Autism Spectrum Symptomatology in Children the Impact of Family and Peer Relationships

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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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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


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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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Autism Spectrum Symptomatology in Children the Impact of Family and Peer Relationships