Apego en Autismo y Otros Transtornos

7/27/2019 Apego en Autismo y Otros Transtornos

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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)

1124 J Autism Dev Disord (2007) 37:11231138

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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

J Autism Dev Disord (2007) 37:11231138 1125

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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.


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.


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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