Quantitative Methods Discussion

A Comparison of Social Cognitive Profiles in children with Autism Spectrum Disorders and Attention-Deficit/Hyperactivity Disorder: A Matter of Quantitative but not Qualitative Difference?

Carly Demopoulos • Joyce Hopkins •

Amy Davis

Published online: 27 September 2012

� Springer Science+Business Media, LLC 2012

Abstract The aim of this study was to compare social

cognitive profiles of children and adolescents with Autism

Spectrum Disorders (ASD) and ADHD. Participants diag-

nosed with an ASD (n = 137) were compared to partici-

pants with ADHD (n = 436) on tests of facial and vocal

affect recognition, social judgment and problem-solving,

and parent- and teacher-report of social functioning. Both

groups performed significantly worse than the normative

sample on all measures. Although the ASD group had more

severe deficits, the pattern of deficits was surprisingly

similar between groups, suggesting that social cognitive

deficit patterns may be more similar in ASD and ADHD

than previously thought. Thus, like those with ASDs,

individuals with ADHD may also need to be routinely

considered for treatments targeting social skills.

Keywords Autism � ADHD � Social skills � Facial and vocal affect recognition � Pragmatic judgment � Parent and teacher report

Introduction

A deficit in social interaction is a defining feature of Aut-

ism Spectrum Disorder (ASD; DSM-IV-TR 2000); how-

ever, social deficits are also a well-documented

phenomenon in children with ADHD (Clark et al. 1999;

Corbett and Constantine 2006; Hattori et al. 2006; Leyfer

et al. 2006; Stormont 2001; Whalen et al. 1990). Indeed,

there is a considerable body of research that has identified

symptom overlap between ADHD and ASD (Corbett and

Constantine 2006; Goldstein and Schwebach 2004; Holt-

mann et al. 2007; Leyfer et al. 2006; Sturm et al. 2004;

Yerys et al. 2009; Yoshida and Uchiyama 2004). It is not

clear, however, if the social deficits in each diagnostic

group differ in quality or degree.

Models of social information processing propose that

receptive social skills (attending to, perceiving, and accu-

rately interpreting relevant social information) are neces-

sary to inform and execute an appropriate social response

(Crick and Dodge 1994; Shapiro et al. 1993). Thus, diffi-

culties at the level of either receptive social skills or

behavioral response could adversely impact a social out-

come. The hierarchical nature of these models implies that

deficits in receptive social skills lead to a suboptimal

behavioral response based upon misunderstanding of the

social context. Alternatively, accurate social perception in

the context of a limited repertoire of appropriate social

problem-solving or response options may result in socially

detrimental behavior as well. Thus, the specific skill defi-

cits (i.e., social comprehension vs. social response) that

lead to inappropriate social behaviors are distinct from

each other and require different interventions to improve

social functioning. Understanding the nature of social dif-

ficulties in children with poor social competence is essen-

tial to identifying appropriate interventions. The aim of the

This paper was prepared from a predoctoral thesis submitted by the

primary author as part of the degree requirements for the Ph.D.

program in clinical psychology at Illinois Institute of Technology.

C. Demopoulos � J. Hopkins Illinois Institute of Technology, Department of Psychology,

3105 South Dearborn, Suite 252, Chicago, IL 60616-3793, USA

C. Demopoulos (&) Mind Research Network, Pete and Nancy Domenici Hall,

1101 Yale Blvd. NE, Albuquerque, NM 87106, USA

e-mail: [email protected]

A. Davis

Alexian Brothers Neuroscience Institute, 801 Biesterfield Rd.,

Elk Grove Village, IL 60003, USA

123

J Autism Dev Disord (2013) 43:1157–1170

DOI 10.1007/s10803-012-1657-y

present study was to examine a range of skills relating to

social comprehension and execution of social behavior in

children with ASD and ADHD, and to determine if these

groups differ in type or degree of social impairment.

Receptive Social Skills

Facial Affect Processing in ASD

Comprehension of affective cues is considered to be an

essential aspect of receptive social processing (Crick and

Dodge 1994; Shapiro et al. 1993). As such, affect recog-

nition has been the focus of numerous studies of children

with ASD and ADHD. Converging evidence indicates that

some level of impairment in facial affect recognition is

common in children with ASD (Bölte and Poustka 2003;

Braverman et al. 1989; Celani et al. 1999; Gross 2004; Hall

et al. 2003; Mazefsky and Oswald 2007; Ozonoff et al.

1990; Piggot et al. 2004; Welchew et al. 2005), although,

there are some contradictory data indicating that these

children are not impaired on basic emotion recognition

tasks (Baron-Cohen et al. 1997a; b; Castelli 2005; Gepner

et al. 2001; Heerey et al. 2003; Prior et al. 1990; Wang

et al. 2004). In two of these studies (Baron-Cohen et al.

1997a, b), the children with ASD exhibited impaired per-

formance relative to controls when recognition of complex

emotions was tested, although they were not impaired in

the recognition of basic emotions.

The complexity of affective stimuli, however, cannot

fully account for the discrepant findings in the remainder of

the studies in which intact affect recognition was reported

in the ASD samples. An additional factor that may con-

tribute to the inconsistent findings is the failure of some of

the studies to control for IQ, despite evidence that perfor-

mance on facial affect recognition tasks is related to gen-

eral intellectual (Bölte and Poustka 2003; Mazefsky and

Oswald 2007), or verbal ability (Braverman et al. 1989;

Ozonoff et al. 1990; Prior et al. 1990). A large number of

studies, however, have identified impairments even after

controlling for these variables (Bölte and Poustka 2003;

Celani et al. 1999; Gross 2004; Humphreys et al. 2007;

Mazefsky and Oswald 2007), or have failed to find any

relationship between intellectual functioning and facial

affect recognition (Davies et al. 1994; Heerey et al. 2003).

Results also have indicated associations between affect

recognition and age (Bölte and Poustka 2003), suggesting

that there may be a developmental component to difficulty

with emotion recognition. For example, children who

experience delays in these skill areas may acquire com-

pensatory strategies with age and experience. Null findings

reported in some of these studies may be a result of failure

to control for a potential age-related confound.

Gross (2004) controlled for these potentially confound-

ing variables by comparing children with autism to those

with intellectual disability, language disorder, and typically

developing controls on a multi-species facial emotion-

recognition task. Results indicated that children with aut-

ism scored significantly lower than the three other groups

of similarly-aged children despite the fact that two of these

groups exhibited cognitive and language impairments

comparable to those of the autistic group. While all char-

acteristics were not simultaneously controlled in this study

(i.e., IQ was significantly higher in the children with autism

than in those with intellectual disability, but significantly

lower than controls, and communication scores in the

autism group were significantly lower than controls), these

data support the hypothesis that children with autism are

less accurate in identifying facial affect for reasons not

related to language or general intellectual ability. In sum,

the weight of the evidence suggests that there is an elevated

frequency of deficits in facial affect comprehension among

the ASD population; however, the factors impacting the

variability of skills within this group remain unclear.

Facial Affect Processing in ADHD

Facial affect recognition in children with ADHD has not

been studied as extensively as in those with ASD; however,

the extant literature presents the same pattern of mixed

results, with some studies identifying deficits (Cadesky

et al. 2000; Corbett and Glidden 2000; Norvilitis et al.

2000; Pelc et al. 2006; Rapport et al. 2002; Shapiro et al.

1993; Singh et al. 1998), and others failing to do so (Guyer

et al. 2007; Hall et al. 1999; Sprouse et al. 1998). Also

consistent with findings in the autism literature, there is a

trend toward impaired affect recognition in studies of

younger children with ADHD (Singh et al. 1998), with one

study identifying a significant group by age interaction

(Shapiro et al. 1993). This age effect was not supported in a

study that reported facial affect recognition impairments in

28 adults with ADHD relative to a control group, however

(Rapport et al. 2002). In a study by Guyer et al. (2007), in

which both age and IQ were covaried, no significant dif-

ferences were found between ADHD and control groups on

facial affect recognition performance. Similarly, other

studies have also failed to find group differences on facial

affect recognition tasks between children with ADHD and

controls when matched on age and IQ (Hall et al. 1999;

Sprouse et al. 1998). Two studies in which IQ alone was

controlled identified deficits in facial affect recognition in

children with ADHD relative to controls; however, despite

all IQs being in the average range, significant IQ advan-

tages were noted in the control groups for both studies

(Cadesky et al. 2000; Corbett and Glidden 2000). In sum,

the literature on facial affect recognition in ADHD is

1158 J Autism Dev Disord (2013) 43:1157–1170

123

inconsistent. Similarly to the ASD literature, differences in

study designs and participant and task characteristics make

definitive conclusions difficult to draw. In general, the lit-

erature suggests that it is important to control for partici-

pant age and IQ in the study of facial affect recognition in

children with both ADHD and ASD.

Vocal Affect Processing in ASD

Data on vocal affect recognition in children with ASD are

similarly inconsistent. Specifically, several studies have

indicated poor recognition of vocal affect in individuals

with ASD (Golan et al. 2006; Järvinen-Palsey et al. 2008;

Linder and Rosen 2006), whereas other studies have failed

to find deficits. Mazefsky and Oswald (2007) found that

children and adolescents with high functioning autism

exhibited impaired vocal affect recognition while those

with Asperger’s Disorder did not. In a study that compared

affect matching (face to voice) and naming in children with

ASD to those with specific language impairments (SLI),

and a control group, the children with ASD scored lower

than controls and higher than the SLI group on the affect

matching task (Boucher et al. 2000). Surprisingly, affect

naming was only impaired in the SLI group and not in the

ASD group. O’Connor (2007) also failed to find differences

between adult participants with Asperger’s Disorder and

controls in identifying affect in face or voice, although

identification of incongruent affect among face-voice

paired stimuli was impaired in the Asperger’s group.

This complex pattern of findings has spurred several

studies that have examined auditory processing of voices in

ASD. There is well-documented evidence of abnormal

auditory processing in individuals with ASD (Baranek

1999; Dahlgren and Gillberg 1989; Gillberg and Coleman

1996; Lepistö et al. 2005; Osterling and Dawson 1994;

Rimland and Edelson 1995), specifically with regard to

elements of speech that relate to understanding of emo-

tional content, such as prosody (Järvinen-Palsey et al.

2008; Korpilahti et al. 2007; Rhea et al. 2005). Neverthe-

less, a direct relationship has not been established between

these sensory processing issues and social cognitive

deficits.

Vocal Affect Processing in ADHD

There are few studies that have examined vocal affect

processing in children with ADHD; however, unlike the

ASD literature, results provide consistent evidence of

deficits in vocal affect recognition (Corbett and Glidden

2000; Norvilitis et al. 2000; Rapport et al. 2002). For

example, children ages 6 to 11 with ADHD scored sig-

nificantly lower than controls when required to match

prosody to sentence content and facial expression (Shapiro

et al. 1993). Abnormal auditory processing also has been

demonstrated in children with ADHD (Huttunen-Scott

et al. 2008; Kemner et al. 2004), potentially accounting for

the difficulty in interpreting vocal affect. However, also in

line with the ASD literature, no studies have directly linked

auditory processing difficulty to errors in vocal affect

recognition and thus, the etiology of these deficits remains

unclear.

Expressive Social Skills

Deficits in social interaction are a defining feature of ASD

(DSM-IV-TR 2000), and, therefore, there is an extensive

literature focused on defining and assessing the nature of

atypical social behavior in individuals on the autism

spectrum. MacIntosh and Dissanayake (2006) found that

children ages 4-10 with autism and Asperger’s Disorder

were significantly less likely than their typically develop-

ing peers to interact socially with other children, to sustain

interactions, or to interact with three or more children at a

time during unstructured playground observations. Differ-

ences between clinical groups were largely due to a higher

level of involvement in conversation in the children with

Asperger’s compared to those with autism, which may

relate to differences in expressive language, rather than

social motivation. Further, when the social interaction was

structured, as in the case of complementary play, both

clinical groups were as frequently involved in social

interaction as the typically developing children. In contrast,

during periods of unstructured social play, children with

ASD were less likely to participate. The authors suggested

that this finding was related to difficulty understanding

social expectations in children with ASD. In another study

using direct observation to assess social behavior in chil-

dren with ASD and typically developing peers, Murdock

et al. (2007) found that children ages 5–10 with ASD

demonstrated significantly fewer initiations of verbal

behavior or joint attention, fewer verbal responses, and

fewer total interactions than typically developing peers.

Some studies have examined the quality of social

interactions, rather than specific behaviors in individuals

with ASD. For example, Ghaziuddin (2008) categorized

social interaction of individuals ages 7–51 with autism and

Asperger’s Disorder according to the three categories

‘‘aloof,’’ ‘‘passive,’’ and ‘‘active but odd.’’ Aloof partici-

pants were described as indifferent toward others in most

situations, while passive participants did not initiate con-

tact but responded appropriately without adding informa-

tion to further the interaction. Finally, active but odd

participants often initiated social interactions of an inap-

propriate nature (i.e., asking personal questions, etc.).

Results indicated that most individuals with autism were

categorized as aloof and passive, while those with

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Asperger’s Disorder were most often classified as active

but odd. The author discussed this finding in relationship to

shared symptoms of Asperger’s Disorder and ADHD.

Ruble (2001) reported findings based on natural observa-

tion in their homes during structured and unstructured time

of 6–10-year-old children with autism and Down syn-

drome, respectively. Results suggested differences in the

frequency and complexity of socially-intended behaviors in

children with autism, with a possible mediating effect of

executive function and attention.

Studies examining behavior of children with ADHD

during social interaction have demonstrated a failure to

modulate behavior according to the social context. In a

review of the literature, Landau and Moore (1991) con-

cluded that children with ADHD were less sensitive to

more passive roles that require less activity during inter-

action. Further, children ages 6–12 with ADHD did not

appropriately modulate communication style for different

roles assigned to them in a role-playing task (Landau and

Milich 1988). There is also some evidence that children

with ADHD have poor social problem-solving skills, which

lead to poor social judgments and behavior. In a study by

Grenell et al. (1987), 7–11-year-old children with ADHD

gave less suitable descriptions of an appropriate social

behavior in response to a social vignette compared to peers.

Comparison Studies

There are a few studies that have directly compared social

behavior in children with an ASD to those with ADHD.

Luteijn et al. (2000) compared social deficits in 5- to

12-year-old children with ADHD and those with a Perva-

sive Developmental Disorder, Not Otherwise Specified

(PDD-NOS). The authors reported social difficulties in

both groups, differentiated by greater severity of deficits in

social skills, withdrawal, relating, social interaction and

communication in the PDD-NOS group. Data from this

study, however, were limited to parent report measures,

and the authors were, therefore, unable to control for IQ.

Dyck et al. (2001) found that 9- to 16-year-old children

with autism, Asperger’s Disorder and ADHD all scored

lower than a control group on a battery of emotion rec-

ognition tests. When IQ was covaried, this pattern held for

all groups except the Asperger’s group, who performed as

well as controls. However, because analyses were per-

formed on composite scores from a battery of tests of

‘‘empathic ability,’’ it is unclear which specific social

cognitive deficits differentiated groups. In a study of 8- to

18-year-old children and adolescents, Buitelaar et al.

(1999) found that an ASD group (including participants

with autism and PDD-NOS) could not be differentiated

from an ADHD group on theory of mind or emotion

recognition tasks; although both groups performed

significantly worse than a control group. Through their

focus on the dimension of social cognition across diag-

nostic groups, these comparison studies have significantly

added to a growing body of research investigating the

nature of the deficits that lead to the poor social outcomes

in children with both of these disorders.

To summarize, the literature on facial affect processing

suggests that there is variable performance among children

with both ADHD and ASD. The factors that affect perfor-

mance are not clear, although there is evidence of a relation-

ship between affect comprehension and age (De Sonneville

et al. 2002), possibly indicating that some individuals with

deficits in facial affect identification may develop compen-

satory skills that allow them to improve their performance as

they get older. Although vocal affect processing has been

more frequently studied in children with ASD than in those

with ADHD, the evidence of vocal affect processing deficits is

more consistent in the studies of children with ADHD. To

date, there are no studies that have concurrently examined

facial and vocal affect processing, as well as expressive social

behavior and social outcomes in children diagnosed with ASD

and ADHD, as we did in this study. The shape of each group’s

social cognitive profiles may offer insight into the etiological

sources of social deficits in these two groups of children.

Finally, information regarding the levels at which the social

information processing system is disrupted in children with

ASD or ADHD can be used to direct early intervention in

children with these disorders.

Methods

Participants

Potential participants included 710 consecutive children and

adolescents referred to a pediatric neuropsychology clinic in

an academic medical center in the Midwestern United States

who received a diagnosis of an ASD or ADHD. Inclusion

criteria did not include language ability because impairment

in communication is a defining feature of ASD, and the

severity and type of communication impairments encompass

a wide range of language abilities. Thus, excluding partici-

pants based on language ability would result in a biased

sample of children on the autism spectrum. In addition,

previous research has suggested that some of these skills may

vary with age, and that a limited or discordant age range may

account for inconsistent findings among studies with respect

to facial affect processing deficits. Thus, all participants who

were of appropriate age for the study measures (ages 6–17)

were included.

This resulted in a final sample of 573 children with a

mean age of 10.54 years diagnosed with an ASD

(N = 137) or ADHD (N = 436). Sample size for different

1160 J Autism Dev Disord (2013) 43:1157–1170

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subtypes are described in Table 1 and participant charac-

teristics are presented in Table 2, with scores indicating

minimal difference in ADHD symptom rating between the

ASD and ADHD groups (Table 2). This finding is in line

with previous research demonstrating high levels of ADHD

symptomatology in individuals with ASDs (Corbett and

Constantine 2006; Goldstein and Schwebach 2004; Holt-

mann et al. 2007; Leyfer et al. 2006; Sturm et al. 2004;

Yerys et al. 2009; Yoshida and Uchiyama 2004).

Diagnoses were made by a licensed, board certified,

clinical neuropsychologist based on integration of devel-

opmental history, parent interview, school observation,

record review, neuropsychological testing, and scores on

the ADHD Rating Scale (DuPaul et al. 1998). In addition,

the Childhood Autism Rating Scale (CARS; Schopler et al.

1980), the Social Communication Questionnaire (SCQ;

Rutter et al. 2003), and the Autism Diagnostic Observation

Schedule (ADOS; Lord et al. 1989) were administered to

all children with suspected autism symptomatology.

Diagnosis of an ASD was ultimately based on clinical

judgment incorporating all sources of information rather

than on cut-off scores on the ADOS, for reasons specified

in the measures section. Participants in both groups met

diagnostic criteria according to DSM-IV-TR.

Measures

Diagnostic Assessment

The ADHD Rating Scale (DuPaul et al. 1998) is an 18-item

parent report measure of ADHD symptomatology with

adequate psychometric properties. Specifically, Cronbach’s

alpha values range from 0.79 to 0.84 and test–retest reli-

ability is reportedly .85 (Zhang et al. 2005). The Childhood

Autism Rating Scale (CARS; Schopler et al. 1980) is a

15-item clinician-report measure with good psychometric

properties. Interrater reliability of the CARS subscales

ranges from .71 to .93, with an internal consistency coef-

ficient alpha of .94. The correlation between CARS scores

and consensus clinical diagnosis is .80 (Schopler et al.

1980). The Social Communication Questionnaire (SCQ;

Rutter et al. 2003) is a 40-item parent report measure with a

sensitivity of .92 and specificity of .62 in classification of

ASD compared to clinical diagnosis (Witwer and LeCav-

alier 2007). The Autism Diagnostic Observation Schedule

(ADOS; Lord et al. 1989) is a semi-structured observa-

tional tool used to quantify social and communicative

behavior in relation to autism symptomatology. Assess-

ment of classification accuracy of the ADOS compared to

consensus clinical diagnosis has indicated that the ADOS

Table 1 Sample size of group subtypes

Subtype N

Autistic disorder 49

Asperger’s disorder 39

PDD-NOS 49

ADHD, combined type 271

ADHD, inattentive type 137

ADHD-NOS 28

Table 2 Group characteristics (M ± SD)

* p \ .01 ** p \ .001 a

Corrected values—equal

variances not assumed

ASD group ADHD group Statistics/range

Age 10.39 ± 3.49 10.58 ± 3.11 t(208.49) = .57 a

FSIQ 88.33 ± 18.86 98.20 ± 14.79 t(191.36) = 5.61** ,a

VIQ 93.27 ± 18.25 103.66 ± 13.60 t(185.80) = 6.15** ,a

POI/PRI 95.01 ± 17.13 100.30 ± 15.36 t(571) = 3.42*

BASC-P: hyperactivity 62.88 ± 13.12 63.48 ± 13.55 t(531) = .44

BASC-P: inattention 63.49 ± 7.58 64.81 ± 8.05 t(532) = 1.64

BASC-T: hyperactivity 60.62 ± 12.28 58.84 ± 13.15 t(414) = -1.23

BASC-T: inattention 60.96 ± 8.57 61.28 ± 8.87 t(415) = .32

ADOS (S ? C total) 12.14 ± 5.04 Range: 1–23

CARS 31.34 ± 5.58 Range: 20–47

SCQ 14.45 ± 6.92 Range: 0–30

Ethnicity (n)

Caucasian 102 316

African American 2 20

Hispanic 5 8

Asian 4 4

Other 5 6

Unknown 19 82

Male:female 123:14 293:143

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effectively differentiated autism from non-spectrum disor-

ders with reported specificities of .93–1.0 (Lord et al.

2000). The ADOS was designed to be used in the context

of a larger and thorough diagnostic evaluation incorporat-

ing developmental history. Several instances in which a

participant may fail to meet criteria on the ADOS while

meeting criteria for an ASD are outlined in the ADOS

Manual (Lord et al. 2001). Thus, clinical judgment incor-

porating diagnostic tools such as the ADOS is considered

to be the ‘‘gold standard’’ in diagnosing an ASD, and

therefore this approach was used in the present study.

Intelligence

IQ was assessed with the age-appropriate Wechsler test,

including either the Wechsler Intelligence Scale for Chil-

dren-IV (WISC-IV; Wechsler 2003) or the Wechsler Adult

Intelligence Scale-III (WAIS-III; Wechsler 1997), which

have been shown to be reliable measures of IQ. Reliability

between WAIS-III and WISC-IV was reported to be

r = .89 for Full Scale IQ, r = .86 for Verbal Compre-

hension Index (VCI), and r = .76 between the WAIS-III

Perceptual Organization Index and the WISC-IV Percep-

tual Reasoning Index (PRI; Flanagan and Kaufman 2009).

Affect Recognition

The child and adult faces and paralanguage subtests of the

Diagnostic Assessment of Nonverbal Accuracy-2 (DANVA-

2; Nowicki and Duke 1994) were used to measure facial and

vocal affect identification abilities. This computer task pre-

sents the participant with a photographic image of an indi-

vidual from the head to shoulders for 2 s for the facial affect

recognition subtest. For the vocal affect recognition task the

participant hears the same spoken sentence, ‘‘I’m going out

of the room now, but I’ll be back later,’’ presented in a range

of vocal affective tones one at a time. For each stimulus

presentation the participant selects a response from a choice

of four, labeled ‘‘happy,’’ ‘‘sad,’’ ‘‘angry,’’ or ‘‘fearful.’’

Stimuli range in varying levels of subtlety of emotional

expression, and high- and low-intensity expressions from

adult and child stimuli were combined to increase power,

resulting in two variables, for facial and vocal affect,

respectively. Dependent variables were standard scores

derived from a table of age norms for total errors on each

subtest. The DANVA-2 has been used in studies examining

specificity of emotion-labeling deficits in a range of child-

hood psychopathology (Guyer et al. 2007) and also in studies

examining social cognition and disorders of social func-

tioning (see manual for a list of citations; Nowicki 2010).

The DANVA-2 has been shown to have acceptable internal

consistency and reliability (Nowicki and Carton 1993;

Nowicki and Duke 1994), with reported reliabilities ranging

from .69 to .88 and internal consistency ranging from .64 to

.90 (Nowicki 2010; Nowicki and Duke 1994; Nowicki and

Mitchell 1998). Further information on studies demonstrat-

ing convergent, discriminant, and other criterion-related

validity measures of the DANVA-2 can be found in the test

manual (Nowicki 2010).

Social Problem-Solving

The Test of Problem Solving 3-Elementary (TOPS-3E;

Bowers et al. 2005), appropriate for children ages 6-13, and

Test of Problem Solving 2-Adolescent (Bowers et al. 2007;

TOPS-2A), appropriate for ages 12–18, were used to

measure ability to integrate social skills to accurately read

and formulate an appropriate response to picture stimuli

(TOPS-3E) or written paragraphs (TOPS-2A) about inter-

action with others and the environment. Test–retest reli-

abilities range from .64 to .95 for the TOPS-3E and from

.85 to .96 for the TOPS-2A.

Social Judgment

The pragmatic judgment subtest of the Comprehensive

Assessment of Spoken Language (CASL; Carrow-Woolfolk

1999) was used as a second measure of social performance

ability. This subtest evaluates the effective use of language in

common, real-life social situations, asking the examinee to

use contextual factors, apply mentalizing skills, and flexibly

respond to contrived social situations, such as adjusting

behavior during introductions to different people (i.e., peers

vs. authority figures), politely declining offers, and

expressing honesty with sensitivity to the feelings of another

person, etc. Carrow-Woolfolk (1999) reported internal

consistency reliabilities ranging from .79 to .92 across the

range of age groups in the normative sample.

Informant-Report of Social Competence

The parent- and teacher-report on the Social Skills Scale of the

Behavior Assessment Scale for Children-2nd Edition (BASC-

2; Reynolds and Kamphaus 2004) was used to measure parent

and teacher ratings of social skills and behavior. Test–retest

reliabilities range from .74 to .86 for the Social Skills scale,

and interrater reliability between two parents ranges from .64

to .75 (Reynolds and Kamphaus 2004).

Procedure

All tests were administered and scored according to age-

scaled norms by a trained psychometrician and scoring was

checked by a licensed, board-certified neuropsychologist.

To avoid the above-mentioned concerns regarding sample

bias due to limitations of age or language ability in test

1162 J Autism Dev Disord (2013) 43:1157–1170

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administration, data imputation was performed to replace

missing data so that a representative sample of children

with ADHD and ASD could be included in this study. A

multiple imputation was performed on LISREL 8.8 using

the EM algorithm with settings of 200 iterations, 10 rep-

etitions, random seed, and convergence criteria of 0.00001.

In multiple imputation a series of imputed datasets are

created, analyzed, and ultimately combined into a final

dataset. This procedure acknowledges the uncertainty due

to imputation and attempts to minimize the resulting

increase in error. See Shafer and Graham (2002) for a

discussion of these multiple imputation methods. Conver-

gence was reached in 18 iterations with a missing values

rate of 18.71 %. Missing values for individual tests are

reported in Table 3.

Results

Preliminary Analyses

Based on previous data indicating associations between age

or IQ and social perception, correlational analyses were

performed to determine which of these variables correlated

with social cognitive measures. Pearson correlation coef-

ficients for the combined sample are reported in Table 4.

Because all scores are based on age-scaled norms, perfor-

mance differences due to age were not expected; however,

research describing a potential interaction of age and

diagnostic group on social cognitive skill development

suggests that examination of correlations was warranted.

Correlational analyses failed to indicate any strong corre-

lations between age and any of the social measures (max-

imum r = -.11); therefore, age was not specifically

controlled beyond the age-scaled test scoring.

Some strong relationships were found, however,

between social cognitive performance measures and mea-

sures of IQ. Examination of partial correlations indicated

that full scale IQ (FSIQ) had the strongest relationship to

the majority of social cognitive measures (with partial

correlation values ranging from .02 for Parent Report

BASC to .27 for Pragmatic Judgment) after controlling for

all other IQ measures, including VIQ and PIQ. As such,

FSIQ was systematically controlled in all analyses.

Analyses

A series of one-sample t tests compared to the normative

means were performed to determine if each group of

children differed from the standardization sample. Group

differences between measures were tested using a 2 9 6

mixed Analysis of Covariance (ANCOVA), with IQ

entered as a covariate, to assess for between- and within-

subject main effects, as well as interactions between

diagnostic group and specific skill deficit. Finally, a post

hoc oneway ANCOVA was performed for each social

cognitive task to explore group differences on individual

tasks when IQ was covaried. Bonferroni corrections for

multiple comparisons were employed for all univariate

tests (corrected p value of \.0017). Results of the one-sample t-tests indicated that children

in both groups scored significantly lower than expected

Table 3 Sample size with percentage missing by study task and group prior to imputation

Task condition ASD (N = 137) ADHD (N = 436)

FSIQ 112 (18.25 %) 414 (5.05 %)

VIQ 113 (17.52 %) 414 (5.05 %)

PIQ 114 (16.79 %) 415 (4.82 %)

Facial affect 115 (16.06 %) 276 (36.70 %)

Vocal affect 113 (17.52 %) 274 (37.16 %)

Pragmatic judgment 95 (30.66 %) 158 (63.76 %)

Problem-solving 74 (26.89 %) 163 (62.61 %)

Parent rating 130 (5.11 %) 399 (8.49 %)

Teacher rating 108 (21.17 %) 307 (29.59 %)

Table 4 Pearson correlation coefficients (r) for combined groups

Age Facial affect Vocal affect Prag. judg. Prob. solv. Parent report Teacher report FSIQ VIQ PIQ/PRI

Age –

Facial affect .07 –

Vocal affect .09 .70 –

Pragmatic affect -.11 .56 .64 –

Problem-solving .09 .53 .63 .88 –

Parent report -.01 .18 .11 .22 .16 –

Teacher report .02 .18 .14 .30 .29 .43 –

FSIQ .01 .60 .67 .78 .80 .09 .12 –

VIQ .02 .49 .61 .80 .83 .12 .16 .88 –

POI/PRI -.08 .55 .55 .59 .59 .04 .01 .85 .65 –

J Autism Dev Disord (2013) 43:1157–1170 1163

123

according to age-scaled scores on all social cognitive tests.

On both parent- and teacher-report both groups of children

scored significantly lower on the Social Skills Scale of the

BASC-2 than the normative sample (see Table 5). In the

ADHD group effect sizes were moderate for the CASL,

TOPS, and BASC-2 parent and teacher report of social

skills, and effects were small for DANVA Facial and Vocal

Affect. In the ASD group effect sizes were large for the

CASL, TOPS, and DANVA Facial Affect. Effects on all

other measures were moderate.

Box’s Test of Equality of Covariance Matrices was

significant, F(21, 242,245.72) = 7.34, p \ .001, indicating that the homogeneity of covariance assumption was vio-

lated. However, considering the sufficiently large sample

size (N = 573), the F-tests can be expected to be robust to

this violation. Mauchly’s Test of Sphericity was significant,

v2(14) = 654.81, p \ .001, indicating that the sphericity assumption was also violated. Greenhouse-Geisser correc-

tions were used to control for violation of this assumption.

Multivariate analyses were significant at the level of task

condition with IQ covaried, K = .58, F(5, 566) = 83.03, p \ .001, with a moderate effect size of partial g2 = .42. The interaction between task condition and diagnostic

group also yielded statistically significant results, K = .92, F(5, 566) = 10.12, p \ .001, although the effect size was much smaller, partial g2 = .08. Mixed ANCOVA results indicated significant effects of diagnostic group, F(1,

570) = 86.50, p \ .001, g2 = .13, social cognitive task condition, F(3.59, 2,048.21) = 119.56, p \ .001, g2 = .17, and the interaction between group and condition, F(3.59,

2,048.21) = 9.30, p \ .001, g2 = .02, when IQ was covaried.

Univariate ANCOVA analyses indicated that the ADHD

group performed significantly better than the ASD group on

all social cognitive tasks (Table 6), but with generally small

effect sizes. Figure 1 illustrates the interaction between

group and task. Performance differences on the social per-

ception measures were minimal compared to the discrep-

ancy between groups on the measures of social response and

outcome ratings. Skill profiles were strikingly similar

overall, however, with the difference mainly in the degree

of impairment rather than the shape of the profiles, as

indicated by the smaller effect size for the interaction than

for Group and Condition effects. Overall, children in both

groups demonstrated similar patterns of strengths and

weaknesses, with significantly lower scores in the ASD

group across all measures. This poorer performance was

slightly more pronounced for measures of social responding

than for measures of social perception.

Discussion

Difficulty in social interaction is a defining feature and one

of the criteria for diagnosing an ASD. Accordingly, there is

an extensive body of research dedicated to understanding

the nature, causes, and treatment of the social deficits

observed in ASD. Social deficits are also common in

children with ADHD, although they are not thought to be a

central feature of the disorder, and are not included in the

diagnostic criteria. This study was the first to concurrently

compare the performance of children with ASD and ADHD

on a range of social cognitive tasks and parent- and tea-

cher-report of social skills. This allowed for the

Table 5 One-sample t test of group performance compared to

the normative sample mean

IQ was not controlled in these

analyses

* p \ .001

Task condition ASD (N = 137) ADHD (N = 436)

t Cohen’s d t Cohen’s d

Facial affect -8.55* -0.86 -9.79* -0.36

Vocal affect -6.68* -0.62 -5.70* -0.18

Pragmatic judgment -14.46* -1.55 -12.56* -0.51

Problem-solving -17.22* -1.54 -16.72* -0.55

Parent rating -15.38* -0.77 -16.52* -0.77

Teacher rating -14.23* -0.56 -13.77* -0.56

Table 6 Oneway ANCOVA results for group differences in

social cognitive task standard

scores with IQ as covariate

* p \ .05 ** p B .01

*** p \ .001

Task condition ASD: M ± SD (N = 137) ADHD: M ± SD (N = 436) F g2

Facial affect 87.15 ± 17.60 94.67 ± 11.37 6.64** .01

Vocal affect 90.72 ± 16.26 97.34 ± 9.76 4.59* .01

Pragmatic judgment 76.72 ± 18.85 92.43 ± 12.58 91.29*** .14

Problem-solving 76.97 ± 15.65 91.80 ± 10.24 154.65*** .21

Parent rating 81.46 ± 14.11 88.47 ± 14.57 20.46*** .04

Teacher rating 84.86 ± 12.45 91.53 ± 12.83 22.90*** .04

1164 J Autism Dev Disord (2013) 43:1157–1170

123

examination of differences in abilities across measures in

each diagnostic group, as well as differences in the overall

pattern of the social cognitive skill profiles of each group.

Both groups performed significantly below the normative

mean on all social cognitive measures, further corroborat-

ing previous research indicating that children with ADHD,

as well as those with an ASD, have deficits in social skills.

Affect Recognition in ASD

The ASD group performed significantly below the nor-

mative mean on the facial affect recognition task which is

consistent with previous research identifying deficits in

comprehension of facial affect in children with ASD (Bölte

and Poustka 2003; Braverman et al. 1989; Celani et al.

1999; Gross 2004; Hall et al. 2003; Mazefsky and Oswald,

2007; Ozonoff et al. 1990; Piggot et al. 2004; Welchew

et al. 2005). The effect size for this difference was large

(Cohen’s d = -0.86). Thus, the present results lend further

support to the converging data that suggest that deficits in

facial affect recognition are common in ASD (Baron-

Cohen et al. 1997a, b; Castelli 2005; Gepner et al. 2001;

Heerey et al. 2003; Wang et al. 2004). The present results

are also consistent with previous studies showing a deficit

in vocal affect recognition in children with an ASD (Golan

et al. 2006; Järvinen-Palsey et al. 2008; Linder and Rosen

2006). That is, impairments were found relative to the

normative mean on the vocal affect comprehension task,

although the effect size was moderate.

Affect Recognition in ADHD

The ADHD group also performed below the normative

mean on the facial and vocal affect comprehension tasks,

corroborating the extant literature indicating that children

with ADHD are less skilled than their normative peers on

these aspects of social cognition (Corbett and Glidden

2000; Norvilitis et al. 2000; Pelc et al. 2006; Rapport et al.

2002; Singh et al. 1998). The effect sizes were small for

both facial and vocal affect recognition, in contrast to the

moderate to large effects found in the group with ASD.

Thus, these data suggest that the ADHD group, although

less skilled, still perform better than children with an ASD.

Although both groups’ performances are in the average

range, it is still possible that mildly inferior skills in affect

perception may contribute to difficulties in social interac-

tion. Alternatively, it is possible that a subset of children in

each group demonstrated clinically significant impairments

in affect recognition, while others within the group had

intact affect recognition. Further investigations of the

impact of minor difficulties in social perception as well as

symptom-level examination of affect recognition and

social outcome are warranted to inform recommendations

for assessment and treatment.

Group Differences

Results indicated that there were group differences in

performance on all social cognitive tasks and ratings on

both parent and teacher reports of social skills. Specifically,

the ADHD group demonstrated better social skills in all

task conditions when the effects of IQ were systematically

removed. The effect sizes, however, were small in all

conditions, indicating that performance on a variety of

social skills is slightly worse in children with ASD than in

children with ADHD, beyond that which would be

expected by differences in intellectual ability. This finding

is in line with the general diagnostic expectation that

children with ASD generally display greater impairment in

social interaction than children with ADHD. The small

effect sizes contribute to the growing body of literature

suggesting that children with ADHD also display traits of

ASD (Clark et al. 1999; Reiersen et al. 2007; Santosh and

Mijovic 2004) or also have difficulties on social cognitive

tasks. For example, Dyck et al. (2001) reported extremely

similar performance between groups with ADHD

(M = 18.25, SD = 3.82) and Asperger’s Disorder

(M = 18.92, SD = 4.12) on a facial cue recognition task;

however, the performance was not similar to the group with

Autism (M = 12.15, SD = 5.90). Further, Buitelaar et al.

(1999) found that 78 % of children with ADHD were

classified within the PDD-NOS cluster in a discriminant

analysis involving emotion recognition and theory of mind

tasks. The ADHD sample in that study was quite small,

however, (N = 9), as they were part of a larger psychiatric

control group. Also, in that study the children in the ASD

group were described as ‘‘high functioning.’’

Fig. 1 Standard scores on social cognitive tasks across diagnostic groups

J Autism Dev Disord (2013) 43:1157–1170 1165

123

The present results are also consistent with the extant

literature indicating that, although children with both an

ASD and ADHD have weaker social performance skills than

a normative sample, performance of children with an ASD

was significantly worse than the performance of those with

ADHD. For example, Brieber et al. (2007) reported large

discrepancies between groups on ASD symptoms but not

symptoms of ADHD. The measure of ASD symptom pre-

sentation for this study, however, was a parent report ques-

tionnaire rather than a performance measure of social

functioning. Other studies that have examined differences

between ADHD and ASD on parent ratings of autism

symptoms when symptoms are broken down by category

have indicated significant group differences in the area of

social interaction or social skills (Hattori et al. 2006; Jensen

et al. 1997; Luteijn et al. 2000).

Performance Profile Comparisons

Results also indicated a small effect for an interaction

between group and task, suggesting that the discrepancy in

performance between groups was slightly, but significantly

more pronounced on some tasks than others. Specifically,

although the children with an ASD generally demonstrated

weaker performance than the children with ADHD, this

difference in performance was greater on tasks involving

social responding (CASL and TOPS), than on tasks

involving social perception without response. There are

two possible explanations for the greater discrepancy

between groups on this task. If these results were applied to

Crick and Dodge’s (1994) model of social information

processing, receptive social skills, such as the affect rec-

ognition tasks measured by the DANVA-2, would be

necessary to inform and execute an appropriate response.

Because the ASD group performed more poorly at this

lower level of social information processing, the result of

these low level deficits may have a greater impact on

developing skills at the next level.

A second possible explanation for the interaction effect is

the methodological confound between measures of social

perception versus response and outcome. The social per-

ception measures were administered in a recognition format,

requiring a single-word response from the participant to

name the given emotional expression in a face or voice. The

receptive language demands were also minimal, requiring

comprehension of simple instructions and response choices.

The vocal affect recognition task did involve a spoken sen-

tence of neutral content, but because it was the same sentence

for all stimuli, comprehension of the sentence was not nec-

essary for accurate performance on this task. Thus, both

receptive and expressive language demands for this task

were very minimal. Measures of social responding, however,

placed significantly greater language demands on

participants. For example, both the CASL and the TOPS

required participants to comprehend verbally-administered

questions and then generate a verbal response for each item.

Considering the high incidence of language disorder in ASD,

it is possible that the greater performance gap between the

ADHD and ASD groups on these two measures is an artifact

of language abilities rather than social cognitive processes,

specifically. Because language was not assessed in this study,

it is not clear how language abilities impacted the differences

in performance, especially with respect to the measures of

social response, which had the greatest language demands.

While verbal IQ may be a gross estimate of language func-

tion, it may not be sensitive to the specific aspects of lan-

guage that may be differentially impaired in autism. These

more subtle aspects of language require more formal

assessment of language functioning.

Withstanding the failure to control for language abili-

ties, however, the interaction effect is small (partial

g2 = .017), which is an unexpected finding with respect to our understanding of the nature of social deficits in ADHD

and ASD. The fact that the social cognitive profiles of these

two groups are nearly identical with respect to shape, and

differ almost exclusively in terms of severity of impair-

ment, is an unexpected finding. Historically, the social

difficulties in children with ADHD have been considered to

be secondary to symptoms of impulsivity or executive

dysfunction. For example, Barkley (1997) hypothesized

that poor social competence in ADHD is a problem of

execution of social behavior, rather than being related to

problems in social comprehension and knowledge base.

Other researchers have also suggested that social skills

deficits in ADHD are directly related to core symptoms of

ADHD (Greene et al. 1996). Shapiro et al. (1993) tested a

model of social information processing in a group of

children with ADHD. Their results suggested that abilities

were likely intact at the level of stimulus perception and

encoding, and that social difficulties are likely arising at the

level of behavior selection, performance, or regulation,

thereby leading to the hypothesis that the social deficits in

ADHD are secondary to executive dysfunction.

These executive hypotheses of social dysfunction in

ADHD are in direct contrast to the theories of social dys-

function in ASD, which are based upon the notion that

social deficits are primary. Results of this study, however,

suggest that the processes of social dysfunction in ADHD

and ASD are more alike than once thought, as deficits in the

early stages of social information processing (social per-

ceptual deficits, as in affect recognition) were demonstrated

in both groups, which would likely have an impact on

functioning in later stages of the process (social responding

and response evaluation). This raises the question of whe-

ther the underlying causes of the early stage social deficits

are also brought about by the same pathological processes.

1166 J Autism Dev Disord (2013) 43:1157–1170

123

A possible reason for the poor performance of children

with ADHD on affect recognition tasks is that misidentif-

ications are a result of impulsive responding, rather than

impaired social perceptive knowledge. However, if the

errors in facial affect recognition were an artifact of

impulsivity, error patterns would be expected to be ran-

dom, which is in contrast to results of several studies of

ADHD (Marsh and Williams 2006). Further, in a study that

examined reaction times on a static facial affect recogni-

tion task, children with ADHD demonstrated longer reac-

tion times, a finding which is not suggestive of impulsive

responding (Kats-Gold et al. 2007). In a preliminary study

examining visual scanpaths of facial expressions of emo-

tion in ADHD, it was found that individuals with ADHD

demonstrate extensive patterns of scanning evidenced by

longer scanpath lengths (Marsh et al. 2000). Thus, the

evidence to date does not suggest that poor performance on

facial affect recognition tasks in ADHD is not secondary to

inattention or impulsivity; rather, it is likely to be associ-

ated with difficulty in perceptual processing or judgment of

the social stimuli, again, suggesting that the underlying

processes of social perceptual dysfunction may be similar

in ASD and ADHD. Specifically, these findings suggest

that the pattern of social skill deficits is extremely similar

with regard to strengths and weaknesses, and that the dif-

ference between groups is mainly one of severity of skill

deficit rather than type. This is not to suggest that the

difference in severity is trivial. The ADHD group, while

statistically different from the normative sample on all

measures, still performed in what is considered the average

range. Thus, there may be a qualitative difference in the

impact on functional impairment produced by these minor

deficits in social cognition. Alternatively, children with

ADHD do demonstrate poor social outcomes, which could

also indicate that even minor deficits in social cognition

may impact social functioning. Yet another possibility is

that group averages in this study obscured clinically sig-

nificant deficits in some children and intact social func-

tioning in others. Further investigation of the relationship

between functional outcomes and different types and

degrees of social cognitive impairment is warranted.

Nevertheless, these data suggest that strategies designed to

improve social perception skills may be a promising novel

intervention approach that may be effective in improving

the social performance of children not only with an ASD,

but also those with ADHD.

Limitations

Several limitations of the current study must be considered.

First, the homogeneity of the sample with respect to ethnic

background limits the generalizability of these results to a

more diverse population. A second limitation is that

language ability was not systematically assessed in indi-

viduals with ADHD, which precluded the ability to control

for differential effects of language difficulties in ASD.

Because of the greater language demands of some tasks as

opposed to others, it is unclear whether the interaction

effect reported in these results would have reached sig-

nificance if language ability had been controlled beyond

that which was controlled in IQ. For example, the TOPS

and CASL scores may have been more similar between

groups if language had been systematically controlled, as

these tasks had the greatest language demands and also the

largest effect sizes for group differences. Further, greater

performance differences may have been detected between

different subtypes of diagnostic groups and this warrants

investigation in future studies. A third limitation is the

higher percentage of missing data in the ADHD group on

the measures of social judgment and problem solving.

Replication of this study in a research sample with a fixed

battery is warranted. An additional limitation is the inclu-

sion of some mildly impaired individuals with ASD, with

low scores on the ADOS and/or SCQ despite their clinical

presentation and developmental history being consistent

with a diagnosis of ASD. While their inclusion may be

representative of the very mildly impaired individuals on

the Autism Spectrum, it may also have made it more dif-

ficult to detect differences between groups. Finally,

because this study compared participants to the normative

mean using one-sample t-tests, it was not possible to match

groups on IQ for this analysis, which also may account for

the difference in findings.

Future Directions

Despite these limitations, this study is one of the first to

systematically compare social cognitive and social per-

formance skills in children with ASD and ADHD. The

present data show that both groups of children performed

more poorly than a normative group on receptive and

expressive aspects of social skills. Further, the present

findings indicate that the differences in performance

between these two groups appear to be quantitative rather

than qualitative. Results of this study highlight the need for

symptom-level investigations into the etiology of social

dysfunction, as a categorical approach to this research may

not be appropriate to the study of disorders with such

diverse presentations characterized by equifinality. Future

research aimed at modeling systems of social dysfunction

should examine hierarchical models, such as that outlined

by Crick and Dodge (1994). These models should incor-

porate nonsocial perceptual control measures as well as

measures of behavioral regulation, language functioning,

and general intellectual ability. These data also suggest that

strategies designed to improve receptive social skills may

J Autism Dev Disord (2013) 43:1157–1170 1167

123

be a promising new avenue for improving social skills in

children with ADHD (as well as those with an ASD).

Finally, incorporation of neurophysiological and functional

imaging data will further add to understanding of the

neurological processes underlying these deficits.

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