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Autism Spectrum Symptomatology in Children:
The Impact of Family and Peer Relationships
Adrian B. Kelly & Michelle S. Garnett & Tony Attwood &
Candida Peterson
Published online: 25 April 2008# Springer Science + Business Media, LLC 2008
Abstract This study examines the potential impact of
family conflict and cohesion, and peer support/bullying onchildren with autism spectrum disorder (ASD). While such
impacts have been established for a range of non-ASD
childhood disorders, these findings may not generalize to
children with ASD because of unique problems in
perspective-taking, understanding others’ emotion, cogni-
tive rigidity, and social reasoning. A structural model-
building approach was used to test the extent to which
family and peer variables directly or indirectly affected
ASD via child anxiety/depression. The sample ( N =322)
consisted of parents of children with ASD referred to two
specialist clinics. The sample contained parents of children
with Autistic Disorder (n =76), Asperger Disorder (n =188),
Pervasive Disorder Not Otherwise Specified (n=21), and
children with a non-ASD or no diagnosis (n=37). Parents
completed questionnaires on-line via a secure website. The
key findings were that anxiety/depression and ASD
symptomatology were significantly related, and family
conflict was more predictive of ASD symptomatology than
positive family/peer influences. The results point to the
utility of expanding interventions to include conflict
management for couples, even when conflict and family
distress is low. Further research is needed on the potentially
different meanings of family cohesion and conflict for
children with ASD relative to children without ASD.
Keywords Autism spectrum disorder . Asperger ’s
syndrome . Autism . Family . Peers . Conflict . Support
Introduction
Early prevalence studies based on small samples indicate
that ASD affects between 36 and 48 children per 10,000
(Ehlers and Gillberg 1993; Kadesjo et al. 1999), however
recent reviews are more conservative (2.6 per 10,000;
Fombonne 2007). ASD often produces difficulties with
conversation and formation of friendships (Asperger 1944,
1979). Children with ASD have particular difficulty
understanding and using the rules governing social behav-
iors (Wing 1981, 1992) and with using and interpreting
nonverbal social and conversational cues (Ehlers and
Gillberg 1993; Gillberg and Gillberg 1989; Szatmari et al.
1989). Children with ASD may be over-literal in interpre-
tation (Ehlers and Gillberg 1993), often display intense
preoccupations with narrowly specific interests (Attwood
2003; Myles et al. 2001), and may have ritualized behavior
and experience distress at small changes to routine (Attwood
2006). Hyper- or hypo-sensitivity to auditory, olfactory,
tactile, or visual stimuli are also commonly reported
(Dunn et al. 2002; Rogers and Ozonoff 2005) and there
may be motor coordination problems (Gillberg and Gillberg
1989).
Under the ASD umbrella is included Autistic disorder,
Asperger disorder (commonly considered equivalent to
high functioning autism; Gilchrist et al. 2001; Mayes and
Calhoun 2001), and Pervasive Developmental Disorder Not
Otherwise Specified (PDDNOS; DSM-IV-TR; APA 2000).
J Abnorm Child Psychol (2008) 36:1069 – 1081
DOI 10.1007/s10802-008-9234-8
A. B. Kelly
School of Social Science, The University of Queensland,
Brisbane, Australia
M. S. Garnett : T. Attwood : C. Peterson
School of Psychology, The University of Queensland,
Brisbane, Australia
A. B. Kelly (*)
School of Social Science, The University of Queensland,
St Lucia, QLD, Australia
e-mail: [email protected]
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These ASD subtypes are diagnosed on the basis of
qualitative impairments in social interaction and communi-
cation, and stereotyped/repetitive behaviours (APA 2000).
The subtypes are thought to exist on a severity continuum,
with children with Autistic disorder showing greater
impairment than children with Asperger disorder in social
interaction, communication, and repetitive behaviours
(Gilchrist et al. 2001; Howlin 2003; Iwanaga et al. 2000;Ozonoff et al. 2000). PDDNOS includes children who have
features of Autistic disorder and Asperger disorder but do
not meet full criteria for the latter categories. Persons with
Autistic disorder are commonly characterised by develop-
mental delay of speech and low intelligence (IQ< 70),
though a diagnosis of Autistic disorder can be made
without reference to language delay (Lord et al. 1997).
Children with Asperger disorder generally have IQs greater
than 70 and have no clinically significant delay in cognitive
and language development (Verté et al. 2006). For the
purposes of the present study, we examined the links
between family/peer functioning and ASD symptomatology by including children with all three ASD subtypes, given
evidence that these subtypes appear to exist on a continuum
of severity.
There is very little known about the extent to which
children with ASD are affected by their family and peer
environments. Interpersonal relationships have long been
thought to be important in both diminishing and increasing
psychological and physical health in vulnerable people (e.g.,
Burman and Margolin 1992; Kiecolt-Glaser et al. 2003).
Positive family/peer relationships can buffer the individual
against stress (Cohen and Wills 1985), and negative family/
peer relationships can add to the stress and adjustment
problems of the individual. Burman and Margolin propose
that a key mechanism by which families impact on
individual health is via the buffering/exacerbating effects
of relationship quality on anxiety/depression.
While the above theorists concentrated on the effects of
family/peer relationships on adult anxiety/depression, there
is broad support for the utility of these models for children.
Among community samples of children, those who are
subject to peer victimization typically suffer poor anxiety/
depression outcomes (Hawker and Boulton 2000), and
children who are in conflictual families are more liable to
develop depression (Rice et al. 2006). There is also
evidence that having high quality peer and family relation-
ships characterised by closeness and support provides a
buffer for children, lowering the likelihood of developing
depression or anxiety (e.g. Bollmer et al. 2005; Bukowski
et al. 1994; Hay et al. 2004; Kashani et al. 1995).
Furthermore, family relationships can affect the anxiety/
depression of children with neurodevelopmental disorders
other than ASD. For example, high family conflict, low
family cohesion and punitive – authoritative parenting have
been linked with increased severity and co-morbidity in
children with attention deficit disorder (e.g., Biederman et
al. 1995, 2002; duPaul et al. 2001), obsessive compulsive
disorder (Apter et al. 1984; Bolton et al. 1983; Piacentini
et al. 2003; Toro et al. 1992), and mood disorders (Rice et
al. 2006).
Family interactions may influence and be influenced by
ASD symptomatology in children. Most research on thisissue has focused on the impact of ASD on parent well-
being. Families with children with ASD report high levels
of stress (Rodrigue et al. 1990; Sanders and Morgan 1997;
Sharpley et al. 1997), and parents of children with ASD
show increased rates of depression (e.g. Benson 2006;
Bristol 1987; Dumas et al. 1991; Sharpley et al. 1997)
relative to parents of children with other disorders. Very
little research has examined the potential effects of family
interactions on children with ASD. The research that is
available mostly comes from the therapeutic literature. For
example, parental mental health has improved in concert
with children’s symptomatology and mental health as aresult of parental training directly addressing the core
characteristics of autism (Solomon et al. 2004; Tonge et
al. 2006). In outcome studies of Applied Behavioural
Analysis (ABA; Lovaas 1987), parental stress was associ-
ated with fewer improvements in core characteristics of
autism in their children (Gabriels et al. 2001; Luiselli et al.
2000; Ozonoff and Cathcart 1998). Caution is warranted
because intervention studies often involve changes in many
variables, and there is little direct research testing the nature
and degree to which family relationship quality impacts on
children with ASD. There is also no research exploring the
degree to which family relationship quality, anxiety/
depression, and child ASD symptomatology are related.
A similar conclusion is reached from available research
on peer relationship quality and children with ASD.
Bauminger and Kasari (2000) found that children with
ASD had poorer quality friendships and more loneliness
than children without a clinical diagnosis. Receipt of
bullying is four times higher for children with ASD
compared to other children (Little 2002), and peer-mediated
interventions for children with ASD result in reduced social
impairment (Kamps et al. 2002; Pierce and Schreibman
1997; Sasso et al. 1987). However, the hypothesis remains
to be tested that peer relationship problems are a source of
anxiety/depression, and this in turn is associated with ASD
symptomatology.
There is cause to question whether more general findings
on the impact of family and peer on child anxiety/
depression generalize to children with ASD. Family/peer
interactions may have different effects on the levels of
anxiety/depression experienced by children with ASD
relative to other groups, given that successful family/peer
interactions frequently require socio-emotional skills that
1070 J Abnorm Child Psychol (2008) 36:1069 – 1081
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are limited or absent in children with ASD. Recent research
has established five core socio-emotional problems among
children with ASD: Understanding and expressing emotion,
perspective-taking, sensory sensitivity, rigidity, and orien-
tation towards exclusive and narrow areas of knowledge
(Garnett et al. 2008, manuscript under review). Difficulties
in these areas are likely to impede the child’s engagement
in rewarding and supportive family/peer relations andcapacity to effectively cope with negative family/peer
events. For example, children with ASD may be especially
sensitive to family conflict, given their problems with
cognitive/behavioral rigidity, sensory sensitivity, and per-
spective taking. Problems with expressions of affection and
closeness may also be apparent, given that children with
ASD have difficulties with understanding and expressing
emotion. Consistent with this, expressions of affection/love
by family members and concepts of friendship may be
confusing for children with ASD (e.g. Bauminger et al.
2003; Berthoz and Hill 2005; Hill et al. 2004; Happé and
Frith 1996; Howard et al. 2006; Nieminen-von Wendt 2004; Rastam et al. 1997; Tani et al. 2004). Also,
researchers and clinicians have noted that these children
have less need for interpersonal closeness, tend not to seek
assistance from others for their problems, and tend not to
see people as part of a potential solution to their problems
(Attwood 2006; Berthoz and Hill 2005; Dunn et al. 2002;
Harrison and Hare 2004; Hill et al. 2004).
The overall aim of this study was to test an integrated
multivariate model of family and peer relationships that
may exacerbate/ameliorate ASD symptomatology and
anxiety/depression in children with ASD. More specifically,
structural equation models were used to test the fit of peer
and family variables in the explanation of associations
between ASD and anxiety/depression. An innovation of
this research was that we considered positive and negative
dimensions separately given that in the couples/family
literature, there is increased acknowledgement of the
nonorthogonality of these dimensions (Fincham 2003),
and that positive relationship experiences can moderate
the impact of negative relationship experiences (Fincham
2003; Kelly et al. 2003). By using a model building
approach in which positive and negative dimensions are
separately considered, the relative contribution of these
dimensions could be evaluated. The key family-related
variables were conflict and support given that these are
among the best longitudinal predictors of stability, satisfac-
tion, and health of families (Bradbury et al. 2000; Collins et
al. 1993). We also focused on peer bullying and rewarding
friendships given the well-established association of these
with child adjustment (Bollmer et al. 2005; Hay et al.
2004). There were several potentially confounding varia-
bles that might account for any significant relationships
between family conflict/support, anxiety/depression, and
ASD symptomatology, including intellectual impairment,
language impairment, ASD diagnoses in the parents/
siblings, and gender. Child intellectual/language impair-
ment is known to increase child and family stress (Dumas
et al. 1991), multiple ASD diagnoses within families may
compound communication problems within families, and
there are established gender effects for childhood anxiety/
depression. Inclusion of these potential confounds permitteda clearer evaluation of associations between family factors,
child anxiety/depression, and ASD symptomatology.
The specific hypotheses were:
Hypothesis 1 There will be a significant positive
relationship between the child’s anxiety/
depression and ASD symptomatology.
Hypothesis 2a/2b Family conflict/peer victimization will
indirectly predict ASD symptomatolo-
gy via anxiety/depression.
Hypothesis 3a/3b Family cohesion/positive friendships will
indirectly negatively predict ASD symp-tomatology via anxiety/depression.
Hypothesis 4 Given that children with ASD are likely
to find family conflict particularly dis-
tressing and may have limited capacity
to understand and utilize the benefits of
friendship, negative peer and family
relationships will have a greater effect
on anxiety/depression than positive
relationships.
Method
Sample
All children included in the study had been referred to two
clinics specializing in pervasive developmental disorders
for diagnostic assessment because their caregiver/s or
teacher/s suspected that the child had ASD. Children were
included in the study if they had received an ASD diagnosis
[Autistic disorder (n=76), Asperger disorder (n=188),
PDDNOS (n =21)]. The sample also included a small
number of referred children who had elevations in social
cognitive dimensions of the ASASD (see Measures; Garnett
et al. 2008, manuscript under review) relative to a normal
control group [greater than two standard errors above the
normal control) but who were not diagnosed as having
ASD (n =37). This group was included because (a)
differential ASD diagnosis was not central to this study
and we conceived ASD symptomatology as varying from
low severity (i.e., subclinical) to high severity (i.e., as is
often the case with Autistic disorder), (b) maximal variance
in ASD symptomatology was needed to detect relationships
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between this variable and family/peer relationships, and (c)
because we wanted to maximize statistical power to pick up
statistically significant relationships within the models. The
age range of participants was limited to 6 – 16 years old.
Included children had generally received their diagnosis
during their first appointment in one of the clinics during
the years 2003 – 2006.
Differences in sociodemographic and family variablesaccording to gender and diagnostic group (Autistic disor-
der, Asperger disorder, PDDNOS, other/none) were tested
using a 2×3 MANOVA. The dependent variables included
age, socioeconomic status (SES) of the family, and number
of siblings in the family. The main effects and interaction
terms were nonsignificant for age, number of siblings, and
SES. The mean age of the total sample was 10.9 years (SD=
2.9), the mean number of siblings was 1.6 (SD=2.9), and
the mean SES was 2.8 (SD=1.6; see Measures). Consid-
eration was given to systematic differences in intelligence
across groups. Formal IQ testing was not conducted
because 92% of children had completed a formal IQ test (parent report) and resources precluded such large scale
IQ testing. 21% of those who had completed an IQ test
(n =62) were reported by parents to have previously
received a diagnosis of intellectual impairment (IQ
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310 cases the number was no longer current. In these cases
the family name was consulted in the telephone directory
over the internet and in 66 cases the family was located. In
total 856 families were successfully contacted. Initial
agreement was excellent with 850 parents agreeing to
participate, n(autism)=150, n(Asperger disorder)= 408, n
(clinical non-ASD)= 57, n(other/none)=80). If families
agreed to participate but had not completed the questionnaireswithin one month a reminder telephone call was made.
Questionnaire completion rates following telephone agreement
was 51%, 46%, 37% and 46% for families in which the child
had a diagnosis of Autistic disorder, Asperger disorder,
PDDNOS and other/none, respectively. As with most clinical
studies, pathways to participation can create biases in the final
sample. For example, those who choose to participate may be
more organized, have less pathology, or may show other
features such as greater perceived need for assistance. Because
the sample was drawn from client records there was the
potential to gather information about those who chose not to
participate, to gain information on the potential biasesassociated with pathways to participation. Because consent for
the use of data in this way was not obtained, we did not do this.
Parents were given a choice between paper and web
versions of the questionnaires. All parents who agreed to
participate in the study were sent a covering letter, which
gave information about the anonymity of the study and
consent issues, and advised parents of their PIN number,
password and directions to find and negotiate the website.
Participants were provided further assistance if required via
telephone contact. The website contained a login page,
information about the study, and the on-line questionnaires.
The website was designed so that people without a PIN
number and password were unable to access the website,
and the password uniquely identified each research partic-
ipant. Since the entire battery of questionnaires took 1 –
1.5 h to complete, the website design allowed participants
to login and submit each questionnaire individually, thus
giving the option of completing the questionnaires in
stages. For each questionnaire all items had to be completed
to allow successful submission, thus forcing choice and
minimizing missing data. Permission to use questionnaires
in this study was kindly granted by the authors of
questionnaires. Incoming data was temporarily stored on
the website then downloaded and de-identified. In cases
where all questionnaires had been completed, a letter of
thanks was sent to the participant. If any data was absent, a
thank-you letter was sent that included a paragraph to request
that the participant complete the remaining questionnaire/s.
Measures
ASD symptomatology The Australian Scale for Autism
Spectrum Disorder (ASASD; Garnett et al. 2008, manu-
script under review) was used to measure ASD symptom-
atology. The ASASD consists of 46 items measuring five
dimensions of ASD — understanding emotion, perspective
taking, sensory sensitivity, cognitive and behavioral rigid-
ity, and fact-orientation (7-point Likert Scale rating from 0
‘much less than a typical child’ to 7 ‘much more than a
typical child’). This measure is completed by the target
child’s parents. The five individual scales show a clear factor analytic structure, load highly and uniformly on a
second-order factor ASD symptomatology, and the sub-
scales strongly differentiate children with ASD from non-
clinic children (omitted for masked review). The intraclass
correlation coefficients (ICC) for 2-week retest data (Griffin
and Gonzalez 1995) are generally high [ICC (fact oriented)=
0.83, ICC (sensory sensitivity) =0.84, ICC (perspective
taking)= 0.85, ICC (rigidity)= 0.90, ICC (understanding
emotion)=0.52, and the ASAS-R total score (ICC=0.86).
The ASAS-R correlates well (r =0.56) with a theoretically
related and established measure, the Autism Spectrum
Screening Questionnaire (Ehlers et al. 1999), and three of the subscales scores (understand emotion, fact-oriented ,
and sensory sensitivity) and total score are significantly
higher for children with ASD compared to subclinical
children after adjusting for family-wise error rate (Garnett
et al. 2008, manuscript under review). The derived measure
(observed variable) of ASD symptomatology was the
weighted total score on the ASASD. Weightings for the
five factors were based on factor analyses reported
elsewhere (omitted for masked review) and were 0.50 for
understand emotion, 0.48 for fact oriented , 0.52 for sensory
sensitivity, 0.65 for perspective taking , and 0.63 for rigidity.
Family relationship variables To measure conflict and
cohesion, the two so-named subscales of the Family
Environment Scale — Real Form (FES-R; Moos and Moos
1994) were used. The two subscales each consist of nine
items (e.g., conflict subscale: “We fight a lot in our
family”, “Family members sometimes get so angry they
throw things”; cohesion subscale: “Family members really
help and support one another ”, “There is plenty of time
and attention for everyone in our family”) and items are
rated as true or false. Coefficient alphas for cohesion and
conflict are 0.69 and 0.70, and confirmatory factor
analysis of the six key subscales show moderate to high
factor loadings and good fit (Sanford et al. 1999). The
convergent validity of the cohesion and conflict subscales is
indicated by significant correlations with a range of
established measures of related constructs [e.g., the Family
Adaptability and Cohesion Evaluation Scale (Olson et al.
1982) and the Conflict Tactics Scale; Straus 1979)]
(Sanford et al. 1999). The derived measures of conflict
and cohesion were the total scores for each of these
subscales.
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Peer relationship variables Positive peer relationship qual-
ity was measured using the Spence Social Competence
Questionnaire — Parent Form (SCQ; Spence 1995), which
consists of a 9-item scale assessing the extent of rewarding
social relationships (e.g., “has at least one close friend”, has
good relationships with classmates”). Questions are rated
on a 3-point scale (0 ‘not true’, 1 ‘sometimes true’, and 2
‘mostly true’). The derived measure of positive peer relationships was the total score on this measure. The
SCQ was standardized on Australian parents of children
and adolescents, and it has high internal consistency
(coefficient alpha=0.81; Spence 1995).
The Bullying and Teasing Questionnaire (BTQ) was
developed by the authors on the basis of Rigby’s (1996)
formulation of bullying and teasing. The BTQ consists of
15 items measuring the extent to which the child is
victimized, engages in victimization, and copes with
victimization (five items each). Parents rate how often the
child is subject to/perpetuates/copes with physical bullying,
name calling, sexual harassment, deliberate exclusion, andcruel teasing (four-point scale from 0 ‘rarely or never ’ to 4
‘very often’. Our research indicates that the scale has
excellent internal consistency (ά=0.93) and good conver-
gent validity. The derived measure of peer victimization
was based on the total score for the first and third subscales.
Anxiety/depression The emotion subscale of the Strengths
and Difficulties Questionnaire — Parent Form (SDQ-P:
Goodman 2001) was used as the derived measure of
anxiety/depression. The emotion subscale consists of five
items (e.g., “many worries, often seems worried”, “often
unhappy, down-hearted, or tearful”) each rated on a three-
point scale (0 ‘not true’, 1 ‘somewhat true’, 2 ‘certainly
true’). Developed for assessing the psychological adjust-
ment of 3 – 16 year olds (Goodman 2001), the SDQ-P has
adequate inter-rater reliability (r =0.62), internal consisten-
cy was adequate (ά=0.67), and emotion subscale scores
correlate with DSM-IV diagnoses of anxiety/depression
(Goodman 2001). This measure was used in preference to
the widely-used and validated Child Behavior Checklist
(CBCL; Achenbach 1991) because the SDQ appears at least
as good as the CBCL in detecting internalizing problems
(e.g., anxiety/depression) but has far fewer items (Goodman
and Scott 1999). [ Note — the SDQ has a ‘ peer problems’
subscale but this was not used to measure peer victimiza-
tion because this subscale has poor internal consistency
(0.41; Goodman 2001)].
Other Measures
Formal intelligence testing was not conducted because 92%
(n=296) of children had previously completed some form
of intelligence assessment by a health/education profes-
sional (based on parents’ reports) and resources precluded
such large scale IQ testing within the clinic (2 – 3 h per
child). For the purposes of this research, a derived measure
of intellectual impairment was based on the presence/
absence of a formal IQ test score of less than 70 as reported
by the parent. For children who had not previously
conducted an IQ test, intellectual impairment was basedon language impairment scores (see below). An imputed
value of intellectual impairment (coded 1) was used if
language scores were in the bottom half of the distribution
of language impairment scores. For the purposes of
controlling for the potential confound of language impair-
ment, a short measure was developed for use in this study.
The derived measure of language impairment consisted of
the total score from five supplementary questions (yes/no)
that assessed whether the child had speech, whether the
child used two to three word utterances only, had immature
grammar and syntax, and/or poor comprehension of
language. Parents reported on the presence or absence of an ASD diagnosis for themselves or their partner, and for
other siblings. From these reports, two derived measures
were created — presence of ASD diagnosis in one or both
parents (yes/no), and presence of ASD diagnosis in one or
more siblings of the identified child (yes/no). Socioeco-
nomic status was measured using a revised form of
Congalten and Daniel’s (1976) seven-point Likert scale,
which ranges from ‘1’ unemployed to ‘7’ professional. This
scale is a reliable and valid index of the SES of Australian
families (Kelly et al. 2006).
Statistical Procedure
Hypotheses 1 – 4 were tested using structural equation
modeling (AMOS 6.0, SPSS 2005). To conduct these tests,
a model building approach was used. The model building
moved from simple to complex. Nonsignificant pathways
between observed/unobserved were removed from all later
complex models on the basis that respecification to a
simpler form is justified when pathways are nonsignificant.
Secondary variables (i.e., potential confounds not central to
the hypotheses) included age of child, intellectual impair-
ment (1 ‘ present ’ 0 ‘absent ’), language impairment, siblings
with ASD (0 ‘no siblings with ASD’ 1 ‘one or more’), and
gender (1 ‘male’ 2 ‘female’) were included as observed
variables in all models (parental ASD diagnoses were not
included in any model because this variable was unrelated
to ASASD total score). Where paths involving secondary
variables were not significant, these were deleted from each
of the final models in the interests of model parsimony.
Model A included the observed variable ASD symp-
tomatology and anxiety/depression, with error terms spec-
ified for each variable and secondary variables (model of
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best fit presented in Fig. 1). In Model B, negative family
and peer influences were added to Model A (testing
Hypothesis 2a – b). Paths that were freed included those
from family conflict/peer bullying to child anxiety/depres-
sion, and from family conflict/peer bullying to ASD
symptomatology. The model of best fit is presented in
Fig. 2. In Model C, positive family/peer influences were
added to Model A (testing Hypotheses 3a – b). Paths that were freed included those from family support/peer
friendship quality to child anxiety/depression, and from
family support/peer friendship quality to ASD symptom-
atology. In the comprehensive model (D), all paths that
were significant in Models B and C were retained in Model
D (testing Hypothesis 4), and nonsignificant paths in the
complete model were removed (see Fig. 3). Maximum
likelihood estimation was used to assess the fit of the
models, with the primary fit indices including the chi-
square goodness of fit statistic ( p>0.05) and the root mean
square error of approximation (RMSEA). The RMSEA has
recently been recognized as one of the most informativecriteria in covariance structure modeling (Byrne 2001),
where values less than 0.05 indicate a good fit (Browne and
Cudeck 1993).
Results
Due to the design of the website it was not possible for
participants to submit questionnaires with missing values.
Participants were permitted to submit each questionnaire
separately. To test for differences in those who completed
all questionnaires (n =322) versus those who did not (n=
46), one-way ANOVAs were conducted on continuous
demographic variables, SDQ subscale scores, FES subscale
scores, and peer victimization scores. Across all these
variables there were only two significant differences
between the two groups. Noncompleters had children who
were significantly older than completers [ M =13.1(SD=
4.3), M =11.7(SD=3.6), for noncompleters and completers
respectively, F (1, 321)=5.63, p
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8/14
5 were observed and 5 unobserved. The model contained
20 distinct sample moments and 14 distinct parameters to
be estimated (df =6). The model achieved good overall fit [χ
2(6)=6.64, p=0.36, RMSEA=0.018] and the anxiety/
depression – ASD symptomatology unstandardized regres-
sion weight ( B) was 2.20, p
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0.01]. Inspection of the beta paths indicated that the paths
from both family cohesion to ASD and family cohesion to
anxiety/depression were nonsignificant with family conflict
in the model. There was a significant, negative relationship
between family cohesion and family conflict, ( B=−0.54, p <
0.001, 95% CIs=0.47 – 0.65). Hypothesis 4 was confirmed.
When entered together, family conflict remained a signif-
icant direct predictor of anxiety/depression, ( B=0.28, p<0.001, 95% CIs=0.16 – 0.42) and indirectly predicted sever-
ity of ASD symptomatology (r =0.13), and family cohesion
was not uniquely predictive of either anxiety/depression or
ASD symptomatology.
Given previous research findings that child ASD may
impact on the family relationship quality of parents (see
Introduction), supplementary post hoc variations on Model
D were tested to examine the directionality of significant
paths involving ASD symptomatology and conflict/cohe-
sion scores for parents. When the paths between these
variables were reversed, the ASD symptomatology – family
conflict/cohesion paths were nonsignificant and the modelshowed poor fit. While causal directions between family
relationship quality and ASD symptomatology cannot be
established in this study, overall results were consistent
with the possibility that family relationship quality predicts
ASD symptomatology more strongly than the reverse.
Discussion
The results of this study go some way towards clarifying
the links between family conflict and cohesion, peer
relationships, anxiety/depression, and ASD symptomatolo-
gy. There was a significant association of severity of ASD
symptomatology and anxiety/depression. Family conflict
predicted anxiety/depression, and anxiety/depression pre-
dicted severity of AS. Peer victimization weakly and
directly predicted ASD symptomatology. Family cohesion
negatively predicted anxiety/depression, but this association
was no longer significant when family conflict was
included (Model D). Positive peer relationships were
unrelated to anxiety/depression or severity of ASD symp-
tomatology. Findings remained statistically significant
when foreseeable confounds such as child age, intellectual
impairment, gender, language impairment, and siblings
with ASD were built into the model. Post hoc analyses
found support for the hypothesis that family relationship
quality predicted ASD symptomatology but not vice versa.
The findings of this study were new in several regards.
First, this study showed that anxiety/depression and ASD
symptomatology are significantly related. While prior
research has established that anxiety/depression is common
in children with ASD, this study showed that a latent
construct of ASD symptomatology was continuously
associated with anxiety/depression. The model is consistent
with the possibility that as anxiety/depression increases, so
do the core features of ASD. Second, the study highlights the
indirect yet significant potential effects of family conflict on
children with ASD. Higher family conflict was associated
with more child anxiety/depression, which in turn, statisti-
cally predicted ASD symptomatology. Negative relation-
ships had more weight than positive relationships in the prediction of anxiety/depression and ASD symptomatology.
Family conflict may be linked to ASD symptomatology
through one or more mechanisms. As with typically
developing children, family conflict may increase symp-
tomatology by threatening perceived safety/security within
the family. This proposed mechanism assumes that children
with ASD are able to have an emotional attachment with
their family that provides them with a sense of safety and
security. There is research evidence for this. While children
with autism have been found to be significantly less
attached to their parents than comparison groups of
children, this difference is not present in children withhigher mental development, and in children with less severe
symptoms of autism (Rutgers et al. 2004). A second
possible mechanism is that family conflict may exacerbate
key features of ASD, notably distress upon disruption of
routine and sensory sensitivity. Family conflict character-
ized by shouting and arguments may be distressing because
of the aversiveness of such stimuli, and the disruptive and
unpredictable nature of family conflict, particularly from
the perspective of the children with ASD.
It was notable that the mean ratings of family conflict
were not particularly high for this sample. The mean score
for the total sample in this study was 3.56 (SD= 2.30)
whilst the mean for the original normative sample was 3.18
(SD= 1.9; Moos and Moos 1994). Given that family
conflict is a key marker of family relationship distress
(Kelly et al. 2003), the overlap of normative distributions
with the present study indicated that family relationships
were generally not distressed. However, the findings
suggested that ASD symptomatology is potentially respon-
sive to relatively mild levels of family conflict. Although
the levels of family conflict in this study were not clinically
significant, these levels may have indirect clinical signifi-
cance for these families, because they predict the severity of
a clinically significant problem. Perhaps because of the
unique profiles of children with ASD, the effects of
apparently non-problematic levels of family conflict may
be magnified for these children. Conducting in-depth
interviews with children with ASD to determine their own
thoughts and reactions to family conflict may explicate
reasons that these children are adversely affected by the
conflict.
The post hoc finding of a nonsignificant path from ASD
symptomatology to family conflict is somewhat at odds
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with the above-reviewed prior research on the impact of
child psychopathology on parental well-being and couple
relationship quality. Several potential artifacts may account
for this negative finding. It is possible that ASD symptom-
atology increases family conflict at other critical points in
the often-long journey of awareness and acknowledgement
of ASD, formal diagnosis, and help seeking. This study
involved the recruitment of past clinic clientele, so anyfamily stress/conflict associated with children with ASD
may have been a trigger for initial help seeking and had
receded at the time of participation. It is also possible that
families high in relationship distress/conflict are less likely
to seek assistance for ASD or were less likely to consent to
participating in a study of this sort. These types of biases in
pathways to participation are common in clinically oriented
research. Nevertheless, the results are consistent with the
possibility that post diagnosis and/or therapy, ASD symp-
tomatology may minimally predict family conflict.
Family support appeared less closely related to anxiety/
depression and ASD symptomatology than family conflict.The weak indirect effect of family support on ASD
symptomatology became nonsignificant after accounting
for family conflict. The greater potential effect of family
conflict relative to family support is somewhat inconsistent
with the marital/family literature, where family support has
been found to have at least as strong an influence on
individual and relationship health as family conflict (Bradbury
et al. 2000). This result also is in contrast with earlier
reviewed research on other childhood disorders, where low
family support is associated with increased severity of
ADHD in vulnerable children. On the basis of this
interpretation, there may be a greater clinical prerogative
to focus on reduction of family conflict rather than
enhancement of family support, at least for samples similar
to this one. On the whole, participating families reported
comparatively high levels of intra-family support ( M =6.5;
mean for normative sample was 6.7). However, based on
the results for Model D, enhancement of family support
may assist families with children with ASD indirectly by
reducing the likelihood of family conflict. It is also possible
that the support measure we used in this study did not
capture the dimensions of support that most affect children
with ASD. For example, support dimensions that empha-
size attachment and emotional closeness (Cutrona and Suhr
1994) may be less potent for children with ASD than
other forms of support, such as providing practical help
and routines that minimize distress (e.g. Attwood 2006;
Willey 2001).
The lack of strength in the family support – ASD
symptomatology relationship was comparable to the lack
of significant associations of peer support and ASD
symptomatology. The latter finding stands in contrast to
two previous studies (Bauminger and Kasari 2000; Weidle
et al. 2006) suggesting that peer support was important to
people with ASD. This finding is also inconsistent with
research findings that the number and quality of friendships
buffer typically developing children against anxiety/depres-
sion and the effects of peer victimization (e.g. Bukowski et
al. 1994; Bollmer et al. 2005; Hay et al. 2004; Kashani et
al. 1995). As with family support, it is possible that
children with ASD do not find conventional forms of peer support as reinforcing as typical children. Consistent with
this, children with ASD have definitions of friendship and
loneliness that have reduced affective content, and having a
friend does not assuage loneliness in children with ASD
(Bauminger and Kasari 2000). An alternative explanation
was that the children in the current study did not have
enough friends to provide social support. The mean score
for the entire sample on the measure of peer support used in
this study was very low ( M =5.5, SD =4.5). This mean was
one to two standard deviations lower than the mean of the
original standardization sample of typically developing
children ( M =15.5, SD=9; Spence 1995). Such low scoresindicate that the children in the current study experienced
very few positive social outcomes (e.g. few close stable
friendships; few invitations to parties, other children’s
homes or social events; poor relationships with classmates).
The findings have several implications for expanding the
reach of common interventions for children with ASD. The
results point to the possibility that identifying and treating
symptoms of anxiety and depression directly may reduce
ASD symptomatology. This is consistent with emerging
evidence that CBT is effective for children with ASD
(Sofronoff et al. 2005). The results also point to the utility
of adjunctive interventions designed to effectively manage
family conflict, even when levels of family conflict are
relatively low. Behavioral couples therapy has traditionally
focused on improving communication and managing
negative emotions (Kelly et al. 2003) and improvements
in these areas may reduce a contextual antecedent to ASD
symptomatology. Given the relatively low levels of family
conflict, brief or minimal behavioral couple interventions
(e.g., Halford et al. 1996) may be useful for these families.
Several limitations of this study must be noted. The
cross-sectional design of the study does not permit
conclusions about causal pathways. While path analyses
suggested that family relationship quality predicts ASD
symptomatology more than the reverse, these findings
would need, at the very least, to be robustly demonstrated
in longitudinal designs. The findings of the present research
are limited to parent self-report data, and may not
generalize to children with ASD who experience less
bullying and teasing (noncompleters reported less bullying
and teasing than completers). The research focused on
families with a children with ASD, across a broad age range
(6 – 16 years old), and it is possible that the interactions
1078 J Abnorm Child Psychol (2008) 36:1069 – 1081
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between family and peer relationships and children with
ASD might be different in other age groups. For example,
in younger children, family conflict may be more strongly
related to ASDs, and in older children (young adults),
family conflict may be less important than peer relation-
ships. These sorts of developmentally-related influences are
evident in other child behaviors, where family influences
appear stronger than peer influences in earlier years, but this reverses somewhat as children move into adolescence
(Kotler and McMahon 2005; Marshall and Chassin 2000).
Conclusion
This study is a key first step in evaluating the potential
impact of family and peer relationship quality on the
symptomatology of children with ASD. Results were
consistent with the possibility that anxiety/depression is a
key conduit by which family conflict increases ASD
symptomatology, however longitudinal research is neededto begin disentangling causal relationships. Interventions
for children with ASD may be fruitfully enhanced by
including couple/family interventions designed to manage
conflict, even when the severity/frequency of conflict is
within the range of nondistressed couples/families.
Acknowledgements The authors thank Beverlee Garnett for invalu-
able administrative assistance. This research was conducted during an
NHMRC Career Development Fellowship awarded to the first author.
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