Comparing social cognitive profiles in children with autism and ADHD

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
J Autism Dev Disord (2013) 43:1157–1170 1159
123
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
123
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

123
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
123
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 –

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
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
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.
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
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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c.10803_2012_Article_1657.pdfA Comparison of Social

Cognitive Profiles in children with Autism Spectrum Disorders
and Attention-Deficit/Hyperactivity Disorder: A Matter of
Quantitative but not Qualitative
Difference?AbstractIntroductionReceptive Social SkillsFacial
Affect Processing in ASDFacial Affect Processing in
ADHDVocal Affect Processing in ASDVocal Affect Processing
in ADHDExpressive Social SkillsComparison
StudiesMethodsParticipantsMeasuresDiagnostic
AssessmentIntelligenceAffect RecognitionSocial Problem-
SolvingSocial JudgmentInformant-Report of Social
CompetenceProcedureResultsPreliminary
AnalysesAnalysesDiscussionAffect Recognition in ASDAffect
Recognition in ADHDGroup DifferencesPerformance Profile
ComparisonsLimitationsFuture DirectionsReferences
Article
Are parents identifying
positive aspects to parenting
their child with an intellectual
disability or are they just
coping? A qualitative
exploration
Carole Beighton
Kingston & St. Georges University of London, United Kingdom
of Great Britain and Northern Ireland
Jane Wills
London South Bank University, United Kingdom of Great
Britain and Northern Ireland
Date accepted: 30 May 2016

Abstract
Although acknowledging the stress of raising their child with
intellectual disabilities, parents also
report that their child has brought about many positive changes
in themselves and family. This
study reports what parents perceive to be a positive aspect of
parenting their child, as currently
what constitutes a ‘positive’ is unclear. Seven key themes were
identified; an increased sense of
personal strength and confidence, changed priorities, greater
appreciation of life, pleasure in the
child’s accomplishments, increased faith/spirituality, more
meaningful relationships and the positive
effect that the child has on the wider community. Interpretive
examination of the themes reveals
that the positive aspects identified consist mostly of meaning-
focused coping strategies. These
enable parents to adapt successfully to the stressful experiences
of raising their child and therefore
could be amenable to meaning-focused therapeutic interventions
for parents with newly diagnosed
children or for those unable to identify any positive aspects of
parenting their child.
Keywords
intellectual disabilities, caring, meaning-focused coping,
positive aspects, positive reframing
Corresponding author:
Carole Beighton, Faculty of Health, Social Care and Education,
Kingston & St. Georges University of London, Cranmer
Terrace, London, SW17 0RE, United Kingdom of Great Britain
and Northern Ireland.

Email: [email protected]
Journal of Intellectual Disabilities
2017, Vol. 21(4) 325–345
ª The Author(s) 2016
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Background
Most children with intellectual disabilities live at home with
their parents, with the majority of
parents providing lifelong support for their child (Emerson and
Hatton, 2008). This support can
include direct care (helping with activities of daily living, i.e.
washing or dressing), emotional care
(providing support and encouragement), mediation care
(negotiating with others on behalf of the
individual, i.e. services) and financial care (Horowitz, 1985). In
addition, the child will often
experience long-term chronic conditions and/or complex health-

care needs that will also require
ongoing daily management, time and resources.
This need for lifelong support has led historically to research on
parenting a child with intel-
lectual disabilities to be framed within stimulus-based
orientation to stress models and the medical
model, both of which construct intellectual disability as a series
of functional deficits (Emerson
and Hatton, 2014). Both focus on the child as a ‘negative
stressor’ and report the negative impact or
burden that the child’s impairment(s) have on the parent or
family, including higher levels of
psychological distress, depressive symptoms and poorer general
health than parents of typically
developing children (Miodrag and Hodapp 2010; Woodman and
Hauser-Cram, 2013), with these
poor outcomes increasing with the duration and intensity of the
‘caring’ role (Department of
Health, 2010; Neece and Baker, 2008).
Anecdotal findings of parents reporting ‘positive aspects’ of
parenting in studies exploring
stress were initially seen as denial or as a maladaptive reality
distortion (Affleck and Tennen,

1996), however, although often conceived as reflecting opposite
dimensions, negative and positive
appraisals of the impact of parenting a child with an intellectual
disability have been found to be
independent of each other and can also occur simultaneously
(Hastings and Taunt, 2002; Rapanaro
et al., 2008; Stainton and Besser, 1998).
Positive aspects
The aspects that parents perceive to be positive are difficult to
define as the disability field lacks
theoretical models that address the idea of ‘positivity’ and in
addition, the elements that contribute
to the construct of a positive aspect are complex, not clearly
defined and there is a lack of con-
ceptual clarity leading it to be conceptualized differently
between studies (Blacher and Baker,
2007; Helgeson et al., 2006). Only a few studies have provided
definitions of what a positive aspect
is, ‘any indication that the family or any of its individual
members have benefited as a result of the
child with disabilities’ (Helff and Glidden, 1998: 459) or the
‘belief or conclusion that an adverse
event or circumstance has revealed or evoked positive outcomes
in one’s life’ (Rapanaro et al.,

2008: 35).
In addition, the terms used by researchers to define these
positive aspects are used inter-
changeably, the most common being positive impact(s) (Blacher
and Baker, 2007; Blacher et al.,
2013; Hastings et al., 2002; Lakhani et al., 2013; Scallan et al.,
2011; Stainton and Besser, 1998).
Others variously describe positive perceptions (Baker et al.,
2005; Greer et al., 2006; Hastings
et al., 2002; Hastings and Taunt, 2002; Vilaseca et al., 2013) as
benefits or benefit finding
(Rapanaro et al., 2008; Foster et al. 2010), positive
contributions (Hastings et al., 2005), rewards
(Grant et al., 1998), positive experiences (Kimura and
Yamazaki, 2013), gratifications (Valentine
et al., 1998), positive contributions (Behr et al., 1992; Turnbull
et al., 1988), stress-related growth
(King and Patterson, 2000), transformations (Scorgie et al.,
2001) and positive aspects (Kenny and
McGilloway, 2007).
326 Journal of Intellectual Disabilities 21(4)

The positive aspects that parents identify can refer to actual
changes that they have undergone
or perceptions of change, however, due to the lack of
conceptual clarity this has resulted in a mix of
quantitative instruments and measures being used, generating
results that are difficult to compare.
Meta-analytic findings of benefit finding and growth (across a
wide range of stressful events)
suggest that benefit finding measured ‘sometime’ after the event
reflects actual change or growth
in the person, whereas measuring benefit finding soon after the
event reflects a cognitive strategy
used to reduce stress, however it is conceded that this is
difficult to pinpoint as it appears
researchers are not all studying the same phenomenon
(Helgeson et al. 2006).
Caregivers of older people with dementia who report positive
aspects of caring have been found
to have better self-reported health, less depressive symptoms
and higher caregiving competence
(Basu et al., 2015; Cheng et al., 2013). However, similar studies
about carers supporting older
people express concerns for carers who are unable to identify
any positive aspects of their caring

role; one concluding, ‘carers who cannot identify anything
positive about caring may be at par-
ticular risk for depression and poor health outcomes in addition
to institutionalizing the cared for
earlier than others’ (Cohen et al., 2002: 188), and Nolan et al.
(1996) report that a lack of carer
‘gratification’ could be an indicator of risk of abuse for older
people.
Parents of children with intellectual disabilities spend the
longest time as carers (it is estimated
that 75% of parents have been caring for more than 20 years,
compared to an average of 18.1% for
all carers in England; Emerson et al., 2012), and this has been
shown to impact their well-being.
Therefore, it is important to understand what these parents
perceive to be positive aspects and in
addition whether the positives they describe could be amenable
to therapeutic interventions that
might increase positivity. This could be an important resource
for parents of newly diagnosed
children or for parents who are unable to identify any positive
aspects.
In an attempt to draw conclusions about the nature of the
‘positive perceptions’, Hastings and
Taunt (2002) compared five studies where parents were asked to

describe ‘the positive impact that
a child with a disability can have on the family’ and identified a
framework of 14 key positive
themes. Despite differing sample sizes, methodologies and ways
of conceptualizing positive
perceptions and experiences, they found consistent themes
identified across all the studies as
shown in Table 1.
It has been posited, however, that parents are not actually
identifying positive aspects of par-
enting their child per se, but the positives they describe are
adaptive coping mechanisms in which
they engage in positive reframing, one of the most common
components of meaning-focused
coping (Hastings et al., 2002; Park and Folkman, 1997). Some
do not support this assumption
and argue that these benefits are not artifacts of cognitive
coping mechanisms (Greer et al., 2006;
Stainton and Besser, 1998; Taylor, 1983) and that if a parent
reports benefits, ‘we should take them
at their word’ (McConnell et al., 2015: 1).
Meaning-focused coping
Coping is a response aimed at ‘diminishing the physical,

emotional and psychological burden that
is linked to stressful life events . . . ’ (Snyder and Dinoff, 1999:
5) and the transactional model of
stress and coping (Lazarus and Folkman, 1987) highlights the
cognitive and emotional aspects of
the person experiencing the stress with the appraisal and coping
process central to this perspective.
This model includes ‘positive psychological states’ which are
the result of meaning-focused
coping strategies that involve searching for ‘a more favorable
understanding of the situation and
Beighton and Wills 327
its implications’ (Park, 2013: 40) and has been widely adopted
for use in studies of families of
children with intellectual disabilities (Grant et al., 1998).
Within meaning-focused coping, positive reappraisal (also
referred to as positive reframing,
positive cognitive restructuring and benefit finding) is the most
commonly used strategy. Pos-
itive reappraisal is a way of viewing and experiencing the
stressful events, ideas, concepts and
emotions in order to find more positive alternatives; for
example, deciding that there are ‘more

important things in life’, ‘something a lot worse could happen’
or ‘finding a silver lining’ (Hill
Rice, 2012; Troy et al., 2010). In quantitative studies, positive
reappraisal was found to be a
significant independent predictor of positive perceptions in
mothers of children with an intel-
lectual disability after controlling for other factors such as
social support and degree of care
required (Hastings et al., 2002).
‘Meaning’ is described as ‘making sense, order or coherence out
of one’s existence’ (Reker
et al., 1987: 44). Meaning-focused coping is based on the
assumption that individuals experience
stress when they perceive discrepancies between their appraised
meaning of a particular situation
(degree of threat, harm, controllability, implications) and their
global meaning (fundamental
assumptions of life, values, goals, beliefs, desires) (Park and
Folkman, 1997). For example, most
parents assume that their child will be healthy and follow a
normal development pattern and the
diagnosis of intellectual disability is likely to violate their
beliefs about the fairness of why this has

happened to them. Most will be faced with how to resolve the
incongruence between their global
and appraised meaning. This will require them to reevaluate
their hoped-for future life goals, plans
and priorities, and this incongruence may be changed by
searching for a more favourable
understanding of the situation, reducing the mismatch between
situational and global meaning
(Park, 2013).
Other strategies used in meaning-focused coping includes
benefit reminding (making an
intentional effort to recall previously found benefits), adaptive
goal processes (revising goals and
planning goal-directed problem-focused coping that fosters
meaning in terms of purpose and
control), reordering of priorities (value-based process where
aspects of life move up or down the
priority ladder) and activating spiritual beliefs and experiences
through which individuals find
existential meaning (Park, 2011).
Table 1. Positive perceptions identified by parents: Themes
across five studies (Hastings and Taunt 2002: 118).
� Pleasure/satisfaction in providing care for the child
� Child is a source of joy/happiness

� Sense of accomplishment in having done one’s best for the
child
� Sharing love with the child
� Child provides a challenge or opportunity to learn and
develop
� Strengthened family and/or marriage
� Gives a new or increased sense of purpose in life
� Has led to the development of new skills, abilities or new
career opportunities
� Become a better person (more compassionate, less selfish,
more tolerant)
� Increased personal strength or confidence
� Expanded social and community networks
� Increased spirituality
� Changed one’s perspective on life (clarified what is important
in life, more aware of the future)
� Making the most of each day, living life at a slower pace
Over the past 20 years there has been a small body of literature
that has recognized the positive
contributions, rather than the negative effect, a child with an
intellectual disability makes to the
family (Hastings and Taunt, 2002). However, exploring what
parents describe or perceive to be
positive and the factors surrounding their occurrence requires
further investigation in order to
understand this phenomenon more fully.

Aim of study
The aim of this study is to explore what parents perceive to be
the positive aspects of parenting
their child with intellectual disabilities. Its objective is to
clarify the nature of any positive aspects
that parents describe. Secondary objectives are to ascertain if
any positive aspects identified arise
from parents reframing their experience, which could be
considered meaning-focused coping stra-
tegies or if there is a discourse of parenting a child with
intellectual disabilities which is positive.
Methods
This qualitative study was undertaken as the first phase of a
sequential mixed methods study
(Creswell and Clark, 2007) and is underpinned by the
philosophy of pragmatism (Biesta, 2010).
One of the fundamental components of pragmatism is that it is a
process of ‘knowing’ the current
situation and through action re-shaping a new reality (Hartrick
Doane and Varcoe, 2005).
Ethical approval for this study was granted from the London
South Bank University research
ethics committee in September 2013 (UREC 1338). Face-to-face
semi-structured interviews were

considered most appropriate as they would be more convenient
for carers and allow them to
respond to guided questions (Kvale, 2007; Mays and Pope,
2008) and were undertaken by the first
author. The parents’ own characteristics and attributes and the
wider social/psychological envi-
ronment were then explored through a series of questions
included in the interview schedule (Box
1). The interviews were audio-recorded and following each
interview field notes were written
which included the researcher’s reflections.
The audio files were transcribed verbatim, reviewed for
accuracy and potential identifying
features were anonymized. The data were then analysed using a
thematic analysis (Braun and
Clarke, 2006) to identify key themes at a semantic level which
Boyatzis (1998) describes as not
looking beyond what the participant has said. As the first author
had already undertaken a
systematic literature review on the positive aspects of parenting,
it was important, while
undertaking the data analysis, to avoid the unconscious ‘seeing’
of data that researchers expect to

find (Crabtree and Miller, 1999) and also not to force the data
into preconceived categories,
affecting the confirmability of the findings. Multiple readings
of the transcripts and field notes
took place and annotations were added prior to coding. Coding
was initially a phrase or a single
word that captured the ‘essence’ of what a positive aspect might
be and was undertaken first in
individual transcripts and then across all 17 transcripts. Areas
of consensus began to emerge and
cluster as themes in relation to the research question, and the
themes were then further clustered
and assigned succinct phrases to describe the meaning that
underpinned each theme. The ade-
quacy and appropriateness of the themes were subject to
interpretive rigour (Ezzy, 2002) as these
were checked by two other researchers and any discrepancies or
disagreements led to all the
research team reading the transcript together and agreeing a
coding and theme, increasing the
credibility and trustworthiness of the data interpretation.
Following this analysis, the secondary
objective of whether these themes could be considered meaning-
focused coping strategies was

Beighton and Wills 329
explored at an interpretive level (Boyatzis, 1998) by
scrutinizing the ‘broader meanings of the
themes’ (Patton, 2002).
Participants
Fourteen mothers and five fathers (includes two couples) were
recruited through learning disability
partnership boards and local MENCAP (a leading charity for
people with ID) organizations from
London boroughs between October 2013 and March 2014.
Inclusion criteria for the parent par-
ticipants were that the child they supported had a diagnosis of
intellectual disability, parents had to
communicate using English language, be aged over 18 years and
that the child was over 5 years of
age and lived in the same household. Between them the
participants parented 10 males and 9
females who had a diverse range of intellectual and associated
physical disabilities with two
families containing more than one child with intellectual
disabilities. Table 2 provides a summary
of the characteristics of the participants and their child

(children) at the time of the interview.
Findings
All but one parent chose to be interviewed in their own home
and each interview lasted approx-
imately 1 h. Despite the focus of the interviews being to
identify the positives of parenting a child
with intellectual disabilities, in every interview a much larger
proportion of time was spent by the
parent talking about the negative aspects of parenting their child
which is consistent with other
qualitative studies, (Foster et al., 2010; Rapanaro et al., 2008;
Skotko et al., 2011). However, only
the positive aspects will be reported here. Six of the
overarching themes identified were broadly
similar across the framework of positive themes identified by
Hastings and Taunt (2002) however,
one theme was identified from this study which had not been
identified by them, the positive effect
the child has on others.
The seven key themes identified covered three broad areas.
Intrapersonal factors, those which
have a direct influence on the parent themselves (increased
personal strength, changed priorities, a

greater appreciation of life, increased spirituality/religiosity),
interpersonal factors; factors that
relate to aspects which exist between persons (more meaningful
relationships with others, the
positive effect the child has on others) and one factor where the
child is the source of positivity, the
child’s accomplishments. These themes were identified in the
transcripts of all parents irrespective
of their gender or the age of the child.
1. Tell me about yourself . . .
2. Can you tell me about your child?
3. Can you describe to me in which ways [child’s name] had a
positive impact on you or
your family?
4. What makes these ‘positives’ meaningful for you?
5. Are there other words or a term you would use instead to
describe the(se) ‘positive
aspects’?
6. In your experience, do/can these positive aspects change over
the time/years you spend
caring?
Box 1. Interview schedule.

T
a
b
le
2
.
S
u
m
m
ar
y
o
f
th
e
ch
ar
ac
te
ri
st
ic

s
o
f
th
e
p
ar
ti
ci
p
an
ts
an
d
th
e
ir
ch
ild
(c
h
ild
re
n
).
P

ar
e
n
t
C
h
ild
/a
d
u
lt
w
it
h
ID
N
o
A
ge
G
e
n
d
e
r
E
th

n
ic
it
y
M
ar
it
al
S
ta
tu
s
O
cc
u
p
at
io
n
A
ge
G
e
n
d

e
r
D
ia
gn
o
si
s
P
o
si
ti
o
n
in
F
am
ily
1
6
2
F
B
ri
ti
sh

M
ar
ri
e
d
R
e
ti
re
d
4
3
F
G
D
D
/P
h
ys
ic
al
d
is
ab
ili
ti

e
s
O
n
ly
ch
ild
2
5
3
,
4
0
M
,
F
C
au
ca
si
an
M
ar
ri
e
d

U
n
e
m
p
lo
ye
d
/
ca
re
r
1
5
,
1
3
M
,
M
B
o
th
G
D
D
,
p

lu
s
o
n
e
al
so
h
as
A
S
D
S
e
co
n
d
an
d
th
ir
d
o
f
fi
ve

ch
ild
re
n
3
6
4
F
W
h
it
e
S
o
u
th
A
fr
ic
an
D
iv
o
rc
e
d

/
si
n
gl
e
R
e
ti
re
d
1
2
F
A
S
D
O
n
ly
ch
ild
(g
ra
n
d
d

au
gh
te
r)
4
6
3
,
6
4
M
,
F
C
au
ca
si
an
M
ar
ri
e
d
R
e
ti

re
d
3
4
M
S
p
in
a
b
if
id
a,
h
yd
ro
ce
p
h
al
u
s
Y
o
u
n
ge

st
o
f
3
5
7
0
F
C
au
ca
si
an
M
ar
ri
e
d
R
e
ti
re
d
7
M
A

S
D
O
n
ly
ch
ild
(g
ra
n
d
so
n
)
6
4
5
F
C
o
lu
m
b
ia
n
D

iv
o
rc
e
d
/
si
n
gl
e
F
u
ll-
ti
m
e
ca
re
r
1
2
F
A
S
D

O
n
ly
ch
ild
7
3
3
F
T
u
rk
is
h
M
ar
ri
e
d
F
u
ll-
ti
m
e
ca

re
r
7
,
7
M
,
M
G
D
D
,b
lin
d
,o
n
e
al
so
p
ar
ti
al
ly
d

e
af
O
n
ly
ch
ild
re
n
(t
w
in
s)
8
4
0
M
A
si
an
M
ar
ri
e
d

U
n
e
m
p
lo
ye
d
1
0
F
G
D
D
Y
o
u
n
ge
st
o
f
th
re
e
9
5

9
F
C
au
ca
si
an
M
ar
ri
e
d
U
n
e
m
p
lo
ye
d
3
3
F
W
ill

ia
m
s
sy
n
d
ro
m
e
Y
o
u
n
ge
st
o
f
tw
o
1
0
6
8
M
C
au
ca

si
an
M
ar
ri
e
d
R
e
ti
re
d
3
2
M
D
o
w
n
sy
n
d
ro
m
e

Y
o
u
n
ge
st
o
f
th
re
e
1
1
4
9
F
Ja
m
ai
ca
n
S
in
gl
e
E

m
p
lo
ye
d
fu
ll-
ti
m
e
2
5
M
G
D
D
an
d
A
S
D
O
n
ly
ch

ild
1
2
6
0
F
A
u
st
ra
lia
n
S
in
gl
e
F
u
ll-
ti
m
e
st
u
d

e
n
t
3
6
F
B
lin
d
an
d
A
S
D
Y
o
u
n
ge
st
o
f
tw
o
1
3

5
1
F
C
au
ca
si
an
M
ar
ri
e
d
E
m
p
lo
ye
d
p
ar
t-
ti
m
e

2
7
M
C
h
ro
m
o
so
m
al
ab
n
o
rm
al
it
y
Y
o
u
n
ge
st
o
f
tw

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