Attachment in Toddlers with Autism and Other Developmental Disorders

Transcription

1 J Autism Dev Disord (2007) 37: DOI /s ORIGINAL PAPER Attachment in Toddlers with Autism and Other Developmental Disorders Fabiënne B. A. Naber Æ Sophie H. N. Swinkels Æ Jan K. Buitelaar Æ Marian J. Bakermans-Kranenburg Æ Marinus H. van IJzendoorn Æ Claudine Dietz Æ Emma van Daalen Æ Herman van Engeland Published online: 8 December 2006 Ó Springer Science+Business Media, LLC 2006 Abstract Attachment was assessed in toddlers with Autistic Disorder (n = 20), Pervasive Developmental Disorder (n = 14), Mental Retardation (n = 12), Language Development Disorder (n = 16), and a nonclinical 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 developmental 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 the SSP. The findings support the importance of disorganized attachment for children with autism. Keywords Autistic disorder Æ Cortisol Æ Physiology Æ Strange situation procedure F. B. A. Naber (&) Æ M. J. Bakermans-Kranenburg Æ M. H. van IJzendoorn Department of Education and Child Studies, Centre for Child and Family Studies, University of Leiden, P.O.Box 9555, 2300 RB Leiden, The Netherlands Fnaber@fsw.leidenuniv.nl C. Dietz Æ E. van Daalen Æ H. van Engeland Æ F. B. A. Naber Rudolph Magnus Institute of Neuroscience, Department of Child and Adolescent Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands S. H. N. Swinkels Æ J. K. Buitelaar Department of Psychiatry, Radboud University of Nijmegen, Nijmegen, The Netherlands Introduction For a long time the inability to form attachment relationships 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, children s behavioral patterns can be coded according to the Ainsworth et al. (1978) attachment classification system. 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 child s behavior during reunion episodes after two short separations from the caregiver. Additionally, a category of disorganized attachment (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 figure s leave taking. Their exploration is considered a strategy aimed at minimization of attachment behavior (Main, 1990). Children

2 1124 J Autism Dev Disord (2007) 37: classified as insecure-resistant (type C) appear preoccupied 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 attachment classifications are summarized in Table 1 (Hesse, 1999, p. 399). Disorganized attachment is observed in children who 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 child s 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 IJzendoorn, and Van Berckelaer-Onnes (2004) found that attachment 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, Bakermans-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 disorganized 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. Disorganized 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 disorganization 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 mother infant interaction for children with autism versus children with disorganized attachment, which suggests that it is possible to disentangle autistic behaviors and disorganized attachment. They also found that highfunctioning 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 disorganized 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 behavior Secure 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 return of the parents, the child actively greets the parent, usually initiating physical contact. After return of the parent, the child is easily settled and returns to play. Insecure Avoidant Attachment (A) Insecure-avoidant children show little or no response to the attachment figure s 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 angry or 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 child s 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. The children may show behavior like freezing, stereotyped behavior, 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)

3 J Autism Dev Disord (2007) 37: 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). Children s coping strategies, expressed in their behavioral responses during the Strange Situation, were also monitored on a biological level (Gunnar, Mangelsdorf, Larson, & Hertsgaard, 1989). This gave rise to a number of studies on the role of cortisol in attachment. Several studies have shown cortisol reactivity in 1-yearolds 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, most studies 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 disorganized 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 (slowing 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 reactivity, 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 for children with clinical disorders like autism under the age of 4 years has not yet been studied. In Corona, Dissanayake, Arbella, Wellington, and Sigman s (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 person s 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 developmental delay to, among others, parental separation and reunion. 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 deficits in the development of understanding other people s actions or situations (Baron-Cohen, 1995; Stern, 1985). Therefore, children with autism may develop a secure attachment relationship, but this development may take more time than children without a developmental delay (Rogers, Ozonoff, & Maslin-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 classifications of these children with children with other social developmental disorders and a non-clinical control

4 1126 J Autism Dev Disord (2007) 37: 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 found in 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 metaanalysis. 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 attachments (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% securely attached (B), and 5% insecure-resistantly (C) attached. One of the three characteristic features of the autistic disorder is qualitative impairment in social relationships (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 addressed. 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 developmental level was the strongest predictor of attachment 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 include 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 developing control group. The inclusion of these groups creates the opportunity to investigate the effects of autism in the development of an attachment relationship 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 children with autism. Sigman and Ungerer (1984) suggested a relationship between cognitive development and attachment behaviors and Rogers et al. (1993) noted that developmental level was the strongest predictor of attachment security within the group of autism. In the study of Willemsen-Swinkels et al. (2000) again the highest proportion of insecure attached children were found among the PDD children with co-morbid mental retardation. Following these results and the metaanalytic 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 developmental disorders, in particular children who are mentally retarded, will show more disorganized attachment (see Rutgers et al., 2004). Studies on attachment in mentally 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 developmental 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 findings (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 reunion 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 children s 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

5 J Autism Dev Disord (2007) 37: 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-Swinkels, van Daalen, van Engeland, & Buitelaar, 2006). Children who were screen-positive for social developmental delay were invited for further investigations at the Department of Child and Adolescent Psychiatry in Utrecht. The study design and screening procedure 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 Disorder), 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 months (SD = 6.04). The developmental level, as measured by the Mullen Scales, of the children with AD was (SD = 3.66) and the developmental level of the group of children with MR (SD = 5.52). The developmental level of the group with LD was (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 developmental 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) developmental level (SD = 5.43), and children with PDDNOS without concurrent mental retardation (PDDNOS not mr, n = 8) developmental level (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 (SD = 15.82) and the developmental level of the group of children without ASD (SD = 15.29). We also included a control group (C). Control group children were screen negative on the ESAT (Early Screening of Autism Traits questionnaire), and based on parental reports and observations of the psychologists these children were free from any child psychiatric disorder. To obtain this control group (n = 18; mean age 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 child s social and cognitive development at home. The control group children were also tested for developmental level with the Mullen Scales. Descriptive 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, developmental 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 developmental quotient (M = 100, SD = 15).

6 1128 J Autism Dev Disord (2007) 37: Table 2 Characteristics and attachment distributions of the clinical and control children (n = 80) PDDNOS MR LD C ASD NASD PDDNOS without mr AD PDDNOS with mr M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) Total Boy/Girl 15/5 5/1 7/1 12/2 8/4 15/1 7/11 27/7 23/12 Age (4.96) (6.45) (5.36) (5.95) (5.85) (6.12) (1.71) (5.32) (5.92) Developmental level (3.66) (5.43) (14.83) (18.77) (5.52) (10.39) (11.49) (15.82) (15.29) Autistic symptoms (9.42) (12.01) (14.16) (16.06) (12.63) (5.71) (13.70) (9.90) Attachment n (%) n (%) n (%) n (%) n (%) n (%) n (%) Insecure avoidant (A) 3 (15%) 2 (33.3%) 1 (12.5%) 3 (21.4%) 2 (16.7%) 1 (6.25%) 0 (0%) 6 3 Secure (B) 7 (35%) 2 (33.3%) 4 (50%) 6 (42.9%) 4 (33.3%) 11 (68.8%) 15 (83%) Insecure resistant (C) 0 (0%) 1 (16.7%) 1 (12.5%) 2 (14.4%) 2 (16.7%) 1 (6.25%) 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 Heart rate analysis Age (4.43) (5.03) (7.68) (5.92) (1.73) Developmental level (4.43) (9.29) (6.81) (7.00) (11.02) Autistic Symptoms (9.65) (3.00) (13.38) 8.80 (4.15) Cortisol analysis Age (5.04) (5.01) (5.85) (5.62) (1.74) Developmental level (3.71) (19.46) (5.52) (10.16) (11.72) Autistic Symptoms (9.54) (14.54) (12.63) (5.26) 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 psychiatrist. The inter-rater reliability for the clinical diagnosis among three child psychiatrists (HvE, JB, ED) was calculated first for two diagnostic categories; ASD or other than ASD. Agreement was reached in 92% (n = 38). Agreement corrected for chance was.74 (Cohen s Kappa). Second, the inter-rater reliability was determined for all diagnostic categories. An agreement was reached of 79% (n = 38), Cohen s 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 in diagnosing 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 beginning of the visit. After the SSP several structured tasks and unstructured play situations were observed. During 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 towards 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 exploration 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 a

7 J Autism Dev Disord (2007) 37: 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 otherwise consistent and organized strategy of emotion regulation (Main & Solomon, 1990; Van IJzendoorn et al., 1999). The SSP was coded by two trained and appropriately 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 (Cohen s 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 disorganized/disoriented attachment. As in our previous study on attachment in children with autistic disorders (Willemsen-Swinkels et al., 2000), the child s baseline behavior during the preseparation episodes of the SSP was taken into account when a score for disorganization was assigned. Intercoder reliability was.77 (Pearson s correlation coefficient) for the security scale, and.66 (Pearson s 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 opportunity to quantify deficits across the autism spectrum, controlling for effects of language and cognitive delay, in individuals with significant impairments. It is suggested that quantitative measures of social reciprocity and repetitive behaviors and interests, with separate quantification of expressive language level and nonverbal intelligence, most accurately reflect the range of behavioral phenotypes in autism spectrum disorders (Lord et al., 2001). However, the ADOS module used in 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 interrater reliability for the ADOS among a child psychiatrist 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 (Cohen s 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 child s 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 20 C 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 collected 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 difference 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

8 1130 J Autism Dev Disord (2007) 37: 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 recorded with the Sport Tester Polar Vantage NV (Polar Electrode 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 interbeat intervals (IBI s) 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 periods. Changes in mean heart rate around reunion were calculated subtracting the average heart rate of the minute before the reunion from the average heart rate of the minute after reunion. Reduction of stress after the reunion will result in lower heart rate and a negative 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 dislodged 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 v 2 -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 performed to distinguish between autistic symptoms and developmental level, as well as between attachment classifications. Cortisol Analyses We first examined whether a difference in cortisol response was detected among the various diagnostic groups. The analyses were followed by contrast analyses 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 attachment, the continuous scores for attachment security and disorganization of the children were used in multiple 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 measurement of intensity of autism (number of autistic symptoms). 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, no overall 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 residual 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

9 J Autism Dev Disord (2007) 37: 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 Kolmogorov Smirnov test was used to analyze the distribution of heart rate and of cortisol values, which revealed normal distributions. 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, a preliminary 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 classifications for the various groups. The overall group comparison revealed a difference in distributions of attachment classifications, v 2 (12, n = 80) = 24.35, P =.05. The main difference was found between children 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 significant difference, v 2 (1, n = 80) = 8.18, P <.01, but no differences were detected for the distribution of secure versus insecure classifications in the ASD group compared to the non-asd group. In the clinical groups, insecure attachments were over-represented. All clinical groups, except for LD, showed differences in distribution of secure versus insecure attachments compared with the control group; AD versus C v 2 (1, n = 38) = 9.08, P < 0.01; PDDNOS versus C v 2 (1, n = 32) = 5.72, P = 0.02; and MR versus C v 2 (1, n = 30) = 7.75, P < 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 less often securely attached than the comparisons. The disorganized attachment classification was overrepresented in the clinical groups, v 2 (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, v 2 (1, n = 38) = 12.21, P < 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, v 2 (1, n = 32) = 4.26, P = 0.04; MR versus C, v 2 (1, n = 30) = 6.92, P < 0.01; and the group of LD versus C, v 2 (1, n = 34) = 3.70, P = Attachment disorganization was overrepresented in each of the clinical groups compared 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 variables, the unstandardized regression coefficients (B) and intercept, the standardized regression coefficients (b), R, and R 2 after entry of both variables: developmental 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 attachment 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 attachment. 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,

10 1132 J Autism Dev Disord (2007) 37: Table 3 Predicting attachment security in children with developmental disorders (n = 58) Correlation matrix Developmental level Autistic symptoms Regression analyses B SE B b R R 2 *P <.05, **P <.01 Step Developmental level Step Developmental level 1.00 < Autistic symptoms 0.61** * Table 4 Predicting attachment disorganization in children with developmental disorders (n = 58) Correlation matrix Developmental level Autistic symptoms Regression analyses B SE B b R R 2 *P <.05, **P <.01 Step Developmental level * Step Developmental level Autistic symptoms 0.61** F (1, 57) = 5.56, P = In step 2, with number of autistic symptoms as predictor added to the equation, R 2 did not significantly improve. Therefore, only developmental level significantly predicted disorganization 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). Children 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 regarding the 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 5 Mean cortisol values and contrast analyses of residual cortisol response (n = 68) N AD PDDNOS MR LD C M (SD) M (SD) M (SD) M (SD) M (SD) Residual cortisol response.35 (.83).22 (.86).27 (1.17).19 (1.24) Cortisol 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

11 J Autism Dev Disord (2007) 37: cortisol response non ASD ASD basal cortisol Fig. 1 Cortisol responses of children with and without ASD 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 children with and without the disorganized attachment classification 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 level 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, R 2 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. R 2 did not significantly improve. Therefore, again only more autistic symptoms 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 disorganization 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 control group) 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 disorganization to the regression equation predicted change Table 6 Multiple hierarchical regression analysis on cortisol response (n = 48) Regression analyses Resid Autistic symptoms Att. Security disorganization B SE B b R R 2 Step Resid Autistic symptoms * Step 2a (Att. Security) Resid * Autistic symptoms Attachment security < <.01 Step 2b (Disorganization) Resid * Autistic Symptoms Disorganization *P < 0.05

12 1134 J Autism Dev Disord (2007) 37: Table 7 Multiple hierarchical regression analysis with autistic symptoms and disorganization for predicting heart rate (n = 20) and cortisol response (n = 20) Resid Autistic symptoms Disorganization B SE B b R R2 Regression analysis heart rate Step 1.04 <.01 Resid Autistic symptoms Step Resid Autistic symptoms Disorganization.43* * 1 Regression analysis cortisol Step Resid Autistic symptoms ** Step Resid Autistic symptoms ** Disorganization.43* *P <.05, **P <.01; 1 one-tailed in heart rate F (2, 19) = 2.70, P=0.05, explaining 24% of the variability. Disorganized attachment was associated with more heart rate reactivity. Examining the association between cortisol response, autistic symptoms, and attachment disorganization 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, R 2 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 children with autistic spectrum disorders, other developmental disorders and a non-clinical comparison group was investigated. Contrast analyses of clinical groups versus a control group showed that lower rates of secure 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 cortisol 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 levels, 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 reactivity during the Strange Situation. Distribution of Attachment Classifications Children with autism are, despite their autistic characteristics, 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 predictor 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 children. Children with autism have also been shown to display 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 number of studies with autistic participants that included disorganized attachment. The two studies that did assess disorganized attachment found relatively high percentages of disorganization. However, most of these children were mentally retarded or showed at least