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Abstract Attachment was assessed in toddlers with
Autistic Disorder (n = 20), Pervasive DevelopmentalDisorder (n = 14), Mental Retardation (n = 12), Lan-
guage Development Disorder (n = 16), and a non-
clinical comparison group (n = 18), using the Strange
Situation Procedure (SSP). Children in the clinical
groups were more often disorganized and less often
securely attached. Severity of autism was associated
with more attachment insecurity, and lower develop-
mental level increased the chance for disorganized
attachment. Attachment disorganization was related to
increased heart rate during the SSP. Controlling for
basal cortisol and developmental level, more autistic
symptoms predicted lower cortisol responses to theSSP. The findings support the importance of disorga-
nized attachment for children with autism.
Keywords Autistic disorder Cortisol Physiology
Strange situation procedure
Introduction
For a long time the inability to form attachment rela-
tionships was seen as one of the characteristics of
autism (Rutter, 1978; Volkmar et al., 1987), given the
core problems in social interaction and communication
in children with autism. However, studies that focused
on direct observations of attachment behaviors like
proximity seeking reported that autistic children did
show behavior that is described as attachment related
(Buitelaar, 1995; Capps, Sigman & Mundy, 1994;
Dissanayake & Crossley, 1996; Sigman & Ungerer,
1984). When a standardized test procedure (i.e. the
Strange Situation Procedure, SSP; Ainsworth, Blehar,
Waters, & Wall, 1978) is used to elicit attachment
behaviors in young children with autism, childrens
behavioral patterns can be coded according to the
Ainsworth et al. (1978) attachment classification sys-
tem. These attachment classifications are the secure
classification (B), the insecure-avoidant classification
(A), and the insecure-resistant classification (C), and
they are based on the childs behavior during reunion
episodes after two short separations from the care-
giver. Additionally, a category of disorganized attach-
ment (D) has been developed to account for
momentary break-downs in the regular attachment
strategy (Main & Solomon, 1990).
Children are classified as securely attached (type B)
when they use the attachment figure as a base from
which to explore. These children appear to strike a
balance between attachment and exploration behavior.
Insecure-avoidant children (type A) show little or no
response to the attachment figures leave taking. Their
exploration is considered a strategy aimed at minimi-
zation of attachment behavior (Main, 1990). Children
F. B. A. Naber (&) M. J. Bakermans-Kranenburg M. H. van IJzendoornDepartment of Education and Child Studies,
Centre for Child and Family Studies, University of Leiden,P.O.Box 9555, 2300 RB Leiden, The Netherlandse-mail: [email protected]
C. Dietz E. van Daalen H. van Engeland F. B. A. NaberRudolph Magnus Institute of Neuroscience,Department of Child and Adolescent Psychiatry,University Medical Center Utrecht, Utrecht,The Netherlands
S. H. N. Swinkels J. K. BuitelaarDepartment of Psychiatry, Radboud Universityof Nijmegen, Nijmegen, The Netherlands
J Autism Dev Disord (2007) 37:11231138
DOI 10.1007/s10803-006-0255-2
123
O R IG IN A L P A P ER
Attachment in Toddlers with Autism and OtherDevelopmental Disorders
Fabienne B. A. Naber Sophie H. N. Swinkels Jan K. Buitelaar Marian J. Bakermans-Kranenburg Marinus H. van IJzendoorn Claudine Dietz Emma van Daalen Herman van Engeland
Published online: 8 December 2006 Springer Science+Business Media, LLC 2006
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classified as insecure-resistant (type C) appear preoc-
cupied with their attachment figures throughout the
procedure. They appear to maximize the display of
attachment behavior at the expense of exploration
(Main, 1990). The functional definitions of the attach-
ment classifications are summarized in Table 1 (Hesse,
1999, p. 399).
Disorganized attachment is observed in childrenwho are not able to develop a specific organized
attachment behavioral pattern with their primary
caregiver (Main & Solomon, 1986). The disorganized
(D) classification is considered to index the childs
inability to cope with his or her anxiety in the face of
stress although the attachment figure is present. In fact,
for disorganized children the attachment figure is also
perceived as a source of fright instead of only as a
potentially safe haven.
Based on a meta-analysis of the available empirical
studies, Rutgers, Bakermans-Kranenburg, Van IJzen-
doorn, and Van Berckelaer-Onnes (2004) found thatattachment security is compatible with autism, and can
be assessed with Strange Situation type of procedures.
The co-morbidity of autism and mental retardation
appeared to be associated with attachment insecurity.
With respect to disorganized attachment behavior in
children with autism, conflicting results were reported.
In the study of Capps and colleagues (Capps et al.,
1994) all children with autism appeared to have a
disorganized attachment relationship, but Willemsen-
Swinkels and colleagues (Willemsen-Swinkels, Baker-
mans-Kranenburg, Buitelaar, Van IJzendoorn, & Van
Engeland, 2000) reported a higher percentage of
disorganized classifications only in children with autism
and concurrent mental retardation. It should be noted
that some of the behaviors that are indicative of dis-
organized attachment (e.g., stereotypes, undirected
movements and expressions, and freezing or stilling of
all movement with a disoriented expression, Main &
Solomon, 1990) may be more frequently observed in
children with autism as part of their disorder. Disor-ganized attachment behaviors should, however, be
informative about relational aspects of the child and its
caregiver, and not be the result of neurological
impairments, as Pipp-Siegel, Siegel, and Dean (1999)
have noted. When attachment security or disorgani-
zation is coded in samples with children with autistic
disorders, their baseline behavior in the pre-separation
episodes of the Strange Situation procedure should be
taken into account (as was done in Willemsen-Swinkels
et al., 2000). Using this approach, Willemsen-Swinkels
et al. (2000) reported diverging patterns of behavioral
organization in a separate observation of motherinfant interaction for children with autism versus chil-
dren with disorganized attachment, which suggests that
it is possible to disentangle autistic behaviors and
disorganized attachment. They also found that high-
functioning children with PDD did not reveal higher
rates of a disorganized attachment than matched
comparison groups. Unfortunately, the studies of
Willemsen-Swinkels et al. (2000) and Capps et al.
(1994) are the only two studies to date with disorga-
nized attachment assessed in children with autism and
both these studies were based on children older that
36 months of age.
Table 1 Descriptions of attachment classification behavior
Infant behaviorSecure Attachment (B)Secure children use the attachment figure as a base from which to explore. These children appear to strike a balance between
attachment and exploration behavior. These children may show signs of missing the parents during separation. With returnof the parents, the child actively greets the parent, usually initiating physical contact. After return of the parent, the child iseasily settled and returns to play.
Insecure Avoidant Attachment (A)Insecure-avoidant children show little or no response to the attachment figures leave taking. Their exploration is considered a
strategy aimed at minimization of attachment behavior. These children show little to no proximity or contact seeking, no distress
and no anger.Insecure Resistant Attachment (C)Children classified as insecure-resistant appear preoccupied with their attachment figures throughout the procedure. They appear
to maximize the display of attachment behavior at the expense of exploration. They may seem angryor upset and fail to settle after reunion.
Insecure Disorganized Attachment (D)Disorganized attachment is observed in children who are not able to develop a specific organized attachment behavioral pattern with
their primary caregiver. The disorganized classification is considered to be an index of the childs inability to cope with his or heranxiety in the face of stress although the attachment figure is present. In fact, for disorganized children the attachment figure is alsoperceived as a source of fright instead of only as a potentially safe haven. The children may show behavior like freezing, stereotypedbehavior, cling or cry hard while looking and leaning away.
Note: Descriptions of the infant A, B, C and D classifications are summarized from Hesse ( 1999, p. 399)
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The advances within the neurosciences in the past
decade allowed developmental scientists include
neuro-physiological and behavioral phenomena in an
integrative approach (Cacioppo & Berntson, 1992).
Childrens coping strategies, expressed in their behav-
ioral responses during the Strange Situation, were also
monitored on a biological level (Gunnar, Mangelsdorf,
Larson, & Hertsgaard, 1989). This gave rise to anumber of studies on the role of cortisol in attachment.
Several studies have shown cortisol reactivity in 1-year-
olds to be related to attachment security (Gunnar,
Brodersen, Nachmias, Buss, & Rigatuso, 1996;
Hertsgaard, Gunnar, Erickson, & Nachmias, 1995;
Nachmias, Gunnar, Mangelsdorf, Parritz, & Buss,
1996; Spangler & Schieche, 1998). The adrenocortical
system appears to react most strongly in potentially
threatening situations, when the resources to cope with
the threat are lacking (Kirschbaum & Hellhammer,
1994; McEwen & Sapolsky, 1995; Nachmias et al.,
1996; Spangler & Scheubeck, 1993). Nevertheless, moststudies indicate that there is considerable individual
variation in cortisol responsiveness (Jansen et al.,
1999). Studies on adrenocortical responses to the SSP
have shown that in particular children with a disorga-
nized attachment relationship show elevated responses
in cortisol levels after separation from the mother
(Hertsgaard et al., 1995; Spangler & Grossmann,
1993). Cortisol responses during the Strange Situation
in children with autism under 3 years of age have not
yet been reported.
Cardiac responses have been used in typically
developing children to analyze whether stimuli are
aversive (heart rate acceleration) or interesting (slow-
ing heart rate) (Eisenberg & Fabes, 1999; Fabes,
Eisenberg, & Eisenbud, 1993; Sigman, Dissanayake,
Corona, & Espinosa, 2003). Therefore, as a second
physiological indicator of coping with stress, heart rate
(HR) has also been examined in this study during the
SSP. Changes in heart rate might be related to
attachment classification. In particular disorganized
children may be at risk for deviating heart rate reac-
tivity, because they lack a coherent coping strategy to
deal with the stresses of the SSP. In a community
sample, Spangler and Grossmann (1993) found that
disorganized infants exhibited a particularly high HR
elevation during the second separation. Willemsen-
Swinkels et al. (2000) reported an association between
disorganized attachment and increase in heart rate in
children with Pervasive Developmental Disorders.
Nevertheless, also securely and insecure-avoidant
children showed (lower, but still significant) increased
heart rate. Unlike disorganized children, children with
secure, insecure-avoidant and insecure-resistant infants
are viewed as having a coherent strategy for coping
with stress in the presence of an attachment figure
(Cassidy & Shaver, 1999). Spangler and Grossmann
(1993) analyzed changes in heart rate in normally
developing children, and the study of Willemsen-
Swinkels et al. (2000) involved children with PDD with
a mean age of 68 months. The relation between
attachment and heart rate reactivity during stress forchildren with clinical disorders like autism under the
age of 4 years has not yet been studied.
In Corona, Dissanayake, Arbella, Wellington, and
Sigmans (1998) study children with autism did not
show any heart rate response to the affect of another
person, whereas children with developmental delays
showed a cardiac orienting response. The other per-
sons affect thus seemed interesting to children with a
developmental delay but not to children with autism.
Sigman et al. (2003) investigated the cardiac responses
of children with autism and children with develop-
mental delay to, among others, parental separation andreunion. They found that children with developmental
delays showed lower heart rate during the first 10 s of
separation than baseline, whereas children with autism
did not show any orienting response.
Various theoretical models have been proposed
about the underlying deficits of autism, which may also
contribute to the prediction of attachment quality in
this clinical population. One theory is based on the
effects of impaired developmental level that is seen in
a high percentage of children with autism. The delay in
developmental level may contribute to delays or defi-
cits in the development of understanding other
peoples actions or situations (Baron-Cohen, 1995;
Stern, 1985). Therefore, children with autism may de-
velop a secure attachment relationship, but this
development may take more time than children with-
out a developmental delay (Rogers, Ozonoff, & Mas-
lin-Cole, 1993). Another model describes autism as an
arousal problem. According to this theory, children
with autism are highly aroused in social interaction.
This high arousal may contribute to the aversion of a
child with autism to interact with another person,
which may lead to insecure attachment relationships
(Dawson & Lewy, 1989; Rogers et al., 1993). The
design of this study creates the opportunity to test
these hypotheses. The combination of behavioral data
and heart rate measures during the SSP may contribute
to a better understanding of the social interactions of
the children with autism.
To examine the distribution of the attachment
classifications we compared the attachment classifica-
tions of these children with children with other social
developmental disorders and a non-clinical control
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group. So far, studies of attachment in children with
autism involved children older than 3 years of age, and
modified SSPs were used (for a narrative review and
meta-analysis of these studies see Rutgers et al., 2004).
Our main goal is to test whether the distribution of
attachment classifications of younger children with
autistic spectrum disorders, using an unmodified SSP at
a more proper age, is similar to the distribution foundin the normal western population as reported in the
meta-analysis of Van IJzendoorn and colleagues (Van
IJzendoorn, Schuengel & Bakermans-Kranenburg,
1999), or to the combined clinical samples in that meta-
analysis. The meta-analysis, based on nearly 80 studies,
showed that 15% of the normal middle class children
develop insecure avoidant attachments (A), 62%
secure attachments (B), 9% insecure-resistant attach-
ments (C), and that 15% are disorganized. In clinical
samples, the percentage of disorganized children was
35%. About 13% of the clinical children were found to
be insecure-avoidantly attached (A), 46% securelyattached (B), and 5% insecure-resistantly (C) attached.
One of the three characteristic features of the autistic
disorder is qualitative impairment in social relation-
ships (American Psychiatric Association, 1994).
Because the first social relationship of the child is with
the parent, social development may be influenced by
parenting processes. Although several studies have
focused on the ability of children with autism to
develop an attachment relationship with the parents,
there are still some questions that need to be ad-
dressed. One of the questions is the effect of the
developmental level of the child. A high percentage of
children with autism also have co-morbid mental
retardation. Rogers et al. (1993) noted that the devel-
opmental level was the strongest predictor of attach-
ment security in their study. However, this study did
not include a control group of children with mental
retardation without autistic symptomatology. Also the
study of Willemsen-Swinkels et al. (2000) did not in-
clude such a control group. In our study we included
children with AD and children with PDDNOS, but
also children with MR and LD and a typically devel-
oping control group. The inclusion of these groups
creates the opportunity to investigate the effects of
autism in the development of an attachment relation-
ship while being able to control for mental age.
Our hypothesis is that the group of children with
autism in our sample will show the same attachment
distribution as the children with other developmental
disorders (controlling for baseline behavior), but that
this distribution will be different from the distribution
in the non-clinical comparison group. Following
Rutgers et al.s (2004) meta-analytic results, we expect
an under-representation of secure attachment in chil-
dren with autism.
Sigman and Ungerer (1984) suggested a relationship
between cognitive development and attachment
behaviors and Rogers et al. (1993) noted that devel-
opmental level was the strongest predictor of attach-
ment security within the group of autism. In the study
of Willemsen-Swinkels et al. (2000) again the highestproportion of insecure attached children were found
among the PDD children with co-morbid mental
retardation. Following these results and the meta-
analytic findings of Rutgers et al., (2004) we expect
both autistic characteristics and developmental level to
be associated with security of attachment in clinical
children.
We also expect deviations regarding disorganized
attachment. Our hypothesis is that children with devel-
opmental disorders, in particular children who are
mentally retarded, will show more disorganized attach-
ment (see Rutgers et al., 2004). Studies on attachment inmentally retarded children are scarce. However,
Vaughn and his colleagues (Vaughn et al., 1994) found
an overrepresentation of disorganized attachment in
children with Down syndrome.
Furthermore, in an exploratory way (due to the
small number of children), we investigate whether the
SSP produces the same physiological responses in
children with autism as in children with other devel-
opmental disorders. Based on studies conducted so far,
we also expect overall higher responses in children
with insecure attachments compared to children who
are securely attached. In particular for children with a
disorganized attachment relationship a higher cortisol
response is expected. However, based on earlier find-
ings (Jansen et al., 1999), we expect overall dampened
cortisol responses in the group of children with ASD
compared to the other groups.
Disorganized attachment is also expected to be
related to increased heart rate reactivity during re-
union with the parent after a short separation. Based
on the findings of Sigman et al. (2003) that children
with autism show less cardiac response to parental
separation and reunion, we will investigate whether
increased heart rate reactivity in children with autism is
related to disorganization of attachment, regardless of
the autistic disorder.
In sum, we investigate the distribution of attachment
classifications as well as the childrens physiological
responses as expressed in cortisol response and heart
rate during the Strange Situation in young children
with autism and other developmental disorders. The
outcome of the combined behavioral data of the SSP
with physiological measurements may contribute to a
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better understanding of the social interactions of
the children with autism at an early stage in their
development.
Method
Participants
All children were recruited from a population based
sample around 30,000 children at the age of
14 months, participating in a large screening study in
a geographical defined area, the province of Utrecht
(The Netherlands) for early detection for social
developmental disorders. Details about the screening
are described by Willemsen-Swinkels (Willemsen-
Swinkels, Dietz, van Daalen, van Engeland, &
Buitelaar, 2006) and Dietz (Dietz, Willemsen-Swin-
kels, van Daalen, van Engeland, & Buitelaar, 2006).
Children who were screen-positive for social devel-opmental delay were invited for further investigations
at the Department of Child and Adolescent Psychia-
try in Utrecht. The study design and screening pro-
cedure were approved by the Medical Ethics Review
Board of the University Medical Centre Utrecht.
More information about the percentage of children
who were found screen positive, and the percentages
of children who received a final diagnosis of ASD, is
presented in Dietz et al. (2006).
Diagnostic Groups
Children who were classified with AD (Autistic Dis-
order), PDDNOS (Pervasive Developmental Level,
not otherwise specified), MR (Mental Retardation) or
LD (Language Disorder) at the appropriate age of
42 months were included in the analyses. Children with
other diagnosis were excluded from the analyses. As a
result, data of 62 children with a developmental
disorder were available. The children were divided
across the four groups as follows; AD (n = 20), PDD-
NOS (n = 14), MR (n = 12), and LD (n = 16), with an
overall mean age of 27.65 months (SD = 6.04). The
developmental level, as measured by the Mullen
Scales, of the children with AD was 53.55 (SD = 3.66)
and the developmental level of the group of children
with MR 56.42 (SD = 5.52). The developmental level
of the group with LD was 81.63 (SD = 10.39). The
group of children with PDDNOS showed a wide range
in developmental level, with some of these children
having a mental handicap, and others functioning at a
normal developmental level. Because the develop-
mental level as well as the intensity of the autistic
disorder might influence the attachment relationship,
the group was further subdivided into the following
groups: children with PDDNOS with concurrent
mental retardation (PDDNOS mr, n = 6) develop-
mental level 57.33 (SD = 5.43), and children with
PDDNOS without concurrent mental retardation
(PDDNOS not mr, n = 8) developmental level 86.38
(SD = 14.83).For some analyses, a further contrast was formed of
children with Autism Spectrum Disorders (ASD;
n = 34; mean age 29.79, SD = 5.32) which included
children with AD and children with PDDNOS, versus
children without Autism Spectrum Disorder (non-
ASD; n = 28; mean age 25.04, SD = 5.92) which
included children with MR and children with LD. The
developmental level of the children with ASD was
61.94 (SD = 15.82) and the developmental level of the
group of children without ASD 70.82 (SD = 15.29).
We also included a control group (C). Control group
children were screen negative on the ESAT (EarlyScreening of Autism Traits questionnaire), and based
on parental reports and observations of the psycholo-
gists these children were free from any child psychiatric
disorder. To obtain this control group (n = 18; mean
age 28.11 months, SD = 1.71; developmental level
98.39, SD = 11.49), parents were contacted through
well-baby clinics (see Dietz et al., in prep). Parents
who agreed to participate were interviewed about the
childs social and cognitive development at home.
The control group children were also tested for
developmental level with the Mullen Scales. Descrip-
tive characteristics of the children are presented in
Table 2.
Procedure
Psychiatric examinations included a series of five visits
that were scheduled within a period of 5 weeks. At
each weekly visit, the social and communicative
behavior of the child was observed in a small group of
young children and their parents. The assessments
included a standardized parental interview, develop-
mental history, and the Vineland Social-Emotional
Early Childhood Scales (Sparrow, Balla, & Cicchetti,
1997); standardized behavior observation (Autism
Diagnostic Observation Schedule ADOS-G, (DiLavore,
Lord, & Rutter, 2000), and pediatric examination and
medical work-up. The cognitive level (developmental
level) of the child was measured with the Mullen Scales
of Early Learning (Mullen, 1995). The developmental
level referred to in this paper is the early learning
composite score, which is comparable to the develop-
mental quotient (M = 100, SD = 15).
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At age 42 months the child was re-examined, and
apart from the earlier described measurement, the
ADI-R (Lord, Rutter, & LeCouteur, 1994) parental
interview was used. On the basis of all available
information, and on the basis of clinical judgment, a
diagnosis was given by an experienced child psychia-
trist. The inter-rater reliability for the clinical diagnosis
among three child psychiatrists (HvE, JB, ED) wascalculated first for two diagnostic categories; ASD or
other than ASD. Agreement was reached in 92%
(n = 38). Agreement corrected for chance was .74
(Cohens Kappa). Second, the inter-rater reliability
was determined for all diagnostic categories. An
agreement was reached of 79% (n = 38), Cohens
Kappa = .67. Diagnostic discrepancies were discussed
to consensus. More details on the psychiatric diagnoses
will be reported elsewhere (Van Daalen et al., in
prep). The reliability rates are comparable with the
studies of Stone and colleagues (Stone et al., 1999) and
Fombonne (Fombonne et al., 2004) for reliability indiagnosing autism in very young children.
The SSP took place at the Department of Child and
Adolescent Psychiatry in Utrecht, in the presence of
the primary caregiver of the child. The session was
scheduled during the second of six visits at the hospital,
which usually took 75 min, with the SSP at the begin-
ning of the visit. After the SSP several structured tasks
and unstructured play situations were observed. Dur-
ing this visit, salivary cortisol and heart rate data were
collected.
Measures
Strange Situation Procedure
Ainsworth (Ainsworth et al., 1978) developed the SSP
to observe the attachment behavior of the child to-
wards the mother. The SSP contains two separations
and two reunions with the primary caregiver. During
this procedure the balance between seeking comfort
with the attachment figure and exploration of the
environment is assessed. Securely attached children
show a balance in their proximity seeking and explo-
ration of the environment, whereas avoidant children
minimize their expression of negative emotions and
ambivalent children maximize this expression. These
children may remain passively or angrily focused on
their parents even when the environment calls for
exploration and play (Main, 1990). Nevertheless, these
three organized strategies A (insecure-avoidant), B
(secure) and C (insecure-resistant; Ainsworth et al.,
1978) may be considered as adaptive to the infants
environment, and each is supposed to allow for aTable
2
Characteristicsandattachmentdistributionsoftheclinicalandcontrolchildren(n=80)
AD
PDDNOS
withmr
PDDNOS
withoutmr
PDDNOS
MR
L
D
C
ASD
NASD
M
(SD
)
M
(SD)
M
(SD)
M
(SD)
M
(SD)
M
(SD)
M
(SD)
M
(SD
)
M
(SD)
Total
20
6
8
14
12
1
6
18
34
28
Boy/Girl
15/5
5/1
7/1
12/2
8/4
1
5/1
7/11
27/7
23/12
Age
30.2
0(4.9
6)
27.0
0(6.4
5)
30.8
8(5.3
6)
29.2
1(5.9
5)
24.5
0(5.8
5)
2
5.4
4(6.1
2)
28.1
1(1.7
1)
29.7
9(
5.3
2)
25.0
4(5.9
2)
Developmentallevel
53.5
5(3.6
6)
57.3
3(5.4
3)
86.3
8(14.8
3)
73.9
3(18.7
7)
56.4
2(5.5
2)
8
1.6
3(10.3
9)
98.3
9(11.4
9)
61.9
4(
15.8
2)
70.8
2(15.2
9)
Autisticsymptoms
33.2
2(9.4
2)
32.1
7(12.0
1)
13.2
5(14.1
6)
21.3
6(16.0
6)
19.0
0(12.6
3)
1
1.3
8(5.7
1)
28.3
2(
13.7
0)
14.6
4(9.9
0)
Attachment
n(%)
n(%)
n(%)
n(%)
n(%)
n
(%)
n(%)
Insecureavoidant(A)
3(15%
)
2(33.3
%)
1(12.5
%)
3(21.4
%)
2(16.7
%)
1
(6.2
5%)
0(0%)
6
3
Secure(B)
7(35%
)
2(33.3
%)
4(50%)
6(42.9
%)
4(33.3
%)
1
1(68.8
%)
15(83%)
13
15
Insecureresistant(C)
0(0%)
1(16.7
%)
1(12.5
%)
2(14.4
%)
2(16.7
%)
1
(6.2
5%)
3(16.7
%)
2
4
Disorganized(D)
10(50%)
1(16.7
%)
2(25%)
3(21.4
%)
4(33.3
%)
3
(18.8
%)
0(0%)
13
3
Heartrateanalysis
8
3
4
5
3
Age
29.7
5(4.4
3)
26.3
3(5.0
3)
22.5
0(7.6
8)
2
5.0
0(5.9
2)
29.0
0(1.7
3)
Developmentallevel
54.7
5(4.4
3)
68.3
3(9.2
9)
56.5
0(6.8
1)
8
4.0
0(7.0
0)
99.3
3(11.0
2)
AutisticSymptoms
31.2
5(9.6
5)
34.0
0(3.0
0)
25.5
0(13.3
8)
8
.80(4.1
5)
Cortisolanalysis
19
8
12
1
2
17
Age
30.3
7(5.0
4)
27.5
0(5.0
1)
24.5
0(5.8
5)
2
5.0
8(5.6
2)
28.1
2(1.7
4)
Developmentallevel
53.6
8(3.7
1)
75.2
5(19.4
6)
56.4
2(5.5
2)
8
2.1
7(10.1
6)
98.7
6(11.7
2)
AutisticSymptoms
32.8
4(9.5
4)
26.2
5(14.5
4)
19.0
0(12.6
3)
1
0.6
7(5.2
6)
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maximum of proximity to the specific attachment
figure whose behavior to stress or distress is anticipated
(Main, 1990). Disorganized attachment on the other
hand, can be described as the breakdown of an other-
wise consistent and organized strategy of emotion
regulation (Main & Solomon, 1990; Van IJzendoorn
et al., 1999).
The SSP was coded by two trained and appropri-ately certified observers (SWS & MBK), who were
unaware of the diagnoses of the children. The infants
patterns of attachment behavior were classified as
secure (B), insecure-avoidant (A), insecure-resistant(C)
or disorganized (D) after taking baseline behavior of
the children into account. Based on 28 ad random cases
from this study, agreement for the four attachment
classifications corrected for chance was .74 (Cohens
Kappa). Besides the attachment classifications, we also
used the simplified Richters, Waters and Vaughn
(1988) algorithm to compute continuous scores for
attachment security (Van IJzendoorn, & Kroonenberg,1990) on the basis of the interactive SSP scale scores
for proximity seeking, contact maintaining, resistance
and avoidance. Richters et al. (1988) developed
classification functions to objectively classify infants
attachments only on the basis of the interactive scales
(proximity seeking, contact maintaining, resistance,
and avoidance) and crying behavior in the two Strange
Situation reunion episodes. The simplified and revised
Richters et al. functions (i.e. without crying) appeared
to have good agreement with the original classifications
(Van IJzendoorn & Kroonenberg, 1990). Therefore,
this simplified algorithm was used as a continuous
measure of attachment security, with higher scores
indicating more secure attachment.
Disorganized attachment was coded using the Main
and Solomon (1990) 9-point coding system for disor-
ganized/disoriented attachment. As in our previous
study on attachment in children with autistic disorders
(Willemsen-Swinkels et al., 2000), the childs baseline
behavior during the preseparation episodes of the SSP
was taken into account when a score for disorganiza-
tion was assigned. Intercoder reliability was .77
(Pearsons correlation coefficient) for the security
scale, and .66 (Pearsons correlation coefficient) for the
disorganization scale (n = 28).
Severity of Autistic Symptoms
To quantify the severity of autistic symptoms, the raw
data of the ADOS, collected during the first visit to the
hospital, were used. This instrument, according to Lord
(Lord, Leventhal, & Cook, 2001), offers the opportu-
nity to quantify deficits across the autism spectrum,
controlling for effects of language and cognitive delay,
in individuals with significant impairments. It is sug-
gested that quantitative measures of social reciprocity
and repetitive behaviors and interests, with separate
quantification of expressive language level and non-
verbal intelligence, most accurately reflect the range of
behavioral phenotypes in autism spectrum disorders
(Lord et al., 2001). However, the ADOS module usedin the project was based on children who were 4 years
of age and older. In our study we included younger
children, and the algorithm was therefore not useful for
our sample. Hence, the total sum score of ADOS
module I, (the ADOS for children with little to no
speech) reflects the range of behavioral phenotypes
and was used in this study as a continuous score for
intensity of autism (number of autistic symptoms).
Following the ADOS algorithm, value 3 was recoded
into value 2 before analyzing. ADOS scores of all
clinical groups are presented in Table 2. The inter-
rater reliability for the ADOS among a child psychia-trist and two psychologists was estimated on the basis
of 6 random cases. The percentage of agreement, after
code 3 was recoded to 2, was 97% for total sum score.
Agreement corrected for chance was .62 (Cohens
Kappa).
Physiological Measurements
Salivary Cortisol
Saliva samples were collected before the SSP started
and 25 min after the first separation, in order to
examine the stress response of the children. To collect
the saliva, a sterile cotton role was used to scrape along
the childs inner cheek and under the tongue to absorb
saliva. No oral stimulants (such as Kool-Acid crystals)
were used. Saliva samples were stored frozen at 20C
until analysis. The salivary cortisol concentrations were
measured using a competitive radio-immuno-assay
with antibody according to the new method that measures
small quantities of cortisol in a reliable manner
(De Weerth, Graat, Buitelaar, & Thijssen, 2003).
Of the children participating in the cortisol response
analyses, data of 68 children with two successful col-
lected cortisol samples (one before and one after the
SSP) were available. The other children either refused
to participate in the physiological part of the study
(n = 10; AD (n = 1), PDDNOS (n = 6), LD (n = 2),
C (n = 1)) or one or both saliva samples were not
successfully collected (n = 2; LD (n = 2)). The differ-
ence between cortisol collected before and after the
SSP was used as the value of cortisol response for each
child. These values were used to analyze differences in
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cortisol response between the different groups of
children, taking the basal cortisol level of the children
into account.
Heart Rate
During the session, the heart rate of the child was re-
corded with the Sport Tester Polar Vantage NV (PolarElectrode KY, Finland; Treiber et al., 1989). The
transmitter of the wireless portable monitor was
attached to the chest of the child with sticky electrodes.
The tester was programmed to record and score inter-
beat intervals (IBIs) that were calculated for every 5-s
interval. We used the BPM (beats per minute) for
every 5 s of the last minute of separation and the first
minute of the second reunion episode of the SSP. The
mean heart rate was calculated for each of these peri-
ods. Changes in mean heart rate around reunion were
calculated subtracting the average heart rate of the
minute before the reunion from the average heart rateof the minute after reunion. Reduction of stress after
the reunion will result in lower heart rate and a nega-
tive value of the heart rate reactivity; an increase of
heart rate after reunion with the mother will be
reflected in a positive value of the heart rate reactivity.
The analyses were based on the second reunion of the
procedure in order to examine heart rate reactivity in
the most stressful condition.
The registration of the heart rate was successful for
23 children (AD (n = 8), PDDNOS (n = 3), MR
(n = 4), LD (n = 5), C (n = 3)). The other children
either refused to wear the heart rate monitor or dis-
lodged it. They touched and pulled the heart rate
monitor during the reunion episode, resulting in
unreliable data. However, no systematic differences on
age of the child, developmental level, number of
autistic characteristics, security and disorganization of
attachment were found between these children and
children who did not refuse cooperation, neither in the
total group nor in the group of children with ASD.
Data Analyses
Distribution of Attachment Classifications
The distribution of attachment classifications was
analyzed using the v2-test. First, an overall group
comparison was performed including the control
group. Also, the clinical groups were compared. Two
normative attachment classification distributions,
based on meta-analyses of attachment classifications
for the normal western population and for the clinical
population (Van IJzendoorn et al., 1999), were used
as comparison groups. Contrast analyses were per-
formed to distinguish between autistic symptoms and
developmental level, as well as between attachment
classifications.
Cortisol Analyses
We first examined whether a difference in cortisolresponse was detected among the various diagnostic
groups. The analyses were followed by contrast anal-
yses between children with and without a clinical
diagnosis and children with and without ASD. The
differences in cortisol response were analyzed using
univariate analyses, taking the basal cortisol level into
account as a covariate.
Hierarchical Multivariate Regression Analyses
To investigate the contribution of both developmental
level and intensity of the autistic disorder to attach-ment, the continuous scores for attachment security
and disorganization of the children were used in mul-
tiple hierarchical regression analyses. Developmental
level was entered as first predictor, in order to examine
whether number of autistic symptoms contributed to
security or disorganization after the difference in
developmental level was taken into account. The total
score of the ADOS module 1 was used as a measure-
ment of intensity of autism (number of autistic symp-
toms). The Mullen Scale of Early Learning (Mullen,
1995) was used as index for the level of cognitive
development of the child. For four clinical children, nooverall scores of the number of autistic symptoms were
available, due to difficulties during participation in the
ADOS. For the control group, no ADOS data were
available either. As a result, data of 58 children with
clinical diagnoses were used in these analyses.
Two hierarchical multivariate regression analyses
were performed to analyze the differences in cortisol
response with basal cortisol level, developmental level,
number of autistic symptoms and, in order, attachment
security and disorganization as predictors (n = 58).
Due to high correlations between basal level of cortisol
and cortisol response, a residual of cortisol response
was calculated, taking basal level of cortisol into
account. Number of autistic symptoms and level of
development were also correlated. Therefore, a resid-
ual of the number of autistic symptoms was calculated,
taking developmental level into account. We expected
that attachment disorganization in particular would
predict elevation of cortisol.
It was also expected that attachment disorganization
would predict an increase of heart rate at the reunion
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with the mother. Therefore, a regression analysis with
number of autistic symptoms (taking into account
developmental level) and disorganization as predictors
was performed on mean heart rate values (n = 20).
Results
Preliminary Analyses
In a preliminary analysis, the KolmogorovSmirnov
test was used to analyze the distribution of heart rate
and of cortisol values, which revealed normal distri-
butions. Not all children were tested on the same time
of day. The sessions were divided over the day in 4
parts; 9:15 am, 10:45 am, 13:15 pm and 14:45 pm. Most
children were tested at 9 am (n = 28) and 10:30 am
(n = 19). Ten children participated at 13:15 pm and ten
children participated at 14:45 pm. To test the influence
of time on the first salivary cortisol values, apreliminary analysis for first cortisol values was
performed. Analysis of variance (ANOVA) showed
that there were no effects of time F (3, 67) = 1.85,
P = .13. No differences in cortisol response of boys and
girls were found.
Distribution of Attachment Classifications
Table 2 shows the distribution of attachment classifi-
cations for the various groups. The overall group
comparison revealed a difference in distributions of
attachment classifications, v2 (12, n = 80) = 24.35,P = .05. The main difference was found between chil-
dren with and without a clinical diagnosis. Children
with a developmental disorder were less often securely
attached than comparisons without a developmental
disorder.
The distribution of our combined clinical groups was
not significantly different from the combined clinical
samples (clinical population, CP) of the meta-analysis
of Van IJzendoorn and colleagues (Van IJzendoorn
et al., 1999), and neither did our control group differ
from the normal western population (NWP) in that
meta-analysis.
The distribution of secure and insecure attachments
in the clinical versus control groups showed a signifi-
cant difference, v2 (1, n = 80) = 8.18, P < .01, but no
differences were detected for the distribution of secure
versus insecure classifications in the ASD group com-
pared to the non-ASD group. In the clinical groups,
insecure attachments were over-represented. All clin-
ical groups, except for LD, showed differences in
distribution of secure versus insecure attachments
compared with the control group; AD versus C v2
(1, n = 38) = 9.08, P < 0.01; PDDNOS versus C v2
(1, n = 32) = 5.72, P = 0.02; and MR versus C
v2 (1, n = 30) = 7.75, P < 0.01. No differences in the
distributions of attachment security were detected
between AD and PDDNOS, between AD and MR,
and between PDDNOS and LD. Children with more
autistic symptoms or mental retardation were lessoften securely attached than the comparisons.
The disorganized attachment classification was
overrepresented in the clinical groups, v2 (1, n = 80)
= 7.74, P < .01. The percentage of disorganized
attachments in the ASD group was not different from
that in the non-ASD group. The analyses for AD
revealed differences with the control group, v2
(1, n = 38) = 12.21, P < 0.01. The group with AD was
not different from either the PDDNOS group or the
MR group with respect to disorganized attachment.
Each of the other clinical groups also differed from the
control group; PDDNOS versus C, v2 (1, n = 32) =4.26, P = 0.04; MR versus C, v2 (1, n = 30) = 6.92,
P < 0.01; and the group of LD versus C, v2 (1, n =
34) = 3.70, P = 0.05. Attachment disorganization was
overrepresented in each of the clinical groups com-
pared to the control group.
Is Attachment Security Associated with
Developmental Level and Autistic Symptoms?
Hierarchical regression was employed to determine
whether developmental level or number of autistic
symptoms predicted the development of secure
attachment (continuous attachment security score).
Table 3 displays the correlation between the vari-
ables, the unstandardized regression coefficients (B)
and intercept, the standardized regression coefficients
(b), R, and R2 after entry of both variables: develop-
mental level and number of autistic symptoms. In the
first step developmental level did not contribute
significantly to the prediction of attachment security. In
step two, adding number of autistic symptoms to the
equation, we found a significant regression for attach-
ment security, F (2, 57) = 3.87, P = 0.03, explaining
12% of the variance. More autistic symptoms predicted
less attachment security, even after differences in
developmental level were controlled for.
We also employed a hierarchical regression analysis
to determine the influence of developmental level and
number of autistic symptoms on disorganized attach-
ment. Table 4 shows that developmental level predicts
the continuous score for disorganized attachment
of the child. In the first step with developmental level
as predictor, 9% of the variance is explained,
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F (1, 57) = 5.56, P = 0.02. In step 2, with number of
autistic symptoms as predictor added to the equation,
R2 did not significantly improve. Therefore, only
developmental level significantly predicted disorgani-
zation of attachment.
Cortisol Responses
The mean values of cortisol response (t2 t1) as well
as the residuals of cortisol response after taking basal
cortisol into account are shown in Table 5. Baseline
cortisol and cortisol responsivity in reaction to stress
were significantly correlated (r = .67, P = .00). Chil-
dren who started with low basal cortisol values showed
more response in cortisol than children who started
with higher cortisol values (Fig. 1).
Table 5 displays the mean values of cortisol
response. Diagnostic groups did not differ in mean
basal cortisol values (F (3, 50) = .74, P = .53). There
was an overall significant main group effect in cortisol
response, F (4, 68) = 3.20, P = .02 when basal cortisol
was taken into account. Contrast analyses regardingthe clinical group versus the control group revealed a
stronger response in the control group, F (1, 68)
= 10.34, P < .01. However, the response of the control
children was a decrease, and not an increase that would
be indicative of stress induced by the separation and
reunion with the caregiver. The contrast analysis of
Table 4 Predictingattachment disorganization inchildren with developmentaldisorders (n = 58)
*P < .05, **P < .01
Correlation matrix Regression analyses
Developmentallevel
Autisticsymptoms
B SE B b R R2
Step 1 0.30 0.09Developmental level .06 .03 0.30*Step 2 0.34 0.12
Developmental level 1.00 .04 .03 0.17Autistic symptoms 0.61** 1.00 .05 .04 0.21
Table 5 Mean cortisol values and contrast analyses of residual cortisol response (n = 68)
N AD PDDNOS MR LD CM (SD) M (SD) M (SD) M (SD) M (SD)19 8 12 12 17
Residual cortisol response .35 (.83) .22 (.86) .27 (1.17) .19 (1.24) .62 .60Cortisol response .18 (2.58) .31 (1.90) .03 (4.98) .96 (3.87) .58 (1.78)Basal cortisol 9.65 (3.65) 8.23 (3.29) 9.58 (5.08) 7.68 (2.85) 7.11 (2.34)Contrast analyses cortisol response
Mdif SE Mdif SE Mdif SE Mdif SE Mdif SE
AD PDDNOS .58 (.40) MR .08 (.35) .49 (.43) LD .17 (.35) .41 (.43) .08 (.38) C .97 (.31)* .40 (.40) .89 (.35) .80 (.35)
*P < 0.05, contrast analyses using Bonferoni-correction
Table 3 Predictingattachment security inchildren with developmentaldisorders (n = 58)
*P < .05, **P < .01
Correlation matrix Regression analyses
Developmentallevel
Autisticsymptoms
B SE B b R R2
Step 1 0.23 0.05Developmental level .05 .03 0.23Step 2 0.35 0.12Developmental level 1.00 < .01 .04 0.02Autistic symptoms 0.61** 1.00 .09 .04 0.34*
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children with AD versus control group also showed a
significant difference, F(1, 36) = 10.60, P < .01. There
were no differences between clinical children with and
without ASD, F (1, 51) < .01, P = .93.
Contrast analyses of cortisol response in clinical
children with and without secure attachment did not
reveal any difference, and neither showed childrenwith and without the disorganized attachment classifi-
cation differences in cortisol response to the SSP.
Due to high correlations between basal cortisol level
and cortisol response, the residual of cortisol response
was calculated, taking basal cortisol into account.
Regression analyses for these residuals of cortisol
response were performed to investigate whether
number of autistic symptoms (with developmental le-
vel taken into account) and attachment security or
disorganization influenced cortisol response. Table 6
displays the univariate correlations and results of the
regression analyses. In the first step, number of autistic
symptoms was entered into the equation, contributing
significantly to the prediction of cortisol response, F(1, 48) = 6.50, P = 0.01, with 12% of the variance
explained. In step 2 (Table 6, step 2a), security of
attachment was entered into the equation. Although
the equation was significant, F (2, 48) = 3.18, P = 0.05,
R2 did not improve significantly. Therefore, only more
autistic symptoms significantly predicted less cortisol
response.
In the second hierarchical regression disorganization
of attachment rather than attachment security was
entered as predictor at step 2. R2 did not significantly
improve. Therefore, again only more autistic symp-
toms significantly predicted less cortisol response(Table 6, step 2b).
Heart Rate Variability
Hierarchical regression was employed to determine
whether the number of autistic symptoms (controlled
for developmental level) and attachment disorganiza-
tion predicted heart rate reactivity at the second
reunion (Table 7). Of the 23 children with successful
heart rate measures, 20 children were used in the
regression analysis. Three children (from the controlgroup) had no administration of the number of autistic
characteristics. The predictors were entered in two
hierarchical steps. No significant equation was found in
the first step, entering number of autistic symptoms. In
step 2, a significant contribution of attachment disor-
ganization to the regression equation predicted change
basal cortisol
3020100
cortisolresponse
10
0
-10
-20
non ASD
ASD
Fig. 1 Cortisol responses of children with and without ASD
Table 6 Multiple hierarchical regression analysis on cortisol response (n = 48)
Regression analyses
Resid Autisticsymptoms
Att. Securitydisorganization
B SE B b R R2
Step 1 .35 .12Resid Autistic symptoms .34 .13 .35*Step 2a (Att. Security) .35 .12Resid 1.00 .34 .14 .35*Autistic symptoms
Attachment security.19 1.00 < .01 .04 < .01
Step 2b (Disorganization) .42 .17Resid 1.00 -.29 .13 -.30*Autistic SymptomsDisorganization .22 1.00 .08 .05 .24
*P < 0.05
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in heart rate F(2, 19) = 2.70, P = 0.05, explaining 24%
of the variability. Disorganized attachment was asso-
ciated with more heart rate reactivity.
Examining the association between cortisol re-
sponse, autistic symptoms, and attachment disorgani-
zation in the subgroup of children included in the heart
rate analysis, we conducted a hierarchical regression
analysis (Table 7). Characteristics of this subgroup
(n = 20) are shown in Table 2. In the first step, number
of autistic symptoms was entered into the equation,
contributing significantly to the prediction of cortisol
response, F (1, 19) = 9.41, P < 0.01, with 34% of the
variance explained. Disorganization of attachment was
entered into the equation in step 2. Although the
equation was significant, F (2, 19) = 4.70, P = 0.03, R2
did not improve significantly. Thus, more autistic
symptoms significantly predicted less cortisol response,
confirming the outcome in the larger sample.
Discussion
The distribution of attachment classifications in chil-
dren with autistic spectrum disorders, other develop-
mental disorders and a non-clinical comparison group
was investigated. Contrast analyses of clinical groups
versus a control group showed that lower rates ofsecure attachment and higher rates of disorganized
attachment were found in the clinical groups. There
were no differences in distributions of attachment
classifications among the clinical groups. Further
analyses showed that severity of autism was associated
with less secure attachment, whereas lower intellectual
capabilities increased the chance for disorganized
attachment. The exploratory analyses regarding corti-
sol responses revealed that basal cortisol values
affected cortisol responsivity during the separation.
Children who started with lower basal cortisol levels
showed more responsivity than children with higher
basal cortisol levels. Controlling for basal cortisol lev-
els, more cortisol responsivity was predicted by fewer
autistic symptoms. There was no contribution of
(secure or disorganized) attachment to the prediction
of cortisol responses. Children with disorganized
attachment, however, showed more heart rate reac-
tivity during the Strange Situation.
Distribution of Attachment Classifications
Children with autism are, despite their autistic char-
acteristics, capable of forming attachment relationships
with their caregivers. However, secure attachments
were underrepresented in children with autism,
whereas the percentage of disorganized attachment
was higher compared to the normal population. Similar
to Rutgers et al. (2004) meta-analytic results, the
severity of the autistic disorder was a significant pre-
dictor for the development of an insecure attachment
relationship. It should be noted that our study on
attachment in autism is the first with 2-year-old chil-
dren.
Children with autism have also been shown to dis-
play more often disorganized attachment behavior(Capps et al., 1994; Willemsen-Swinkels et al., 2000).
In the meta-analysis of Rutgers and colleagues
(Rutgers et al., 2004), the issue of disorganized
attachment was not addressed, due to the small num-
ber of studies with autistic participants that included
disorganized attachment. The two studies that did as-
sess disorganized attachment found relatively high
percentages of disorganization. However, most of these
children were mentally retarded or showed at least
Table 7 Multiple hierarchical regression analysis with autistic symptoms and disorganization for predicting heart rate (n = 20) andcortisol response (n = 20)
Resid Autistic symptoms Disorganization B SE B b R R2
Regression analysis heart rateStep 1 .04 < .01Resid Autistic symptoms -.40 2.70 -.04Step 2 .49 .24
Resid Autistic symptoms 1.00 3.05 2.68 -.27Disorganization .43* 1.00 2.45 1.06 .54*1
Regression analysis cortisolStep 1 .59 .34Resid Autistic symptoms -.72 .23 -.59**Step 2 .60 .36Resid Autistic symptoms 1.00 -.78 .26 -.64**Disorganization .43* 1.00 .06 .10 .13
*P < .05, **P < .01; 1one-tailed
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considerable delays in their mental development
(Capps et al., 1994; Willemsen-Swinkels et al., 2000).
The confounding effects of cognitive abilities and dis-
organized attachment has therefore been an issue for
debate.
Lyons-Ruth and colleagues (Lyons-Ruth, Easter-
brooks, & Cibelli, 1997; Lyons-Ruth, Repacholi,
McLeod, & Silva, 1991) found that disorganizedattachment was related to lower mental capabilities.
Vaughn et al. (1994) found that many children with
Down syndrome were disorganized. Dissanayake and
Crossley (1997) suggested that developmental level
may influence the consistency of behavioral patterns,
and thus might be associated with (dis-)organization of
attachment. Associations between disorganized
attachment and neuro-developmental vulnerabilities
have also been reported (Green & Goldwyn, 2002). So,
below a certain level cognitive abilities may play an
important role in the classification of (disorganized)
attachment. Children who do not really understandwhat happens during the separations and reunions with
their parent may not experience stress, or they may
become too confused, which may explain why mentally
retarded children show more disorganized attachment
behaviors compared to normally developing controls.
In our study we found that children with autism as
well as children with MR showed higher percentages of
disorganized attachment. Unfortunately, all children
with autism were also mentally retarded. But in con-
trast to other studies, we were able to disentangle the
influences of autistic symptoms and developmental
level by regression analyses. Hierarchical regression
analyses showed that disorganized attachment was
mainly predicted by the developmental level of the
children, regardless of their autistic symptoms. Mental
retardation therefore appears to affect attachment
disorganization or its assessment, and the increased
level of disorganized behavior in children with autism
may be associated with their being often mentally
retarded as well (see Rutgers et al., 2004).
These findings are partly in line with the theory of
developmental delay (Rogers, Ozonoff, & Maslin-
Cole, 1991). The construction of a working model of
self and parent would be affected by the childs
inability to interpret other peoples emotional cues or
internal states (Rogers et al., 1993). A separation with
the parent, like in the SSP, may not be interpreted as
threatening. Sigman et al. (2003) found that children
with autism had no inclination to orient themselves to
the separation, which may indicate a lack of under-
standing. However, whether this developmental delay
may contribute to a delay in development of security of
attachment remains unclear. To answer that question
the children should be studied again at a later age, to
investigate the development of their attachment rela-
tionship. In sum, severity of autism is a strong predictor
for the development of insecure attachment. More
autistic characteristics enhance the risk for attachment
insecurity. Developmental level is the strongest pre-
dictor for disorganization of attachment. The lower
the developmental level, the higher the risk for thechild to develop a disorganized attachment relation-
ship, regardless of the developmental disorder of the
child.
Physiological Responses
Disorganization of attachment is related to problem-
atic stress management and problematic regulation of
negative emotions (Van IJzendoorn et al., 1999). Ele-
vations in cortisol level and heart rate variability are
also related to stress. In this study we investigated the
relation between disorganized attachment and physio-logical measurements in children with autism and other
developmental disorders. Several studies on normally
developing children reporting adrenocortical responses
to the SSP showed elevated cortisol responses in chil-
dren with a disorganized classification compared to
children with organized attachment classifications
(Nachmias et al., 1996; Spangler & Grossmann, 1993;
Spangler & Scheubeck, 1993). This is in line with the
suggestion that the neuroendocrine system is activated
when coping strategies are inadequate or unavailable
(Spangler & Grossmann, 1993), which indeed is the
case in normally developing children who show dis-
organized attachment (Hertsgaard et al., 1995). In the
current study, we found that attachment disorganiza-
tion did not contribute to differences in cortisol
response. Security of attachment (as a continuous score
based on the interactive behaviors in the SSP) did not
contribute to the difference in cortisol response either.
Controlling for mental development and basal cor-
tisol, more autistic symptoms predicted a lower cortisol
response. A blunted cortisol response in children with
PDD was also found in the study of Jansen et al.
(1999). These findings can also be interpreted as a lack
of understanding of the situation, and thereby also
partly support the developmental delay theory (Rogers
et al, 1991).
We found no differences in basal cortisol between
children participating in the Strange Situation proce-
dure at different times during the day, although we
expected an effect of circadian rhythm. Under normal
circumstances, infants develop a circadian rhythm
during the first year of life, although the age of onset of
this rhythm is still a matter of discussion (De Weerth,
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Zijl & Buitelaar, 2003). The onset of this rhythm in
children with a developmental disorder at this young
age has not been investigated yet. Developmental
disorders may be accompanied by delays in the
development of the circadian rhythm, resulting in
similar basal cortisol levels at different times in our
group. Further research into stabilization of the circa-
dian rhythm in toddlers with developmental disordersis needed. Another explanation might be that we did
not take the emotional state of the child during the
basal cortisol measurement into account. Some
researchers have argued that expression of negative
mood may release tension and thus reduce the activity
of the HPA-axis (Ahnert, Gunnar, Lamb, & Barthel,
2004; Lewis, Ramsey, & Kawakami, 1993).
Elevated heart rate reactivity was found to be
associated with disorganized attachment. This is in line
with findings of Willemsen-Swinkels et al. (2000), who
reported a difference in mean heart rate between
children with ASD with and without disorganizedattachment during a separationreunion episode. It
should be noted that we found more elevated heart
rate in disorganized children after controlling for
number of autistic symptoms and developmental level.
Our study thus extends the earlier finding of a negative
association between stress coping mechanisms and
elevated heart rate, by showing that children with
disorganized attachments display more heart rate
reactivity regardless of their specific disorder. This
provocative finding should be considered a hypothesis
for further investigation into the stress regulation of
disorganized children with clinical diagnoses. Disor-
ganized attachment may lead to dysregulation of
emotions during stress. Due to technical problems,
however, only a small group of children willing to
accept the sticky electrodes and the heart rate meter,
was included in this analysis. This subgroup might be
more advanced in their social or cognitive develop-
ment as they accepted the burden of being tested more
readily than the other children. Their advanced
developmental status might explain the association
between disorganization and stress reactivity, at least
with respect to heart rate. However, no differences
were detected in developmental level, age, number of
autistic symptoms, security of attachment, or attach-
ment disorganization between this subgroup and the
total group of children participating in the cortisol
analyses. Another explanation may be that there are
different sub-types of the autistic spectrum disorder
patterns among children with ASD. Depending on the
specific sub-type, some children may be hypo-respon-
sive, while others are hyper-responsive to various
stressors (Greenspan & Wieder, 2005). Unfortunately,
our group of children with ASD was too small to test
this hypothesis.
This is the first study on toddlers with autism,
combining attachment and physiological data at this
young age. Some limitations should be noted. The
subgroups of children were rather small, in particular
for the physiological part of the study. To understand
more about the physiological responses in childrenwith developmental disorders, larger groups are
required. Larger groups also create the possibility to
differentiate between children with an insecure-avoi-
dant and insecure-ambivalent attachment. However,
collecting this kind of data, especially the heart rate
data, is very complex in young children with develop-
mental disorders. Perhaps the children need to be
prepared for wearing electrodes by using dummy
equipment. After getting used to the dummy, the real
equipment may be accepted more easily. Larger groups
would also create the opportunity to divide the groups
of children in subgroups based on hypo- and hyper-responsivity. Second, not much is known about the
stabilization of the circadian rhythm in children with
developmental disorders like autism. We need more
information on the circadian rhythm in clinical infants
and toddlers for a more definite interpretation of
our data. Third, there was no assessment of autistic
characteristics in the control group; therefore control
children could not be included in the regression
analyses.
Taken together, in this first study on attachment in
2-year-old children with autism we found that severity
of autism was associated with more attachment inse-
curity, and mental retardation increased the chance for
disorganized attachment. Cortisol responsivity
decreased with the presence of more autistic symp-
toms. No influences were detected for attachment
security or disorganization. Nevertheless, in a small
subgroup attachment disorganization was related to
increased heart rate reactivity during the Strange Sit-
uation procedure. The heart rate findings provide fur-
ther physiological evidence for the validity of
disorganized attachment in clinical groups, but the
findings on cortisol also raise questions about the
function of disorganized behaviors of children with
autism in coping with stress, and about the interpre-
tation of disorganized attachment behaviors in men-
tally retarded children.
Acknowledgments This research was funded in part by thefollowing grants: ZonMw Dutch Organisation for ScientificResearch (NWO), Grant for Cure Autism Now, and The Korc-zak Foundation. Marinus van IJzendoorn is supported by theNWO/SPINOZA Prize of the Netherlands Organization forScientific Research, and Marian J. Bakermans-Kranenburg by
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a VIDI grant of the Netherlands Organization for ScientificResearch.
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