5th Congress Autism-Europe
Articulos / Proceeding
Autism-Spain

SUB GROUPS VERSUS THE SPECTRUM: A CLUSTER ANALYSIS OF A SAMPLE OF AUTISTIC CHILDREN.

Margot Prior, Richard Eisenmajer, Susan Leekam, Lorna Wing, and Judith Gould.
Universities of Melbourne and LaTrobe, Australia; Canterbury U.K.; and National Society for Autistic Children, U.K.

Introduction

Current psychiatric classification systems (e.g. DSM IV, ICD-10) have attempted to sub cateagrise children with PDD/autism into subcategories of autism and Asperger Syndrome. Research suggests that this strategy may be meeting with little success, and clinicians are confused about how to diagnose these conditions in a reliable and valid way, based on both current presentation and developmental history. The re-surgence of interest in Asperger Syndrome which has taken place over the last few years has generated considerable research focused on trying to identify similarities and differences between Asperger syndrome and autism.

A number of studies (e.g. Gillberg and Gillberg, 1989 ; Szatmari, Tuff, Finlayson, & Bartolucci, 1990; Waterhouse et al. , 1996; Ozonoff, Pennington & Rogers 1991) have compared children diagnosed with autism or Aspergers on symptom patterns, behavioural manifestations, cognitive profiles, and theory of mind tasks, to try to find more objective ways of differentiating between the disorders. It is probably fair to say that none of these attempts have led to generalisable conclusions. Generally, it seems that Asperger children are those who are at the higher levels of functioning, amongst a group of children with autistic disorder. They are not easily differentiated from high functioning autistic individuals.

One method of investigating whether there are in fact any empirically 'true' diagnostic differences is to use statistical approaches, to look at factors or clusters of symptoms which characterise putative distinguishable sub groups. There have been some previous attempts at sub categorising autistic children using cluster analytic or taxonomic techniques, most commonly using young children. Recent studies of this genre have included that of Waterhouse and colleagues (Waterhouse et al 1993, 1995; Golden & Mayer, in press) who identified two taxa or sub groups of young ( 3- 7 year old) children, primarily differentiated by developmental status (rather than by symptoms), including chronological age, and verbal IQ.

Szatmari (1992), Castelloe & Dawson (1993), Eaves et al (1994), and Siegel et al (1986) have also reported sub classification attempts. It is probably fair to say that in most of this work, differences related to severity of impairment and level of functioning rather than distinctive patterns of symptoms are found.

A further issue of interest concerns the relationship between diagnosis and classification and other marker variables for autism. Strong claims have been made for the importance of 'mentalising ability' or Theory of Mind (ToM) as a distinguishing feature of autism, and for likely connections between specific brain systems or modules and capacities of this kind. In the case of autism it is suggested that there is a basic dysfunction in those systems serving mentalising functions (e.g. Baron-Cohen, 1989; Frith, 1989 ). Originally it was believed that this ability was independent of verbal and cognitive capacities, but most recent research has suggested that this is a 'false belief'. Studies of higher functioning children including AS cases have shown some capacity for mentalising even if this is limited by comparison with that of normally developing children.

It is possible that individuals who show ToM ability may belong to a different category or sub type of autistic disorder from those who do not; hence the role of ToM as a diagnostic marker may be relevant within an autistic spectrum. This research was designed to investigate this possibility. In brief, our study was an attempt to discover whether;

  1. we could find a sub group of AS children distinct from autistic children or those with other related disorders such as PDDNOS; and whether,
  2. performance on theory of mind tasks might meaningfully differentiate between sub groups of autistic, AS, and 'other' children , and therefore might provide some external validity for sub types of PDD.

The first step in this project was to gather a large sample of children with these clinical diagnoses, and to attempt to separate them into empirically derived clusters, based on symptom patterns and developmental history. We could then look at theory of mind and other cognitive and neuropsychological characteristics to see whether they might validate clusters and also provide some clues relevant to theories of aetiology (see Manjiviona and Prior, 1995, for data on the clumsiness marker and their 1996, accompanying paper at this conference).

This paper reports on the cluster analyses undertaken to meet this aim, and the relationships between performance on Theory of Mind experimental tasks and cluster group membership.

METHOD

Subjects: A group of children diagnosed with AS or high functioning autism (HFA) or related PDD, from Britain and from the South Eastern states of Australia was initially enrolled (N = 135).

Added to this a sample is a group of 22 normal British children to provide a comparison group.

Only high functioning children were included since the study would involve theory of mind testing, which required a minimum mental age of approximately 3-4 years. In any case, the diagnostic confusion which drives this research pertains primarily to higher functioning cases.

Children had been independently diagnosed by (nineteen) clinicians from various agencies as HFA, AS, PDD-NOS, DAMP, 'autistic features'. Their ages ranged from 3 to 21 years, with a mean age of 10.22. Verbal Mental Age as assessed with the PPVT or the BPVS ranged from 2.5 to 34 years, with a mean of 9.8 years. There were 114 boys and 21 girls. (Table 1)

Measures:

The major measure used to provide a detailed account of the developmental history and behavioural characteristics of the subjects was a Diagnostic Check List which was developed by the authors and which covers the symptoms required for diagnosing according to DSM III R, DSM IV, and ICD 10 systems. Empirically derived diagnostic clusters can thus be compared with the clinical diagnosis by any one of these systems.

The checklist version used in this study was based on an earlier instrument devised by Wing (published in Rapin 1996), plus some items from the Diagnostic Interview for Social and Communicative Disorders). It covers the domains of : impairments in social interaction (including use of body language, greeting behaviour, comfort seeking, and giving, awareness of feelings of others, friendships, and awareness of social rules; imitation and play , including joint referencing and interactive play, pretend play, and imitation;

impairments in communication and imagination, including comprehension and use of language, speech characteristics, non verbal communication, imagination and pretence;

restrictions and repetition in self chosen behaviour, inciuding stereotyped movements, pre-occupations with objects and with patterns of interests, maintenance of sameness.

In addition, where possible, data is gathered on pregnancy and birth history, developmental milestones, health problems, famiiy history of any disorders, onset of the disorder (or when first noticed), treatment, and current educational milieu.

The Peabody Picture Vocabulary test - Revised is administered to the child to provide a measure of verbal mental age and standard score.

Theory of Mind measures included the now famous "Sally/Anne" task ; and the "Box of Smarties" task, as tests of 'first order' theory of mind, in this case 'false belief'. Performance on these tasks illustrates whether children have the ability to recognise that other people may have false beliefs about a situation which lead them to behave in certain ways.

We also administered a test of 'second order' theory of mind, i.e., understanding related to a belief about another person's belief. In Australia a version of Bowler's (1992) shopping story was used, and in Britain, Baron-Cohen's (1989) Ice Cream story was used. Both stories involve two characters who want to buy something, and through a series of events they develop differing knowledge states. The subject is asked to solve the problem of the kind " X thinks Y thinks that........" and to predict a character's behaviour on the basis of his/her false belief.

The checklist was completed during interview with parents in the famliy home, or (occasionally) in the clinic. In some cases questions are only relevant to either early (e.g. babbling) or current history (e.g. maintaining friendships at school or work), hence developmentally relevant data are incorporated. Children were also observed before, during, or after the interview.

The interview and assessment takes on average about two hours for each child and family.

RESULTS

Methods of Analysis

A K Means Cluster Analysis was the major statistical approach taken, to search for sub categories of children.

This approach uses an iterative partitioning method in which data are successively partitioned into the specified number of clusters.

We tried 2,3,4,5,6,7,and 8 cluster solutions, and the 3 cluster solution seemed to best agree with clinical presentation as described in the literature. It is this solution which is reported here.

(Note, 5 variables for which <10% of yes responses occurred were eliminated; these included no babbling, no spoken language, no response to communication, lack of spontaneous activity, and smearing faeces).

Three cluster solution

Cluster 1 contained 36 cases (plus all of the controls who will not be referred to again in the comparisons to follow but who serve as a kind of validation of a less problematic group), and was termed the 'Mild' group .

Cluster 2 contained 42 cases and was called the Asperger group.

Cluster 3 contained 57 cases and was termed the Autistic group.

Table 2 shows the relationships between cluster diagnosis and clinicians' diagnosis. It demonstrates that most of the clinically diagnosed AS children clustered in the AS group; children with autism clinical diagnoses were evenly divided into AS and Autism clusters, and the Mild cluster comprised most of the PDD and 'other' children, as well as a small and equivalent number of AS and autism diagnosed children.

The important question is how did these children differ from each other, i.e. what was the basis for the separation into the three clusters.

The next section provides information on discriminating variables.

1. Background variables

There were no group differences on:

age, gender, history of language delay or deviance, age of first walking, age when problems were first recognised, or family history of disorder.

The Mild group was more likely to have delayed sitting than the other two groups (p= .016)

The AS group was more likely to have delay in crawling (p = .04).

The Mild group was least likely and the Autistic group the most likely to have had a history of birth difficulties (p = .01).

The Asperger group was significantly older than the Mild group (1 1.6 vs 8.5 years; p < .05)

The verbal MA of the Autistic cluster was significantly lower at 8 years; with the AS and Mild groups equivalent at 11.7 and 10.9 years (p <.05). See Table 1.

The higher functioning children tended to cluster in the AS or mild groups.

2. Diagnostic variables (Tables 3.4.5.)

Logistic regression analyses, which allows the use of dichotomous variables (e.g. symptom or behaviour present or absent) were used as a means of identifying discriminating symptoms between the groups. This technique chooses the best (but not the only) variables to identify group differences, on the grounds of parsimony and significance.

They were run firstly comparing the AS and Autistic groups, secondly comparing the AS and Mild groups, and thirdly comparing the Autistic and Mild groups .

Prediction rates for group membership were all high across all domains, with group comparisons varying between 74% and 99% correct prediction

For most of the symptoms on which a difference was found, the direction was consistently that the autistic group was more severely impaired. This was true for comparisons with both AS and Mild clusters . There are some exceptions to this which are underlined in the tables.

Comparisons between the AS and Mild group were consistent in showing the Mild group as less impaired.

The highlights of these analyses which are relevant to our current diagnostic dilemmas include:

AS children were more likely than other groups to have a friend with similar circumscribed interests;

were more likely than autistic children to use long winded pedantic speech;

were more likely to show joint attention behaviour;

and were more likely than the Mild (but not the autistic) group to engage in one sided repetitive conversation, and to interpret language literally.

3. Theory of Mind comparisons.

Tables 6 and 7 show that there were significant group differences on each ToM task.

In each case the AS group was more likely to give responses demonstrating ToM, or mentalising ability.

However, it is important to remember that this group is also older and has a higher Verbal Mental Age by comparison with the Autistic (but not the Mild) group. Almost all AS children passed the first order tasks.

It should also be noted that well over half the AS group passed second order ToM, compared with less than a third of the Mild group (who were two or more years younger than the other two groups), and one third of the Autistic group.

Results concerning the relationships between diagnostic group membership and ToM performance are thus moderated by the age and Verbal MA associations.

They confirm that the AS cluster is less handicapped by comparison with the Autistic group in all domains.

However, symptomatically AS children are more handicapped in many domains than the Mild group; their superior performance on the ToM tasks may be explicable in terms of age and IQ differences. This does suggest that these may be more powerful influencial variables in sub group discrimination than autism related social and communicative impairments, and is consistent with arguments which have suggested that ToM may be another attribute of intellectual/cognitive development rather than a specific 'modular' cognitive factor.

SUMMARY AND DISCUSSION

1. Empirical clustering showed that it was possible to differentiate three groups or clusters roughly corresponding to those familiar to us through clinical experience. But since the group comparisons suggested that severity of symptoms was a major underlying factor, rather than particular distinctive symptom patterns, this argues for a spectrum concept of autistic type disorders, rather than for distinctive categories.

In other words there seems little evidence other than severity of symptoms and levels of cognitive functioning (which are no doubt related factors), that AS is a separable group. These children were mostly distinguished by their less impaired joint attention skills, their pedantic and long winded style of language and for their tendency to be able to have a 'friendship' based on mutual 'circumscribed' interests.

The fact that there were no cluster group differences on history of language delay or deviance needs to be highlighted. It suggests that this is not a differentiating feature which can reliably be used in differential diagnosis.

2. Comparison of clinician diagnosis with cluster group membership suggests that AS cluster children are more likely to have received an AS diagnosis, but that Autistic cluster children are as likely to have received an AS diagnosis as an Autism one. This could be related particularly to the fact that there has been a marked increase in clinician's use of the AS diagnosis for higher functioning children over the years of this study.

Chi squared comparisons showed that there were no systematic differences between clinicians (nor between Australian and British children) in the likelihood of an AS rather than an autism diagnosis.

It is also worth recalling that the sample in this study was a relatively high functioning one, excluding the substancial proportion of children who are resistant to assessment on standard tests; hence we sampled the upper part of the spectrum.

All of our AS children also met conventional diagnostic criteria (DSM III-R, ICD-10) for autism. The cluster analysis showed that despite this, they could be differentiated on some key items of behaviour.

3. Performance on ToM tasks confirmed the importance of ability /age variables which has been increasingly emerging in studies of this genre. Few AS children failed first order tasks, and more than half could also pass the second order task. Comparison with the Bowler (1992) study (Table 7), indicates that a similar proportion of his AS subjects passed the second order task.

It is also noteworthy that more than half of the Autistic group passed first order ToM, and of that sub sample presented with the second order task, more than half passed . This suggests that when verbal ability is not too far from an average level these deficits are less likely to be evident.

Again we would argue that this impairment may be primarily associated with developmental cognitive and language delay rather than simply autistic disorders.

In general, we believe that the results of this research argue for a continuum of autistic disorders in which severity of social and communicative impairments underlie individual differences. The same conclusion almost certainly applies to interpretations of theory of mind performance.

In their study comparing two taxonomically derived groups ( which broadly comprised a core autistic cluster and an 'other PDD' cluster) with APA and ICD systems, and with Wing and Gould's categorisation of 'active but odd', 'passive' and 'aloof', Waterhouse et al (1 996) considered whether the grouping reflected differentiation on the basis of level of functioning, based on the existence of a 'core' autistic group plus 'others', or based on a severity continuum or spectrum. This question is also of importance to our interpretations.

Bearing in mind that we had an older sample, and three groups rather than two, (compared with Waterhouse et al, our non autistic cluster sub divided into AS and 'Mild'), our data generally support an interpretation based on what Waterhouse called 'severity of developmental compromise' . We would argue that this is not inconsistent with the spectrum conceptualisation of autism. The ToM results demonstrated that verbal comprehension abilities were important in assisting children with considerable social impairments to pass ToM tasks. Our comparisons between AS and Mild groups highlight the importance of this variable. We have gone one step further than Waterhouse et al. in showing that a PDD group can be subdivided according to selected social impairments and ToM ability and that this latter is related to verbal capacity.

We would argue that the distinguishing symptoms of our AS group (limited friendships, pedantic speech and circumscribed interests) might also be related to level of cognitive functioning (see Tsai 1992, and Prior & McMillan 1973) suggesting that it is this which is often primary in influencing an AS diagnosis.

The fact that the developmental history variables did not discriminate between the sub groups in any diagnostically meaningful way (particularly noting the failure of the language development variable in discriminating AS children), suggests the need for caution in using such data for differential diagnosis. It suggests that etiological factors too, may support a continuum concept of autistic disorders.

REFERENCES

Baron-Cohen, S. (1991b). The theory of mind deficit in autism: How spcific is it? Brilish Journal of Developmental Psychology, 9, 301-314.

Bowier, D. M. (1992). "Theory of mind" in Asperger's syndrome. Journal of Child Psychology and Psychiatry, 33, 5, 877-893.

Castello, P., & Dawson, G. (1993). Subclassification of children with autism and Pervasive developmental Disorders: A questionnaire based on Wing's subgrouping scheme. Journal of Autism and Developmental Disorders, 23, 225-237.

Eaves, L.C., Ho, H.H., & Eaves, D.M. (1994). Subtypes of autism by cluster analysis. Journal of Autism and Developmental Disorders, 24, 3-22.

Frith, U. (1989). Autism: Explaining the enigma. Oxford: Basil Blackwell.

Ghaziuddin, M., Butler, E., Tsai, L., & Ghaziuddin, N. (1994). Is clumsiness a marker for Asperger syndrome? Journal of Intellectual Disability Research, 38, 5, 519-527.

Gillberg, I. C., & Gillberg, C. (1989). Asperger syndrome-Some epidemiological considerations: A research note. Journal of Child Psychology and Psychiatry, 30, 4, 631-638.

Manjiviona, J., & Prior, M. (1995). Comparison of Asperger syndrome and high-functioning autistic children on a test of motor impairment. Journal of Autism and Developmental Disorders, 25, 23-39.

Ozonoff, S., Rogers, S.J., & Pennington, B.F. (1991). Asperger's syndrome: evidence of an empirical distinction from high-functioning autism. Journal of Child Psychology and Psychiatry, 32, 1107-1122.

Prior, M.R., & MacMillan, M.B. (1973). Maintenance of sameness in children with Kanner's Syndrome. Journal of Autism & Childhood Schizophrenia, 3, 154-167.

Rapin, I. (1996). Preschool children with inadequate communication: developmental language disorders, autism or low IQ. Clinics in Developmental Medicine, No. 139, Mac Keith Press: London.

Siegal, B., Anders, T.F., Ciaranello, R.D., Bienenstc>ck, B., & Kramer, H.C. (1986). Empirically derived subclassification of the autistic syndrome. Journal of Autism and Developmental Disorders, 16, 275-294.

Szatmari, P. (1992). The validty of autistic spectrum disorders: A literature review. Journal of Autism and Developmental Disorders, 22, 583-600.

Szatmari, P., Archer, L., Fisman, S., Streiner, D.L., & Wilson, F. (in press). Asperger's syndrome and autism: Differences in behaviour, cognition, and adaptive functioning. Journal of the American Academy of Child and Adolescent Psychiatry.

Szatmari, P., Tuff, L., Finlayson, M.A.J., & Bartolucci, G. (1990). Asperger's syndrome and autism: Neurocognitive aspects. Journal of the American Academy of Child and Adolescent Psychiat-y, 29, 130-136.

Tsai, L. (1992). Diagnostic issues in high functioning autism. In E. Schopler & G. Mesibov (Eds), (underline) High Functioning Individuals with Autism, pp. 11-40. New York: Plenum.

Wing, L. (1981). Asperger's syndrome: A clinical account. Psychological Medicine, 11, 115-129.

Wing, L., & Gould, J. (1979). Severe impairments of social interaction and associated abnormalities in children: Epidemiology and classification. Journal of Autism and Developmental Disorders, 9,11-29.

Table 1
N=157(22 controls)
M=114

F=21


PDD
_

X CA=

Asp 11-6 (N=42)

Aut 10-3 (N=57)

"Mild" 8-5 (N=36)

Asp > Mild p<.05

_

X VMA=

(PPVT)

Asp = 11-7

Aut= 8.0

"Mild"= 10-9

Aut < Asp p<.05

Table 2
Cluster

diagnosis

CLINICIANS DIAGNOSIS
Autism AspergerPPDNOS "other"
"Mild"11 125 8
"Asperger" 1130 01
"Autism" 2627 22

p=0.000 Highly sig diff b/w groups

Table 3

FIRST ANALYSIS- which variables predict Autistic and Asperger group N=99

Variable mild/not likely ---- severe/more likely

Social domain

A1BC- dislikes physical affection asp-aut

A3DC- stereotyped comfort seeking asp-aut

A4CC- is distressed by others pain- no offer

of comfort or sympathy asp-aut

A5EC- has 1 friend with same circumscribed interest aut-asp

A5EC is moderately correlated with A7HC (O=0.5) (see below)

A6AC- unaware of need for personal modesty asp-aut

A6AC is moderately correlated with

A6BC (O=0.5) "unaware of psychological barriers"

A7AC- no interest in simple games asp-aut

A7AC is highly correlated with

A3AC (O=1.0) "never seeks comfort/ignore pain,heat, cold"

A7BC- does not point to objects to show interest/pleasure asp-aut

A7EC- involves other children only as mechanical aids in play aut-asp

A7HC- engages with other person who has same

circumscribed interest (correlated with A5EC above) aut-asp

Prediction rate of groups 97.98% with these soccial variables

Communication domain

B1CC- has speech but does not initiate conversation asp<aut

B2BC- no response to instructions asp<aut

B2CC- frequently respond to word/phrase out of context asp<aut

B3AC- use of echolalia asp<aut

B3BC- reverse pronouns asp>aut

B3CC- use of idiosyncratic words or pphrases asp<aut

B3DC- use of long winded pedantic speech aut<asp

B3DC is highly correlated to A6DC (O=1.0) " Make embarrassing remarks in public"

Prediction rate of groups 86.9%

Repetitive / Stereotyped Behaviours domain

C3BC- does collect objects for no apparent purpose aut<asp

C3DC- shows interest in parts of objects aut<asp

C3FC- unusually interested in abstract properties of objects asp<aut

C5AC- insist on maintaining same routines asp<aut

C7AC- severe impairment of spontaneous activities asp<aut

Prediction rate 74%

Table 4

SECOND ANALYSIS - which variables predict Asperger and Milds group N=78

Social Domain

A2BC - does not spontaneously wave good bye mild<asp

A2DC - does not say or sigh "hello" mild<asp

A3CC - shows distress if hurt-does not come for comfort mild<asp

A3DC - stereotyped comfort seeking mild<asp

A5CC - wants friends but poor grasp of friendship mild<asp

A5CC is moderately correlated with

A4AC (O=0.52) "unaware of others personal space"

A5EC - has 1 friend with same circumscribed interest mild < asp

A5EC is highly correlated with

A2EC (O=1.0) "shows innappropriate affection", and moderately correlated with

A7HC (O=0.58) "engage with one other specific person who has same interest"

A6DC - makes embarrassing remarks in public mild<asp

A8EC - tries to imitate social behaviour-looks bizarre mild<asp

A8EC is highly correlated with

B6BC (O=1.0) "shows appropriate use of miniature objects but play is mechanical"

A9AC - fails to animate toy animals or dolls etc mild<asp

A9AC is moderately correlated with

A9BC (O=0.52) "animates few toys but done in a limited repetitive way"

Predicition rate 98,72%

Communication domain

BlDC - engages in one sided repetitive conversations mild<asp

B2DC - interprets language literally mild<asp

B3AC - echolalia mild<asp

B3CC - idiosyncratic use of language mild<asp

B4AC - unusual tone of voice mild<asp

Predicition rate 89.74%

Repetitive stercotyped behaviours domain

C1DC - use of complex finger and hand movements mild<asp

C1DC is highly correlated to

A2EC (O=1.0) "innapropriate show of affection",

A8DC (O=I.0) "imitates person, animal or object", and

C2CC (O=I.0) "engages in self injury"

Table 5

THIRD ANALYSIS- which variables predict Autistic and Mild group N=93

Social domain

A2DC - say hello to greet mild<aut

A6AC - unaware of need for personal modesty mild<aut

A6AC is highly correlated with

ALCC (O=1.0) "no look or smile at social approach",

A3EC (O= 1.0 "comfort seeking is bizarre and repetitive",

A5EC (O= 1.0) "one friend with same interest",

A6BC (O=0.5) "unaware of psycholocical barriers"

A9AC (O=1.0) "fails to animate toys"

C5BC (O=0.5) "has limited self chosen activities", and

C5CC (O= 1.0) "prefer to cling to home or familiar place"

A6DC - makes embarrassing, remarks in public mild<aut

A6EC - lack of awareness/innapp. response to other's emotions mild<aut

A7BC - does not point to objects mild<aut

A9BC - animates few toys but done in a limited repetitive way

Prediction rate 97.9%

Communication domain

B1CC - does not initiate conversations mild<aut

B lDC - encages in one sided repetitive conversations mild<aut

B2DC - understands language in a literal manner mild<aut

B2DC is highly correlated with

A3EC (O=1.0) "comfort seeking is bizarre and repetitive" and

A9AC (O=1.0) "does not animate toys, dolls"

B3AC - echolalia mild<aut

B5AC - no use of non-verbal communication mild<aut

Prediction rate 88.2%

Stereotyped/repetitive behaviours domain

C2DC - sensory disturbances mild<aut

C5AC - interested in maintaining same routines mild <aut

C5BC- limited pattern of self -chosen activities mild<aut

C6BC - act out roles of a person, animal etc mild<aut

C6CC - special skill mild<aut

Prediction rate 83.9%

C3BC - collects objects for no apparent use mild<asp

C5BC - has a limited pattern of self-chosen activities mild<asp

C6BC - acts out roles of person etc in repetitive way mild<asp

C6CC - has a special skill mild<asp

C6CC is moderately correlated with

A5EC "has one friend with same circumscribed interest", and

A7HC "engages with one friend with same interest"

Prediction rate 92.3%


Table 6

THEORY OF MIND

There are sig diffs on both 1st order ToM games. Asp group more likely to pass.

ToM Sally /Anne p=0.000

Mild
Asp
Aut
Pass
53%
90%
58%
Fail
47%
10%
42%

ToM SMARTIES p=0.000

Mild
Asp
Aut
Pass
50%
90%
55%
Fail
50%
10%
45%

Table 7

2nd Order to M Bowler Story

(only given to First Order Passers)

p<.005

Mild
Asp
Aut
Pass
53% (28%)
63% (57%)
50% (28%)
Fail
47% (72%)
36% (43%)
50% (72%)

Figures in brackets = % of total sample

Note 1 Asp= older and have significantly higher VMA

Note 2 Passers could not explain their answers

Note 3 Similarity of results c.f.

Bowlers Asperger group who were older