with ASD+ADHD were not simply biased in their ratings, but targeted specific domains affected by ADHD symptoms. Although it may be tempting to conclude that our both of our ASD groups’ functioning in maladaptive internalizing behaviors is not of clinical concern (T-scores are <1 SD from published norms), it is important to note that relative to their cognitive functioning level and to matched Controls they are exhibiting significantly greater Internalizing problems, and this supports recent findings that internalizing disorders such as specific phobias, OCD and depression are some of the more common comorbid psychiatric conditions in high- functioning ASD (Leyfer et al., 2006).


Implications for Our Understanding of ASD and ASD+ADHD Phenotypes

The current study has implications for the: conceptualization of the ASD+ADHD phenotype; interpretation of past ASD studies of EC; and clinical assessment and treatment of children presenting with ASD and ADHD symptoms. Pennington (2002) outlines six general criteria that must be met to identify a distinct phenotype. There must be differences in: 1) in treatment response; 2) clinical profiles (i.e., discriminates ASD from ASD+ADHD);

3) differences on performance measures that are independent from measures defining the diagnosis, such as neuropsychological or neuroimaging measures; 4) etiology; 5) pathogenesis; and 6) developmental trajectories. The current study is best equipped to address Pennington’s (2002) second and third criteria. Using established cut-offs for children with ADHD (DuPaul et al., 1998) we were able to identify two dissociable groups for the purpose of the current study, but future studies employing multiple methods of diagnosis in both discrete and dimensional fashions will confirm whether this distinction is clinically meaningful. Moreover, our neuropsychological and adaptive behavior findings, which are independent of measures used to define ASD and ADHD, do not support categorically different performance. While speculative, we would suggest that the observation of exacerbation of ASD impairments in some but not all domains of functioning for the ASD+ADHD group is most consistent with a “moderating” hypothesis (Mundy, Henderson, Inge, & Coman, 2007; Gadow et al., 2008). This hypothesis proposes that the presence of ADHD (and associated risk genes and behaviors) affects the expression of the ASD phenotype, but does not constitute a separate phenotype. Consistent with our hypothesis are previous findings of overlapping risk genes (Reiersen et al., 2007; Gadow et al., 2008; Ronald et al., 2008) and brain structure anomalies (Brieber et al., 2007). Future research in the ASD+ADHD phenotype, with a particular focus on treatment response,

pathogenesis, and developmental trajectory, will rigorously test this hypothesis and as well as other models (e.g., for detailed models of comorbidity see Neale & Kendler, 1995).


This study also has implications for the interpretation of EC data collected in previous research that has not routinely screened for ADHD in ASD (but see Goldberg et al., 2005; Corbett et al., 2009). If the presence of ADHD symptoms in the context of ASD creates an exacerbated or moderated profile, as discussed above, past studies should be interpreted with caution when considering the severity (or the effect size) of EC impairment. As the field’s understanding of ASD is refined, specificity regarding its associated features, including EC, will also improve. Finally with respect to clinical implications, the notable findings of increased difficulties with daily living skills make them a primary target in the assessment and intervention of children with ASD and ADHD symptoms.




Several potential factors may limit the generalization of our findings. Many of the key findings are based on informant ratings of child behavior across a variety of domains. While informant ratings are subject to bias, this concern should be mollified by the observation that caregivers in the ASD+ADHD group did not rate their children as more severely impaired across all domains (e.g., VABS Social and Communication Skills, BASC Internalizing Problems). This enhances confidence that group differences are not solely related to informant bias. Another concern regarding the informant ratings is the potential overlap between measures used to create the groups (e.g., ADI and ADHD rating scale) and dependent measures (SRS and BRIEF). The ADI and ADHD rating scale were created to count the number of symptoms for diagnostic purposes, and, particularly in the case of the ADI, are not intended for use as a continuous measure of severity (Gotham et al., 2006). In contrast, the BRIEF (Gioia et al., 2000) and SRS (Constantino & Gruber, 2005) are both well-normed, continuous measures, designed to assess a wide array of neurotypical and clinical populations. Nevertheless, the Inhibition and Working Memory subscales from the BRIEF have a high correlation with ADHD diagnostic measures (Gioia & Isquith, 2001), and therefore findings may reflect group assignment. Somewhat small samples are also a concern particularly when examining performance on the spatial working memory and response inhibition measures; we generally found a trend toward increasing impairment across the TYP, ASD, and ASD+ADHD group, supported by medium effect sizes despite non-significant p values. Another limiting factor is that the ASD+ADHD group was defined through the use of a single parent measure, and this would not suffice using DSM-IV TR criteria for securing significant impairments in two contexts (APA, 2000) or standards applied in the ADHD literature (e.g., Lahey et al., 2004). Another limiting factor is that our sample is considerably high-functioning with a mean IQ in the High Average range, and therefore our findings in the ASD+ADHD group relative to the ASD group may not apply to lower functioning samples. Moreover, establishing a lower bound Full Scale IQ of 80 in all groups during matching reduced differences for the ASD+ADHD group, from which four excluded children were excluded.


The current study examined cognitive, social, and adaptive profiles of children with ASD

+ADHD symptoms relative to children with ASD symptoms. It provides novel findings for a potential ASD+ADHD phenotype that has exacerbated impairments in autistic traits, daily living skills, and maladaptive behaviors, and potentially unique impairments in verbal working memory. The ASD+ADHD phenotype may inform novel treatment targets, as well as provide a potential method for parsing heterogeneity within the autism spectrum.



This work was supported by the Frederick and Elizabeth Singer Foundation and the Studies for the Advancement of Autism Research and Treatment (STAART: NIMH U54 MH066417) for supporting data collection. This work was also supported in part by the Intellectual and Developmental Disabilities Research Center at Children’s National Medical Center (NIH IDDRC P30HD40677) and the General Clinic Research Center (NIH GCRC M01-RR13297). This work was also supported by a T-32 post-doctoral to BEY through the IDDRC (NIH T32HD046388). GLW was supported by the NIH, National Institute of Mental Health Intramural Research Program, during completion of this work.

We thank the children and families that offered their time and energy for the current study. We thank Brett Robinson and Georgia Papatheodrou for their efforts in database management. We thank the entire Center for Autism Spectrum Disorders research team at Children’s National Medical Center for their feedback on data analysis and interpretation. One author (LK) receives financial compensation for the BRIEF.


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Participant demographics

Table 1


Chronological Age (Years)
M (SD)10.30 (1.76)9.70 (2.12)9.65 (1.62)
Full Scale IQ
M (SD)116.24 (11.53)117.39 (18.68)111.24 (13.56)
Gender (male/female)13/820/818/3
Black/African American031
Indian/Southeast Asian020

Family Socioeconomic Status

M (SD)23.71 (8.64)23.13 (11.36)26.16 (14.93)

*AI/AN= American Indian/Alaskan Native



Group Differences in Executive Control Scores

Table 2


TYP M (SD)ASD M (SD)ASD+ADHD M (SD)Group Differences*
Behavior Rating Inventory of Executive Function (BRIEF)
BRI (T-Score)41.62 (6.55)59.92 (11.89)71.60 (10.78)TD<ASD<ASD+ADHD
MCI (T-Score)43.29 (5.55)58.19 (10.57)73.65 (6.75)TD<ASD<ASD+ADHD
Inhibit (T-Score)44.10 (6.88)57.31 (11.81)69.65 (13.28)TD<ASD<ASD+ADHD
Shift (T-Score)43.71 (10.25)63.62 (13.30)72.50 (11.55)TD<ASD<ASD+ADHD
Digit Span (DS)
Backwards (Scaled Score)11.80 (2.80)10.80 (3.08)9.10 (2.63)TD>ASD+ADHD; ASD=TD, ASD=ASD+ADHDa
Spatial Working Memory
BE (Raw Score)38.59 (14.09)43.88 (16.33)49.65 (19.59)Noneb
Walk Don’t Walk
Total (Scaled Score)7.43 (2.60)6.18 (3.29)5.56 (4.27)Nonec

BE= Between Errors

*These differences are significant after controlling for multiple comparisons with the False Discovery Rate (q<0.05), and then using Tukey’s hsd (p<0.05) for post-hoc analyses.

aEffect size for the difference between ASD and ASD+ADHD was medium (Cohen’s d=0.59)

bEffect sizes for the difference between ASD+ADHD vs. TYP and ASD+ADHD vs. ASD were medium-to-large (Cohen’s d=0.65 and 0.42, respectively)

cEffect sizes for the difference between ASD+ADHD and TYP and ASD vs. TYP were medium (Cohen’s d=0.53 and 0.42, respectively)


Table 3

Group Differences in Autistic Traits and Symptoms, and ADHD Symptoms



Social Responsiveness Scale (SRS) *



Group Differences**


Total                        41.30 (5.64)     69.88 (13.01)     81.29 (18.89)    TD<ASD<ASD+ADHD


Social + Communication Score


M (SD)——–11.81 (4.13)11.05 (4.68)N.S.
Social Score
M (SD)——–16.68 (7.06)19.60 (4.84)N.S.
Verbal Communication Score***
Total Score M (SD)     ——–14.52 (5.47)16.65 (4.42)N.S.
Range                       ——–2-248-24
Repetitive Behaviors Score
M (SD)——–6.28 (2.64)6.35 (2.35)N.S.
M (SD)0.10 (0.30)1.89 (1.81)7.52 (1.50)TYP<ASD<ASD+ADHD


ADHD Rating Scale Inattention Symptoms



Hyperactivity/Impulsivity Symptoms


M (SD)0.10 (0.30)1.64 (1.77)5.19 (2.98)TYP<ASD<ASD+ADHD
Total ADHD Symptoms
M (SD)0.19 (0.51)3.54 (3.02)12.71 (3.77)TYP<ASD<ASD+ADHD

*SRS scores are T-Scores (mean=50, SD=10). ADOS, ADI, and ADHD Rating Scale scores are raw scores.

**These differences are significant after controlling for multiple ANOVA or MANOVA comparisons with the False Discovery Rate (q<0.05), and using Tukey’s hsd (p<0.05) for post-hoc analyses.


Table 4

Group Differences in Adaptive Functioning, and Maladaptive behaviors



ASD+ADHD    Group Differences** M (SD)

Vineland Adaptive Behavior Scales (VABS)
Communication106.63 (10.65)94.86 (15.67)85.41 (19.58)TD>ASD=ASD+ADHD
Daily Living Skills104.25 (14.24)79.45 (15.34)66.82 (17.84)TD>ASD>ASD+ADHD
Social Skills103.37 (10.57)79.59 (11.84)73.41 (16.87)TD>ASD=ASD+ADHD
Behavior Assessment System for Children (BASC) Domains
Externalizing Problems42.45 (5.88)49.57 (9.86)62.50 (15.14)TD<ASD<ASD+ADHD
Internalizing Problems41.60 (7.79)51.71 (12.47)52.33 (11.93)TD<ASD=ASD+ADHD
Atypicality43.25 (8.45)58.57 (14.66)67.33 (17.70)TD<ASD=ASD+ADHD
Attention Problems44.90 (6.17)56.48 (8.29)68.22 (5.34)TD<ASD<ASD+ADHD
Hyperactivity41.55 (7.98)55.81 (10.47)67.78 (17.41)TD<ASD<ASD+ADHD
Withdrawal44.75 (8.54)57.48 (11.77)59.28 (13.88)TD<ASD=ASD+ADHD

*All scores except for those from the VABS are T-Scores (mean=50, SD=10). VABS scores are Standard Scores (mean=100, SD=15).

**These differences are significant after controlling for multiple ANOVA or MANOVA comparisons with the False Discovery Rate (q<0.05), and using Tukey’s hsd (p<0.05) for post-hoc analyses.