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DOES GENDER INFLUENCE THE EVALUATION AND DIAGNOSIS OF AUTISM SPECTRUM DISORDER IN CHILDREN? Word count: 14,852

Shannen De Bruycker Student number: 01511156

Supervisor: Prof. Dr. Herbert Roeyers A dissertation submitted to Ghent University in partial fulfilment of the requirements for the degree of Master of Science in Educational Sciences, specialty Special Education, Disability Studies and Behavioural Disorders Academic year: 2016 - 2017

Abstract

In order to gain more insight into gender differences in autism spectrum disorder, this study

examines factors that might differentially impact whether girls or boys meet diagnostic

criteria. 52 girls and boys, with and without diagnosis of ASD, between 4-8 years old, were

age and IQ matched to control for the possible mediating effect of these factors. All of them

had been referred to a diagnostic centre for suspected ASD. The results indicate that girls

and boys are evaluated similarly. No significant gender differences between girls and boys

with ASD are found. Furthermore, uncertainties are present in the evaluation of ASD in

girls, because a discrepancy is discovered between the DSM-5 diagnostic criteria and the

decision for ASD. In this regard, the decision on diagnosis for girls can be challenging.

Furthermore, although there is no significant difference in restricted and repetitive patterns

of behaviour, interests and activities, more than one third of the girls, diagnosed with ASD,

do not fulfil the DSM-5 criteria for this domain. To conclude with, further research into

ASD gender differences is needed to answer if gender differences in ASD exist, and if so,

what the differences are. Consequently, suggestions are made for further research into

possible gender-specific criteria for ASD.

Keywords: Autism Spectrum Disorder, diagnosis, gender differences, children, diagnostic criteria Shannen De Bruycker Academic year: 2016 - 2017 Master of Science in Educational Sciences, specialty Special Education, Disability Studies and Behavioural Disorders Title: Does Gender Influence the Evaluation and Diagnosis of Autism Spectrum Disorder in Children? Supervisor: Prof. Dr. Herbert Roeyers

Abstract

Om meer inzicht te verwerven in geslachtsverschillen bij autismespectrumstoornis, worden

in deze studie factoren onderzocht die mogelijks van invloed zijn op de beslissing of

meisjes of jongens aan de diagnostische criteria voldoen en dus een diagnose ASS krijgen.

52 meisjes en jongens, met en zonder diagnose ASS, tussen 4 en 8 jaar oud, zijn gematcht

op leeftijd en IQ. Dit om een mogelijk mediërend effect van deze factoren uit te sluiten.

Alle participanten zijn verwezen naar een diagnostisch centrum bij een vermoeden van ASS.

De resultaten tonen aan dat meisjes en jongens op gelijkaardige manier geëvalueerd en

gediagnosticeerd worden. Er zijn geen significante geslachtsverschillen. Verder blijken

onzekerheden bestaande in de evaluatie en diagnostisering van ASS bij meisjes, want er is

een discrepantie tussen de DSM-5 diagnostische criteria en de beslissing voor een ASS

diagnose. Vanuit dit opzicht zorgt de diagnosestelling van meisjes voor een uitdaging.

Daarnaast, hoewel er geen significant verschil is in beperkte repetitieve gedragingen,

interesse en activiteiten, voldoet meer dan één derde van de meisjes, gediagnosticeerd met

ASS, niet aan de DSM-5 criteria voor dit domein. Ter conclusie, verder onderzoek naar

geslachtsverschillen in ASS is dus noodzakelijk om antwoord te geven op de vraag of

geslachtsverschillen effectief bestaan, en indien zo, wat deze zijn. Vervolgens zijn

suggesties voor vervolgonderzoek benoemd om mogelijke geslacht-specifieke criteria voor

ASS te onderzoeken.

Kernwoorden: autismespectrumstoornis, diagnose, geslachtsverschillen, kinderen,

diagnostische criteria

Shannen De Bruycker Academiejaar: 2016 - 2017 Master of Science in de Pedagogische wetenschappen, afstudeerrichting Orthopedagogiek Titel: Does Gender Influence the Evaluation and Diagnosis of Autism Spectrum Disorder in Children? Promotor: Prof. Dr. Herbert Roeyers

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Does Gender Influence the Evaluation and Diagnosis of Autism Spectrum Disorder in

Children?

Numerous epidemiological studies have shed light on the ASD sex ratio. Autism

spectrum disorder is approximately four times more prevalent in males than in females

(American Psychiatric Association, 2013; Fombonne, 2003). This male predominance is

one of the most consistent findings in ASD research (Rivet & Matson, 2011). On the other

hand, ASD research has failed to provide consistent findings according to gender

differences in autistic traits (Rivet & Matson, 2011; Van Wijngaarden-Cremers, et al.,

2014).

Diagnosing ASD is a complex process due to the heterogeneity in the clinical

presentation, along with symptom overlap and comorbidity of ASD with other disorders

(Lai, Lombardo, Auyeung, Chakrabarti, & Baron-Cohen, 2015). With the recognition that

ASD is relatively common, an accurate diagnosis is essential to access appropriate

treatment interventions. A proper diagnosis of ASD, especially for girls, however can be

challenging.

Therefore the aim of the present study is to explore the role of gender1 on the evaluation

and diagnosis of ASD in young girls and boys and in particular, to gain insight in factors

that might differentially impact whether girls or boys meet diagnostic criteria for ASD.

Autism Spectrum Disorder and Gender Differences

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by

persistent deficits in (1) social communication and interaction and (2) restricted, repetitive

patterns of behaviour (American Psychiatric Association, 2013). According to the

Diagnostic and Statistical Manual of Mental Disorders - fifth edition (DSM-5) ASD can be

understood as a broad spectrum in which manifestations widely vary on the two

aforementioned domains.

1 Whereas sex is biologically defined, gender is a psychosocial construct based on socio-cultural expectations. It is difficult to separate the effect of sex and gender, as gendered socialisation begins at birth. For this reason, the terms sex and gender are used interchangeably.

2

In what follows, the diagnostic criteria for Autism Spectrum Disorder 299.00 (American

Psychiatric Association, 2013) are briefly summed up. For illustrative examples of each

item, the DSM-5 can be consulted.

A. Persistent deficits in social communication and social interaction across multiple

contexts, as manifested by all of the following (currently or by history):

1. Deficits in social emotional reciprocity

2. Deficits in nonverbal communicative behaviours used for social interaction

3. Deficits in developing, maintaining, and understanding relationships

B. Restricted, repetitive patterns of behaviour, interests or activities, as manifested by at

least two of the following (currently or by history):

1. Stereotyped or repetitive motor movements, use of objects, or speech

2. Insistence on sameness, inflexible adherence to routines, ritualized patterns of verbal or

nonverbal behaviour

3. Highly restricted, fixated interests that are abnormal in intensity or focus

4. Hyper- or hyporeactivity to sensory input or unusual interest in sensory aspects of the

environment

C. Symptoms must be present in early developmental period (but may not become fully

manifest until social demands exceed limited capacities, or may be masked by learned

strategies later in life).

D. Symptoms cause clinically significant impairment in social, occupational, or other

important areas of current functioning.

E. These disturbances are not better explained by intellectual disability (intellectual

developmental disorder) or global developmental delay. Intellectual disability and autism

spectrum disorder frequently co-occur; to make comorbid diagnoses of autism spectrum

disorder and intellectual disability, social communication should be below that expected for

general developmental level (APA, 2013).

As stated before, there is a high male-to-female ratio. As a consequence, a sex

discrepancy in ASD research exists, because the majority of research has focused on males

and thus gender differences within autism have been under-investigated (Baron-Cohen, et

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al., 2014). The few studies, in which gender differences were explored, failed to provide

consistent findings (Rivet & Matson, 2011; Van Wijngaarden-Cremers, et al., 2014). More

specifically, some studies found significant gender differences, while other studies did not.

Although a systematic review of the available findings lies beyond the scope of this

study, a short overview in relation to gender differences in the core symptomatology is

given. In 1979, Wing and Gould were the first to suggest a ‘triad of impairments’:

impairments in social interaction, social communication and social imagination (Wing,

Gould, & Gillberg, 2011). The Diagnostic and Statistical Manual of Mental Disorders

adopted the fact of three basic impairments: social interaction, verbal and nonverbal

communication and repetitive and stereotyped behaviours. But in 2013, with the update of

the DSM-IV, the DSM-5 reduced this to two: impaired social communication and social

interaction (regarded as one conjoined problem) and restricted repetitive behaviours,

interests, and activities (Wing, et al., 2011). For this reason, these two broad domains will

be discussed extensively regarding gender differences.

Generally, in previous studies, there is somewhat a tendency towards gender differences

in these two domains suggesting that girls with ASD have similar problems with

communication, but boys show more repetitive behaviours than girls.

Social communication and social interaction. According to Hartley and Sikora (2009),

“subtle, but potential important differences between the male and female ASD phenotype”

exist (p. 1719). In this study, greater communication deficits in girls are noted. To the

contrary, Andersson, Gillberg, and Miniscalco (2013) found no gender differences. This in

accordance with May, Cornish, and Rinehart (2014) who did not find evidence for gender

differences either. Similar levels of social interaction and communication between affected

boys and girls were described. This finding was supported in Mandy, et al., (2012), stating

that girls had male-equivalent levels of social interaction and communication impairment.

Moreover, according to the meta-analysis of Van Wijngaarden-Cremers, et al. (2014), there

appear to be no sex differences in this domain. Nonetheless, Lai, et al. (2011) identified

superior socio-communicative skills among females with ASD.

Restricted, repetitive patterns of behaviour, interests or activities (RRB). In Hartley,

and Sikora (2009) boys showed more RRB. Several studies supported this finding of girls

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having less or milder repetitive stereotyped behaviour (Hiller, Young, & Weber, 2014;

Mandy, et al., 2012; Sipes, Matson, Worley, & Kozlowski, 2011; Van Wijngaarden-

Cremers, et al., 2014; Duvekot, et al., 2016). Hiller, Young, and Weber (2016) suggest that

it is possibly the nature of interests that differ between boys and girls. More than 50% of

the boys in this sample were interested in, or even fascinated about mechanical objects.

Boys seemingly show more obsessional interest in wheeled toys, whereas girls more in

random objects. This way it may look as less intense, or it possibly reflects the interests of

typically developing girls. However, some other studies did not find any gender differences

in this domain (Carter, Black, Tewani, Connolly, Kadlec, & Tager-Flusberg, 2007;

Holtmann, Bolte, & Poustka, 2007).

Given these inconsistent findings, limited understanding of the gender differences still

exists to date and reasons for this higher prevalence of ASD in males remain unclear.

Multiple hypotheses explaining the failure to consistent findings are suggested in the

literature.

Firstly, according to Rivet and Matson (2011) females tend to be undiagnosed,

misdiagnosed or experience delayed diagnosis, because of the differences in behavioural

features in comparison to males. The findings in Kumazaki, et al. (2015) support this

hypothesis, namely the occurrence of a female ASD phenotype. More specifically, the

researchers suggest that girls are less likely to manifest the full range of autistic traits.

Secondly, several researchers suggest a sex bias in diagnostic criteria (Giarelli, et al.,

2010; Werling & Geschwind, 2013; Lai, et al., 2015). Since the first published descriptions

of autism, by Kanner and Asperger, it has been a male-typical disorder. More specifically,

the longstanding underrepresentation of females in clinical practice and research may have

resulted in a male-biased understanding of autism (Lai, et al., 2015). Sex-specific factors

have been hypothesized to increase the risk for males to meet diagnostic criteria and

subsequently to protect females to receive an ASD diagnosis (Werling & Geschwind, 2013).

In accordance, Koenig and Tsatanis (2005, in Carette, 2014) state that standardized

instruments focus on the male representation of ASD, and so females are compared to male

standards. The results in Dean, Harwood and Kasari (2016) highlight another male bias in

the perception of ASD: “If practitioners look for social isolation on the playground when

identifying children with social challenges, then our findings suggest that girls with autism

spectrum disorder will continue to be left unidentified.” (p. 1). Girls mask their social

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challenges by interacting with peers, blending into social environments and social play.

Social isolation thus, according to the authors, cannot be a criterion to look for ASD in

children.

Thirdly, the ability for girls to camouflage or compensate is another hypothesis

explaining gender differences in ASD. Hiller, et al. (2014) stated girls have the ability,

despite their impairment, to manage their behaviours is social settings. This provides a

possible explanation why ASD may be more difficult to detect in the female population.

Accordingly, girls who show more severe impairments in autistic traits and who are thus

not able to cope with or camouflage their impairments, receive an ASD diagnosis. This is

echoed in the suggestion that girls with ASD are more severely impaired than boys with

ASD (Solomon, Miller, Taylor, Hinshaw, & Carter, 2012).

An underlying explanation for this ability to camouflage or compensate is the role of the

social context. In the early development of girls there is a more explicit focus on social

behaviour (socialisation). This leads to more learning opportunities for girls to develop

empathy, even for girls with autism (Carette, 2014).

In the fourth place, teacher reporting can provide another explanation for the

undiagnosed girls. The results in Mandy, et al. (2012) and Hiller, et al. (2014) show

teachers report fewer concerns in girls than in boys. This finding was also supported in

Hiller, Young and Weber (2016):“If it was reported that no teacher ever expressed concern

for the child’s development, the child was over 13 times more likely to be a girl.” (p. 80).

Consequently, girls are less likely to be referred for a diagnostic assessment in comparison

to their male counterpart. This explanation goes along with the hypothesis of a female

phenotype and with the possibility of girls to camouflage their impairments when in a

social setting, such as school.

Next to teachers’ concerns, other pre-diagnosis concerns are noted. Hiller, Young, and

Weber (2016) investigated ‘why’ it may be more difficult to identify ASD in girls, using a

novel method: through the examination of gender differences in pre-diagnosis concerns for

children which got an ASD diagnosis when school-aged. In particular, imitation ability and

interest in mechanical objects were strong predictors of sex. More than 70% of the girls in

their sample were reported to be able to engage in complex imitation. About 50% of the

girls in their sample did not have any or had little interest in mechanical objects.

Next, Mandy, et al. (2012) highlight methodological issues explaining the inconsistent

findings regarding gender differences in ASD. First, due to the relative scarcity of females

with ASD, studies have examined small samples and consequently lack the statistical

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power to detect significant effects. However, even studies including a large sample have

demonstrated inconsistent findings (Begeer, et al., 2012). Giarelli, et al. (2010) also

acknowledge the aforementioned problem of small sample sizes and the additional

difficulty to generalize findings to the larger population with ASD. Second, studies often

explore gender differences within a broad age range and this variety of ages may obscure

developmental effects (Hartley & Sikora, 2009).

Furthermore, the extreme male brain (EMB) theory of autism, proposed by Baron-Cohen

(2002) provides another possible explanation. The author suggests that two underestimated

facets for understanding gender differences are ‘empathising’ and ‘systemising’.

“Empathising is the drive to identify another person’s emotions and thoughts and to

respond to these with an appropriate emotion” (Baron-Cohen, 2002, p. 248) and

“Systemising is the drive to analyse the variables in a system, to derive the underlying rules

that govern the behaviour of a system.” (Baron-Cohen, 2002, p. 248). Empathising allows

us to predict another person’s behaviour and to care about how they feel. Baron-Cohen

(2002) suggests that on average females, in comparison to males, spontaneously empathise

to a greater degree. Moreover, he states that males spontaneously systemise to a greater

extent than females. One example of evidence is the matter of toy preferences. Boys are

more interested in toy cars and trains, building blocks and mechanical toys, all of which can

be ‘systemised’. Accordingly, this may be a possible explanation why boys, during

observation of play, are perceived of having more impairment in RRB.

Next, another often cited explanation for the gender differences in social interaction

relates to the assumption of increased social expectations placed on girls (Holtmann, 2007

in Kirkovski, Enticott, & Fitzgerald, 2013). Girls are expected to play female-typical games

requiring superior imaginative skills (Kirkovski, et al., 2013). Examples of such pretend

play are playing shopping, playing mommy and daddy, dressing up… As a result, young

girls with ASD, who favour games involving pretence, may go unrecognized.

Finally, there is the possibility that gender differences in children with ASD reflect those

differences found in the general population. Typically developing children in the general

population show certain gender differences as well, so it is possible that differences

between girls and boys with ASD may mirror those between typically developing girls and

boys (Mandy, et al., 2012). This hypothesis was supported in the study of Messinger, et al.

(2015), in which the sex differences in cognitive performance and repetitive behaviours

were not only apparent in high-risk children with ASD, but also in low-risk children. The

authors state: “Sex differences in young children with ASD do not appear to be ASD-

7

specific, but instead reflect typically occurring sex differences seen in children without

ASD.” (Messinger, et al., 2012, p. 1). Although there is increasing evidence for the

presence of autistic traits in the general population, this remains an important area for

future research (Hiller, et al., 2014; Rivet & Matson, 2011). Another study from Harrop,

Green and Hudry (2017) state that girls and boys with ASD were largely equivalent in their

play complexity. Girls and boys differed in their toy engagement (dolls vs. cars), but again

replicating traditional gender differences (gender-typical toys).

In what follows, two additional gender differences, which are often presented in

literature, will be discussed. A first gender difference addresses cognitive ability.

Cognitive ability, next to age, is often suggested to be the greatest mediating factor

influencing symptomatology (Kirkovski, et al., 2013). As mentioned before the 4:1 ASD

sex ratio is dominant in literature. But this prevalence of 4:1 is highly modulated by

cognitive functioning. As intellectual functioning, namely IQ, increases, the asymmetry of

the sex ratio increases as well, up to 6:1. In other words, for the high functioning end of the

spectrum, the sex ratio may increase to approximately 6:1, whereas towards the lowering

end of the spectrum, this ratio becomes approximately 2:1 (Kirkovski, et al., 2013).

As mentioned before, girls are likely to go undiagnosed or misdiagnosed. Two

additional explanations for this phenomenon are linked to cognitive ability: 1) High

functioning females are less likely to have a diagnosis (Giarelli, et al., 2010; Rynkiewicz, et

al., 2016). This can be a possible explanation for the increasing sex ratio in high

functioning people with ASD. Further, Begeer, et al. (2012) suggest that girls with an

average or above average IQ may allow them to cognitively compensate for their

impairments in social communication and interaction. In accordance, Postorino, et al.

(2015) state that girls with an average IQ may mask their clinical symptoms and thus go

undiagnosed or misdiagnosed.

Next, a possible explanation for delayed diagnosis in girls is found in Salomone,

Charman, McConachie and Warreyn (2016). According to the results of this study, there is

a significant correlation between a child’s verbal ability and the age of diagnosis. Non-

verbal children or children with less communication skills are diagnosed earlier. Also a

significant interaction of sex with verbal ability was found in this study. Girls with complex

phrase speech were diagnosed later than boys with the same level of verbal ability. In sum,

these findings suggest a delay in the diagnostic process for females, and particularly

females with better language abilities (Salomone, et al., 2016). 2) Girls, with IQ scores

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above 70, may have a higher language ability and thus being perceived as more social, so

their presentation of symptoms may be misinterpreted, leading to misdiagnosis (Halladay,

et al., 2015).

In what follows, verbal and performance ability, is further explored. Research often

suggests that IQ discrepancy profiles, with performance IQ higher than verbal IQ, are

common in children with ASD (Charman, Pickles, Simonoff, Chandler, Loucas, & Baird,

2010). In Ankenman, Elgin, Sullivan, Vincent and Bernier (2014) the discrepancy between

PIQ and VIQ, in favour of PIQ, occurred more frequent than expected, and this mainly in

boys. But these findings are not replicated, and not much is known about the discrepancy

profile in girls with ASD, because girls are less included in ASD research. Moreover,

results from several studies do not support the discrepancy intelligence profile. For example,

Charman, et al. (2010) found weak support for a distinctive PIQ–VIQ profile.

A second ASD gender difference addresses scores on the Autism Diagnostic

Observation Schedule (see Measures). Carter, et al. (2007) found no sex differences based

on the ADOS. Similarly, Holtman, et al. (2007) did not find gender differences on the

ADOS either. On the other hand, the results in Halladay, et al. (2015) show that males

obtained higher ADOS severity scores. This finding is echoed in Zwaigenbaum, et al.

(2012), in which greater overall symptom severity for boys, as measured by the ADOS-2, is

found. Furthermore, Hartley and Sikora (2008) found that boys have higher scores for RRB,

whereas girls have higher scores for social communication and social interaction the ADOS.

Diagnosing Autism Spectrum Disorder

A single test to diagnose autism spectrum disorder does not exist. Instead, a clinical

diagnosis is based on a comprehensive evaluation, consisting of information about the

child’s behaviour and development. Information from multiple sources is gathered

throughout the diagnostic process (Huerta & Lord, 2012). Firstly, the use of standardised

assessment instruments to assess multiple domains of functioning and behaviour is

recommended. Those must be completed by clinical professionals with extensive

experience in the standardized testing of children with particular expertise in assessment of

ASD.

Secondly, interviews with parents and other caregivers are included as a necessary

component. This way, information about past and current development can be acquired. On

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Multiple sources Multiple domains Multidisciplinary team

top of that, parents can describe the daily functioning of their child at home.

Thirdly, direct observation of the child in a context, in which social-communicative

behaviour and play or peer interaction can be observed, is highly recommended to

incorporate (Charman & Baird, 2002). An experienced clinician should carry out this

observation of the child’s current functioning. Next to this, cognitive testing as well as an assessment of language can be included.

Thus, testing results, information from interviews and observational data should be viewed

as complimentary components of the diagnostic evaluation (Huerta & Lord, 2012).

In addition to covering multiple domains from multiple sources, a multidisciplinary

approach to diagnostic assessment is required. “The composition of teams varies across

centres, but commonly include a paediatrician, a child psychiatrist, a speech and language

therapist, a clinical psychologist and an occupational therapist or physiotherapist.”

(Charman & Baird, 2002, p. 293).

Diagnosis should be made against current diagnostic criteria (DSM-5) using all

attainable sources of evidence. However, Charman and Baird (2002) advise us to be

careful: “The use of standardised assessment instruments and the strict application of the

DSM and ICD diagnostic criteria need to be employed with caution, as an expert clinical

view has been shown to be more accurate.” (p. 289).

Figure 1. Components of ASD Evaluation

Importance of Early Identification

Early detection and identification is generally agreed on to be crucial to receive adequate

treatment in time (Wing, et al. 2011). In its turn, early intervention improves the well-being

✓ Parent/caregiver interview medical and/or development history, report of current behaviour and functioning

✓ Observation e.g. social interaction, social communication, gestures, classroom behaviour

✓ Standardized instruments e.g. cognitive functioning, language assessment Integration of

information

Diagnosis

=

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and development of those children affected with ASD, resulting in better treatment

outcomes and better long-term prognoses (Begeer, et al., 2012).

Considering the aforementioned inconsistencies and methodological difficulties four

choices are made in this study:

(1) ASD gender differences

(2) Early childhood

(3) Controlling for age and IQ

(4) Factors related to evaluation and diagnosis of ASD

Firstly, since the presence of ASD gender differences remains unclear, this study aims

at gaining insight in those gender differences.

Secondly, because symptoms of ASD are already present in the early developmental

period and early childhood being the period in which most children are referred for

diagnostic assessment, this study opted to examine gender differences in children in early

childhood.

Thirdly, two criteria were included, namely a narrow age range (4-8) and without

intellectual disability TIQ>80, because of the possible mediating effect of these factors.

Lastly, to my knowledge, few studies have compared girls and boys in relation to

diagnosis. In fact, the study from Dworzynski, Ronald, Bolton, and Happé (2012) is among

the very first studies to address the difference between diagnosed and undiagnosed girls

versus boys (age 10-12 years old).

The aim of the present study is to explore the role of gender on the evaluation and

diagnosis of ASD in young girls and boys and in particular, to gain insight in factors that

might differentially impact whether girls or boys meet diagnostic criteria for ASD. For this

reason, four groups will be represented in this study: girls who are diagnosed, girls who are

undiagnosed, boys who are diagnosed and boys who are undiagnosed.

All this considered, the main research question is formulated: “Does gender influence

the evaluation and diagnosis of Autism Spectrum Disorder in children?” This main research

question is split up in some additional research questions:

1. Is there a difference in cognitive ability (VIQ and PIQ) between girls and boys/between

diagnosed and not diagnosed with ASD/between girls and boys diagnosed with ASD?

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2. Is there a difference in ADOS (severity score, cut-off, algorithm items, social

communication and social interaction and restricted repetitive behaviour) between

girls and boys/between diagnosed and not diagnosed with ASD/between girls and boys

diagnosed with ASD?

3. Is there a difference in language ability (receptive and expressive language) between


diagnosed with ASD?

4. Is there a difference in the thematic items, present in the descriptive reports between


diagnosed with ASD?

The main tendency towards gender differences in social communication/social

interaction and restricted repetitive patterns in behaviour, interests and activities is

investigated as well. In particular, it is hypothesised that girls show equal problems in

social interaction and communication, but less restricted, repetitive patterns of behaviour,

interests or activities in comparison to boys.

Method

Research Design

As the evaluation and diagnosis of Autism Spectrum Disorder is based upon multiple

sources, with both quantitative and qualitative data, these types of data were integrated

towards one holistic view. Neither the quantitative, nor the qualitative data takes priority, so

the chosen strategy is ‘Concurrent triangulation’. Collection of both types of data is

concurrent and the different kinds of analysis are used to confirm, cross-validate, or

corroborate findings within this study (Creswell, 2003). Both quantitative and qualitative

data were analysed in a quantitative way, using analyses of variance and Fisher’s Exact

tests.

Participants

Four groups of participants were sampled for this study: (1) a group of girls with a

clinical diagnosis of ASD (n=13), (2) a group of girls without ASD (n=13), (3) a group of

boys with a clinical diagnosis of ASD (n=13) and (4) a group of boys without ASD (n=13).

All 52 participants included in this study were selected from the database of all children

12

who have been examined for ASD in a diagnostic centre in Flanders, specialised in the

diagnostic process of ASD in children. Referral to this diagnostic centre occurs if there is

any concern or suspicion of ASD.

Participant recruitment and matching procedure. To select the participants, the

database was explored based on the following inclusion criteria: assessment years from

2013 until 2016, between 4 and 8 years old, no comorbidity and without intellectual

disability TIQ>80. In a next phase, the profiles of the children were age and IQ matched.

This resulted in a sample consisting of 52 toddlers and primary school children between 4

and 8 years old. 26 of the 52 children were male and 26 were female, 26 of the 52 children

did receive a formal clinical diagnosis of ASD, 26 did not. Table 1 displays the means and

standard deviations of age and TIQ of the four groups.

Table 1

Means and Standard Deviations of Age and TIQ

Characteristics Girls Boys

ASD No ASD ASD No ASD

(n=13) (n=13) (n=13) (n=13)

M SD M SD M SD M SD

Age (months) 73,31 17,34 70,85 14,81 70,23 14,79 71,39 14,17

TIQ 100,00 14,29 102,39 13,86 101,08 13,60 98,95 14,73

Age (months); age at the end of diagnostic process or on the moment of advice

conversation

TIQ; Total Intelligence Quotient

The database was explored in several steps. As mentioned before, the first inclusion

criterion is age, in particular between 4 and 8 years. In a first phase, girls were selected on

age. The group of girls was expected to be the smallest, which resulted in the choice to

select the girls first. In the list of 2013, girls who were born between 2005 and 2009, were

selected. In the list of 2014, girls who were born between 2006 and 2010 were selected.

This was done similarly for the list of 2015 and 2016. 50 girls were selected in this first

phase.

In a second phase, the personal files of these 50 girls were consulted in the electronic

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patient database. The files were consulted for TIQ>80. 38 girls remained in this phase.

Some girls were left out because TIQ was lower than 80, or because TIQ could not be

scored or was not known. In a third phase the 38 remaining girls were divided in two

groups according to diagnosis: one group of girls diagnosed with ASD and one group of

girls not diagnosed with ASD. This resulted in 17 diagnosed girls and 21 undiagnosed girls.

In a third and fourth phase, the first and second phase were repeated similarly for the

boys. 147 boys were selected between the age range 4-8. After consulting these files for

TIQ, 121 boys remained.

In a fifth phase, girls were age and IQ matched. Therefore the age (in months) was

calculated between date of birth and date of advice conversation or end of diagnostic

process. Matching was done manually. This resulted in 16 girls with an ASD diagnosis

that could be matched to 16 girls without an ASD diagnosis.

In the following phase, boys were also age and IQ matched to these 16 matched pairs of

girls. Not all 16 profiles from the matched girls were present in the boys’ sample. So in the

end, 13 matched subgroups (A-M) remained. One subgroup exists of one diagnosed girl,

one undiagnosed girl, one diagnosed boy and one undiagnosed boy.

Table 2

Values of the subgroups matched by age and IQ

Girl ASD Girl no ASD Boy ASD Boy no ASD Subgroup Age

(months) TIQ Age

(months) TIQ Age

(months) TIQ Age

(months) TIQ

A 87 80 78 85 82 89 75 85 B 78 85 76 89 73 89 76 84 C 56 98 63 98 66 95 60 88 D 69 99 68 106 62 92 69 97 E 57 81 52 87 52 93 62 80 F 52 107 53 111 49 101 48 114 G 93 93 94 95 90 93 89 92 H I J K L M

77 107 51 61 81 84

125 107 90 119 115 101

73 99 51 64 76 74

134 114 94 112 111 95

64 97 53 68 75 82

133 113 93 119 110 94

71 98 50 73 75 82

132 103 90 104 113 103

As mentioned before, the matching was done manually. As can be consulted in Table 2,

the differences in age and IQ are very small. The data were tested in SPSS Statistics,

14

version 24. No significant differences between mean age and mean IQ are found.

Figure 2. Flowchart of the selected participants.

Measures

As stated before, information from multiple sources is gathered throughout the

diagnostic process. The diagnostic protocol at the diagnostic centre includes following

15

interviews, observations and tests:

Choice-conversation. The term ’Choice-conversation’ replaces the term ‘intake’. This

is based on the philosophy of the ‘Choice And Partnership Approach’ (CAPA), developed

by two child psychiatrists, York and Kingsbury, in 2009. The focus of this approach is the

relationship between parents and carers, based on equal partnership (De Corte, Bal, Antrop,

& Van den haute, 2012). In the brochure from the diagnostic centre we can read the

following (translated to English): “Your first appointment is called a “choice-conversation”.

During this conversation we aim at clarifying the care needed and suitable for your child

and family. In other words: Together we choose what is important to help your son or

daughter. Hence the name ‘choice-conversation’.” (Diagnostic centre, 2016). For all

children in this study, the choice for specific assessment of ASD diagnosis was made

together with parents and professionals.

Development and family anamnesis. Via unstructured interview with the parents or

carers, information about the medical and developmental history, family history, early

concerns and current functioning is gathered. The aim of the developmental anamnesis is to

gain insight in potential delays or other important events that have occurred in the child’s

development. The family anamnesis examines the family background and assesses the

educational climate.

Play observation. A child psychiatrist observes the child’s behaviour and the child-

parent interactions while playing together, during one hour.

School observation. In Belgium, education is compulsory for all children of school-

going age. This starts at the age of 6. But most children participate in early childhood

education. Thus school observation is carried out in most cases. This way social interaction

skills, peer relationships … can be explored in a natural social environment. This takes

about two hours.

Language assessment. To evaluate a child’s communication skills, the Dutch version of

the Clinical Evaluation of Language Fundamentals - Fourth Edition (CELF-4-NL, Kort,

Schittekatte, & Compaan, 2010) is administered. The test is suitable for children and

adolescents between 5 and 21 years old (Prodiagnostiek, 2013). For the younger children,

16

the Dutch version of the Clinical Evaluation of Language Fundamentals - Preschool,

Second Edition (CELF Preschool-2-NL) was assessed.

Social cognition test. Social cognition represents the integrated processing of socio-

emotional information, needed to direct interaction and adaptive social behaviour. It

involves how we think about other people and all things social, how we perceive, process

and interpret other people’s actions and how we adjust our own actions based on other

people’s reactions (Buron, 2007). Thus, social cognition forms the basis for adjusted

(social) behaviour (Duijkers, Vissers, Verbeeck, Arntz, & Egger, 2014). Children with

ASD often have impairments in social cognition, which makes it difficult to understand

how to interact with others.

The ‘social cognition test’ used at the diagnostic centre can be described as an

observation instrument in which social cognition is measured through the exploration of

perspective taking (visual, affective, conceptual), social coherence, context blindness,

imagination and interpretation of body language.

In this study children have been tested on social cognition by a range of self-developed

tests. These self-developed tests are partly based on trainings by Prof. Dr. Herbert Roeyers

and Dr. Peter Vermeulen, and completed with materials from the diagnostic centre, based

on previous experiences. These test were carried out by the speech and language therapist.

Interpretation is based on the child’s performance of the tasks, but the child’s strategies,

methods, reasoning and attitude are also observed and taken into account.

In what follows, some examples of subtests are described. A first example of a task to

test ‘imagination’ is the following: The therapist shows a picture to the child in which a

social situation is illustrated. The child is asked what the characters would feel, think or say

in this situation. An example to test ‘conceptual perspective taking’ is the following: The

therapist shows a picture in which a lot of random objects are depicted. The child has to

name three objects he would or would not take with him if he goes on a sleepover. A third

example of a task: The therapist shows pictures or let the child act out/draw to gain insight

in the way the child recognizes or understands the four basic emotions. The aim of this task

is to test affective perspective taking. Next, an example to study ‘context blindness’: The

therapist shows pictures to the child in which some situations are illustrated, and which

contain one unrealistic element. The child is asked to look for this ‘mistake’ and correct it.

17

Cognitive ability assessment. The widely known Wechsler Intelligence Scales,

developed by David Wechsler, are used to assess cognitive ability. It is a series of

standardized tests used to evaluate cognitive abilities and intellectual abilities in children

and adults. Intelligence is defined according to Wechsler’s conception that intelligence is

not a particular ability, but “the aggregate or global capacity of the individual to act

purposefully, to think rationally, and to deal effectively with his or her environment.”

Intelligence is closely intertwined with aspects of one’s personality and overall adaptive

functioning (Wechsler, 1975).

In this study, the Wechsler Preschool and Primary Scale of Intelligence-Third Edition-

NL (WPPSI-III-NL) was used for children between 4 and 6 years. The English version was

adapted to Dutch norms by Hendriksen and Hurks. For children between 6 and 8 years old,

the Wechsler Intelligence Scale for Children-Third Edition-NL (WISC-III-NL) was used.

The WISC-III-NL is an adaptation of the English version WISC-III (Wechsler, 1992) by

Kort, Schittekatte, Bosmans, Compaan, Dekker, Vermeir, and Verhaeghe.

The Autism Diagnostic Observation Schedule (ADOS). One of the most widely used

observation instruments for assessment of ASD is the Autism Diagnostic Observation

Schedule, second edition (ADOS-2). The ADOS-2 (Lord, et al., 2012) is a semi-structured

observational assessment, which measures social interaction, communication, repetitive

behaviour, play and imagination (Molloy, Murray, Akers, Mitchell, Manning-Courtney P,

2011; Mandy, et al., 2012; Charman & Gotham, 2013). It has been described as the “gold

standard” (Molloy, et al., 2011; Falkmer, Anderson, Falkmer, & Horlin, 2013) for assessing

individuals with suspected ASD. Such tool should be used to complement and guide

multidisciplinary team clinical judgment (Falkmer, et al., 2013). The ADOS includes four

modules, based on expressive language skills (Molloy, et al., 2011). The choice of the

module depends on the individuals’ developmental and language levels, ranging from

children with no expressive language to older and verbally more capable individuals. This

way, the effect of language ability on performance can be minimized. In this study,

participants are assessed on Module 2 and Module 3. Module 2 is intended for individuals

with some phrase speech who are not verbally fluent. Module 3 is intended for verbally

fluent children and young adolescents (de Bildt, et al., 2011).

In what follows, other assessments often used in the diagnostic process are described.

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These are not used by itself for data analysis, yet the descriptive information of these

assessments, if available, is used for a more holistic view to decide on the score of the

thematic items (see further).

Attention assessment. To measure attention skills in children, the Test of Everyday

Attention for Children (TEA-Ch) is used. The TEA-Ch was published in 1998 by Manly,

Robertson, Anderson, and Nimmo-Smith (Pearson Education, 2016). This original version

was adapted in 2007 to Dutch norms by Fontainen, Dekker, Harcourt, Schittekatte, and

Groenvynk (Prodiagnostiek, 2014). The TEA-Ch comprises nine subtests, which helps us

“to assess the ability of children to selectively attend, sustain their attention, divide their

attention between two tasks, switch attention from one task to another, and withhold

(inhibit) verbal and motor responses.” (Pearson Education, 2016).

Phenomenological study. Sometimes a phenomenological study is carried out. The aim

is to offer insight into how a child, in a given context, makes sense of a given event,

experience or phenomenon. Events, such as the divorce of the child’s parents, can be

stressful life events, which have an impact on the child’s functioning and behaviour.

Questionnaires. Alongside the assessments in which the child undergoes the tests,

information can also be gained from some questionnaires.

The Autism Diagnostic Interview-Revised (ADI-R). The Autism Diagnostic Interview-

Revised (ADI-R) is a standardized, semi-structured interview for caregivers of individuals

who have been referred for the evaluation of possible ASD. The instrument focuses on

behaviour in three main areas: communication and language, social interaction, and

restricted, repetitive behaviours. The ADI-R is appropriate for individuals with mental ages

from 18 months and above. The scores on the ADI-R are based on the caregiver’s

descriptions of the child’s behaviour (Lord, Rutter, & Le Couteur, 2003).

The Child Behavior Checklist (CBCL). The Child Behavior Checklist (CBCL;

Achenbach, 1991), a component of the Achenbach System of Empirically Based

Assessment (ASEBA), is a parent report form to screen for emotional, behavioural and

social problems. Two versions are used in this study: The CBCL/1½-5 (Achenbach &

Rescorla, 2000) for preschool children and the CBCL/6-18 (Achenbach & Rescorla, 2001)

19

for school-age children. Studies have explored the relationship between the CBCL profiles

and ASD symptomatology (Mazefsky, Anderson, Conner, & Minshewc, 2011). Bolte,

Dickhut, and Poustka (1999) found that children with autism had scores for Social, Thought,

and Attention problems that were nearly three standard deviations above controls. Similarly,

Noterdaeme, Minow, and Amorosa (1999) found that 66% of the scores of children with

autism were above average on the Attention Problems, Social Problems, and Withdrawn

scales. Another study, Duarte, Bordin, de Oliveria, and Bird (2003) found that the CBCL

could be used to differentiate children with autism from both children without or with

another psychological disorder. More specifically, the Thought Problems scale was found

to discriminate the typical developing children from the children with autism, with

approximately 100% accuracy.

Teacher Report Form (TRF). The Teacher’s Report Form (TRF) is a parallel form to

the Child Behavior Checklist (CBCL), completed by the teacher. The item content of the

TRF closely matches the CBCL content. It is used to assess problem behaviour, academic

performance and adaptive functioning (Frick, Barry, & Kamphaus, 2010).

Advice. The last phase of the diagnostic process is the ‘advice conversation’. Test

results are communicated to the parents and advice related to future care, interventions …

suitable for their child is given and discussed.

Procedure

After the collection of age and TIQ, in order to match, more quantitative and qualitative

data was collected, browsing through the personal files in the electronic patient database.

Data collection. First, the scores on verbal IQ and performance IQ were collected

(see Table 3).

Second, all scores on the ADOS or ADOS-2 were collected. 3 of the 52 participants

were not assessed on the ADOS. Before analysis of these ADOS scores was possible, these

raw scores were converted into comparative severity scores. This way these total scores on

ADOS or ADOS-2 and module 2 or module 3 could be compared in the analysis. The

reason to convert raw scores is twofold: First, the total score for ADOS is not equally

calculated as the total score for ADOS-2. The total score for ADOS is a summation of a

20

score on the Communication domain and a score on the Social domain. Gotham, Risi,

Pickles and Lore (2007) state: “To receive an ADOS classification of Autism or ASD, an

individual’s scores must meet separate cut-offs in a Communication domain, a Social

domain, and a summation of the two.” … “At issue, too, is the inclusion of restricted,

repetitive behaviour (RRB) items in an ADOS diagnostic total. Currently, these items

appear on the algorithm but do not contribute to the total score that results in a

spectrum/non.” But the total score for ADOS-2 is a summation of a score on Social Affect

(SA) and a score on Restricted, Repetitive Behaviours (RRB). The revised algorithm now

consists of two new domains, SA and RRB, combined to one total score (Gotham, et al.,

2007). Second, this way scores on module 2 and module 3 can be compared. Also age of

the participant is taken into account.

To calculate comparison scores for ADOS, the table ‘Mapping of ADOS raw totals onto

calibrated severity scores’ found in Gotham, Pickles, and Lord (2009) was used. This way

raw totals were converted onto calibrated severity scores, ranging from 1 to 10.

Similarly, the ADOS-2 contains a conversion table to calculate the comparison score.

This results in a score from 1 to 10 as well. The range from 1 to 10 gives an indication of

the level of autism spectrum-related symptoms. A score of 1 meaning minimal to no

evidence, score 2-3-4 meaning low, score 5-6-7 meaning moderate and score 8-9-10

meaning high. Severity scores of all 52 participants, except 3 without ADOS assessment,

can be found in Table 4.

Table 3

Verbal and performance IQ

Girl ASD Girl no ASD Boy ASD Boy no ASD Subgroup VIQ PIQ VIQ PIQ VIQ PIQ VIQ PIQ A 90 75 86 88 78 105 94 78 B 80 95 84 89 97 93 92 79 C 112 89 98 102 105 91 94 85 D 91 106 105 102 98 91 94 106 E 86 77 80 91 92 104 84 87 F 94 98 105 115 109 95 109 114 G 88 101 86 107 106 81 97 88 H I J K L M

119 112 92 117 123 102

129 99 87 122 102 99

138 105 82 124 101 111

126 121 104 97 115 78

131 106 89 138 106 98

122 118 100 102 108 91

119 102 84 106 106 102

145 104 106 95 118 104

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Table 4

Severity scores on ADOS/ADOS-2 ranging from 1 to 10

Girl ASD Girl no ASD Boy ASD Boy no ASD Subgroup Severity score Severity score Severity score Severity score A B C D E F G H I J K L M

4 2 5 3 6 5 10 8 9 5 4 2 9

1 1 1 6 - 5 5 4 2 2 6 2 4

8 4 4 5 8 7 5 6 5 7 6 4 6

- 9 3 2 4 5 9 3 2 1 - 4 5

Retrieved from: Gotham, Pickles, & Lord (2009), p. 701.

Furthermore, it was explored whether a participant met the cut-off for ASD according to

the ADOS. Based on the severity score of ADOS, the decision for ‘below cut-off’ (0) and

22

‘above cut-off’ (1) was made. A severity score of 4 corresponds to the cut-off score of 7 for

ASD. Children, who got a severity of less than 4, were coded as ‘below cut-off’ and

children, who got a severity score of 4 or more than 4, were coded as ‘above cut-off’. These

codes can be found in Table 5.

Table 5

Below or above ADOS cut-off score based on ADOS severity score

Girl ASD Girl no ASD Boy ASD Boy no ASD Subgroup Severity score Severity score Severity score Severity score A B C D E F G H I J K L M

1 0 1 0 1 1 1 1 1 1 1 0 1

0 0 0 1 - 1 1 1 0 0 1 0 1

1 1 1 1 1 1 1 1 1 1 1 1 1

- 1 0 0 1 1 1 0 0 0 - 1 1

Third, all scores on the ADI-R were collected. During the collection became clear that

not all caregivers of the 52 participants were interviewed. Only 23 scores were found. For

this reason, the scores on this item were not used for data analysis.

Next, algorithm scores on 8 topics, which are included in ADOS module 2, ADOS

module 3, ADOS-2 module 2 and ADOS-2 module 3, were collected. On the ADOS

algorithm form, items are scored 0, 1 or 2 based on what is observed during this semi-

structured observational assessment. Kroncke, Willard and Huckabee (2016) explain: “A

score of 0 indicates that the skill is present and consistent with typical development. A

score of 1 indicates partial proficiency on a skill and a score of 2 indicates challenges with

the item or an absence of the skill.” (p. 164). The 8 items, all similar for module 2 and 3 of

ADOS and ADOS-2 are the following: (A) Unusual eye contact, (B) Quality of social

overtures, (C) Amount of reciprocal social communication, (D) Overall quality of rapport,

(E) Stereotyped/ idiosyncratic use of words or phrases, (F) Unusual sensory interest in play

matter/person, (G) Hand and finger and other complex mannerism, and (H) Excessive

23

interest in unusual or highly specific topics/objects or repetitive behaviours.

For further analysis, it was opted to combine these to new items, in accordance to the

two domains (SA and RBB) in ADOS-2. The first four items (A) + (B) + (C) + (D) were

combined to ‘social communication and social interaction’ and the last four (E) + (F) +

(G) + (H) to ‘restricted repetitive behaviour’.

Later, scores on CELF-4-NL or CELF Preschool-2-NL were collected. But during the

data collection of these scores some issues became clear. First, 15 of the 52 participants did

not have any percentile score on CELF. Yet, some of them had scores on R-TOS, another

test for language assessment. Still, 6 of the 52 participants did not have any language

assessment at all. Second, Receptive Language Index score (RLI) or Expressive Language

Index score (ELI) were not mentioned in the reports, only percentile scores on several

subtests. Third, exploring the scores on the subtest, the researched observed that some

participants were assessed on only one or two subtests for Receptive Language or

Expressive Language.

Thus, analysis of the percentile scores was not executed because of the gaps in the data.

The researcher opted for a categorical subdivision. The 46 remaining participants were

given a code 0, 1 or 2 for Receptive Language and similarly for Expressive Language.

Code 0 stands for ‘below normal variance’, which means percentile scores lower than 16.

Code 1 stands for ‘normal variance’, which means percentile scores between 16-84 (scores

within 1 standard deviation of the mean). Code 2 stands for ‘above normal variance’,

referring to percentile scores higher than 84.

24

Table 6

Receptive and expressive language codes

Girl ASD Girl no ASD Boy ASD Boy no ASD Subgroup RL EL RL EL RL EL RL EL A 1 1 1 1 . . 1 1 B . . 0 1 1 1 0 0 C 1 1 1 1 0 1 0 0 D 1 1 . 0 0 0 1 1 E 0 0 0 0 . . 0 0 F 1 1 1 1 1 1 1 1 G 1 1 1 0 0 1 0 0 H I J K L M

. 1 1 1 . 0

. 2 1 2 . 1

1 0 0 1 1 1

2 1 0 1 1 1

. 0 0 . 1 1

. 1 1 . 1 1

2 1 0 1 1 1

2 1 1 1 1 1

Scores on CBCL or TRF or other tests/questionnaires were not collected because not

half of the participants were scored on these tests.

Next, the collection of qualitative information throughout all observations, development

and family anamnesis and other reports was completed.

Naturally all descriptive reports (during assessment of ADOS, during play

observation…) contain a set of themes, such as body language, reciprocity… A thematic

analysis of the descriptive reports was done by systematically defining categories. Some of

these categories had been set prior to the start of the analysis and were based upon the

literature study and the diagnostic criteria for ASD. Some of these categories, or subsequent

keywords, were defined during the data analysis, because they were derived from all the

available data. Since the researcher did not carry out the diagnostic assessments, the

available data were not known beforehand. The different categories and keywords, which

are defined before and during the analysis, can be found in Appendix A. Each category was

given a specific colour or symbol, which was then attributed to fragments of the text.

After doing this for all 52 files, 19 themes present in the files remained. Each item was

given a score 0, 1 or 2. The meaning of these scores can be compared to the ADOS

algorithm scores. 0 indicates no problem or the skill is present or qualitatively adequate, 1

25

indicates partial proficiency on a skill or varying in presence or quality and

2 indicates challenges or the skill is absent or qualitatively inadequate. Important to note is

that the score refers to the present functioning of the child, except for the item ‘Early

development (<3 years)’. The item ‘Early development (<3 years)’ has been interpreted as

a broad item. This can refer to cognitive delay in development, problems in speech,

symptoms from ASD visible e.g. no interaction with other children, difficulties with

changes… The meaning of score 0, 1 or 2 on the item ‘Familial occurrence’ also needs

some explanation: score 0 refers to no familial occurrence of ASD, score 1 indicates that

there is someone diagnosed with ASD in the broader family, score 2 indicates that one of

the siblings or parents are diagnosed with ASD. To decide which score was given to a

specific item, the descriptive reports and the ADOS were mutually consulted.

To increase the external reliability of this study, the procedure used to decide on a score

0, 1 or 2 is illustrated by a few examples.

First example is the following: During the ADOS assessment, a score of 2 is given for

unusual eye contact. But during the cognitive ability assessment and play observation, the

psychologist or child psychiatrist reports adequate use of eye contact. This means eye

contact varies in different situations, with different persons. A score of 1 (“varying”) is

given in this example.

Second example: During school observation, the child hardly interacts with peers. The

teacher confirms that the child rather plays alone during playtime, but during class projects

the child interacts in an adequate way with other children. The child has according to the

child itself, the teacher and the parents one best friend. A score of 1 is given in this example,

based on the variety in relationships with peers. It is not a score 0 (“no problem”) because

the child does not play with friends all the time, but it is also not a score 2 (“challenging”)

because relationships with peers are not problematic.

Third, when no information (by the parents) was given about a certain item, for example

‘Relationships with peers’, this was scored as 0, assuming that problems on this item would

have been mentioned during intake and family anamnesis.

To increase the internal reliability of this study, the researcher chose to bring in the

opinion of a second researcher. The second researcher is the researcher’s mentor and works

at the diagnostic centre as a psychologist. The mentor has a lot of experience with assessing

the ADOS and also relevant experience in research. Because of limited time, it was not

26

possible for the second researcher to score each file independently. The second researcher

scored 2 files, after which the scores were compared. This resulted in a discussion about

scoring 0, 1 or 2 and this way it became clearer what is worth a score 0, 1 or 2. After this

discussion the researcher adapted the scores. This resulted in some changes from 0 to 1 or

from 1 to 2.

Next, a total score based on these thematic items was calculated. For example: 1 on eye

contact + 2 on reciprocity + … = a total score of 14. This was done for 17 themes, not all

19. ‘Early development’ and ‘Familial occurrence’ were left out, because the researcher

was interested in the difficulties on the items in current functioning. The total score per

participant can be found in Table 7.

Table 7

Total score on thematic items

Girl ASD Girl no ASD Boy ASD Boy no ASD Subgroup Total score Total score Total score Total score A B C D E F G H I J K L M

12 11 18 11 18 10 11 16 12 8 10 10 17

2 7 6 7 12 15 13 6 4 9 6 6 5

18 15 4 16 17 18 5 18 17 17 9 13 13

10 6 4 8 14 11 13 8 5 7 11 15 12

Lastly, the researcher investigated whether the 13 girls and boys who got an ASD

diagnosis meet the DSM-5 diagnostic criteria to receive a diagnosis of Autism Spectrum

Disorder. This was done similarly for the 13 girls and boys who did not receive the

diagnosis. This was based on the following conceptual model (see Figure 3). In particular

the criteria for social communication/social interaction and restricted, repetitive patterns of

behaviour, interests or activities are interesting to analyse, and to answer the often stated

hypothesis: Girls show equal problems in social interaction and communication, but show

27

less restricted, repetitive patterns of behaviour, interests or activities in comparison to boys.

A code 0 was given for ‘criteria not met’ and a code 1 was given for ‘criteria met’. This

was done for ‘A. Persistent deficits in social communication and social interaction’ and

‘B. Restricted, repetitive patterns of behaviour, interests or activities’ (see Table 8).

28

Diagnostic criteria according to DSM-5

(APA, 2013)

Conceptualized by:

- algorithm items from ADOS

- thematic items from descriptive reports

A. Persistent deficits in social communication and social interaction across

multiple contexts, as manifested by all of the following (currently or by history):

1. Deficits in social emotional reciprocity (B) Quality of social overtures

(C) Amount of reciprocal social

communication

- Reciprocity

2. Deficits in nonverbal communicative

behaviours used for social interaction

(A) Unusual eye contact

- Eye contact

- Body language (facial expression,

gestures)

3. Deficits in developing, maintaining,

and understanding relationships

- Relationships with peers

- Play with others

B. Restricted, repetitive patterns of behaviour, interests or activities, as

manifested by at least two of the following (currently or by history):

1. Stereotyped or repetitive motor

movements, use of objects, or speech

(E) Stereotyped/ idiosyncratic use of

words or phrases

- Stereotyped language

2. Insistence on sameness, inflexible

adherence to routines, ritualized patterns

of verbal or nonverbal behaviour

- Sameness (routines, patterns)

- Stereotyped behaviour

3. Highly restricted, fixated interests that

are abnormal in intensity or focus

(H) Excessive interest in unusual or

highly specific topics/objects or repetitive

behaviours.

- Preoccupation

4. Hyper- or hyporeactivity to sensory

input or unusual interest in sensory

aspects of the environment

(F) Unusual sensory interest in play

matter/person

- Sensory aspects (pain, sounds, light,

textures, smelling, touching, food)

Figure 3. Conceptual model to check whether the diagnostic criteria of DSM-5 are fulfilled.

29

Table 8

DSM-5 diagnostic criteria met or not met

Girl ASD Girl no ASD Boy ASD Boy no ASD Subgroup A B A B A B A B A 1 1 0 0 1 1 0 0 B 0 0 0 1 0 1 0 0 C 1 1 0 0 1 1 0 0 D 1 0 0 0 0 1 0 0 E 1 1 0 0 1 1 1 0 F 0 1 0 0 1 1 1 0 G 1 0 0 0 0 1 1 0 H I J K L M

0 1 1 1 0 1

1 1 0 1 1 1

0 0 0 0 0 0

0 0 1 0 0 1

1 1 1 1 1 1

1 1 1 1 1 1

0 0 0 0 0 0

0 0 0 1 1 0

An overview of the data collection is given. Per participant, it resulted in a set of data:

- VIQ and PIQ

- ADOS severity score (ranging from 1 to 10)

- ADOS cut-off for ASD (0 or 1)

- 8 ADOS algorithm scores (0, 1 or 2)

- ADOS social and ADOS restricted repetitive behaviour

- Categorical score for receptive and expressive Language (0, 1 or 2)

- Categorical scores for 19 themes present in the descriptive files (0, 1 or 2)

- Total score for 17 themes present in the descriptive files

- DSM-5 criteria (0 or 1)

Data analysis. All data were put in a matrix, with all scores per participant.

Statistical analysis was completed using SPSS Statistics version 24. Effects of gender and

diagnosis, on all numeric dependent variables, were explored using two-way analysis of

variance (ANOVA). Interaction effects were also explored. For all categorical dependent

variables, Pearson Chi-square tests were executed. During the analysis of 2x3 chi-square

tests, cell counts less than 5 appeared. For statistical reasons, it was opted for 2x2 cross

tabulations and so Fisher’s Exact tests were used. As each item consisted out of 3

30

categories, codes had to be converted to only 2 categories. For ‘Receptive language’ and

‘Expressive language’ only a few times code 2 (above normal variance) was given. So it

was opted to make a code 0, meaning ‘below normal variance’ and a code 1 meaning

‘normal or above normal variance’. Similarly, this was done for the ADOS algorithm

scores and the thematic items. Originally each item was attributed a code 0 ‘no problem’,

code 1 ‘varying’ and code 2 ‘challenges’. Because no major differences between ‘varying’

(code 1) and ‘challenging’ (code 2) existed, it was opted to take these two codes together as

one. This resulted in a code 0 ‘no problems’ and a code 1 ‘challenges’.

Significance level of α = .05 was employed. Analyses that reached significance at this

level are denoted with an asterisk in the next section “Results”. Cross tabulations in which

significant effects are found can be consulted in the text, cross tabulations in which no

significant effects are found can be consulted in Appendix B.

Results

Cognitive Ability

Verbal IQ. No effect of gender is found (F(3, 48) = 0,056, p = .081). No effect of

diagnosis is found (F(3, 48) = 0,449, p = .506). No interaction effect of gender x diagnosis

is found (F(3, 48) = 0,424, p = .518).

Performance IQ. No effect of gender is found (F(3, 48) = 0,001, p = .971). No effect of

diagnosis is found (F(3, 48) = 0,346, p = .559). No interaction effect of gender x diagnosis

is found (F(3, 48) = 0,195, p = .661).

31

Table 9

Means and Standard Deviations of VIQ and PIQ

Variables Girls Boys


(n=13) (n=13) (n=13) (n=13)

M SD M SD M SD M SD

VIQ 100,46 14,40 100,38 17,30 104,08 16,04 98,69 9,97

PIQ 98,38 15,29 102,69 14,10 100,08 11,53 100,69 18,55

ADOS

ADOS severity score. No effect of gender is found (F(3, 45) = 0,962, p = .332). A

significant effect of diagnosis is found (F(3, 45) = 9,137, p < .005*). No interaction effect

of gender x diagnosis is found (F(3, 45) = 0,348, p = .539).

Table 10

Means and Standard Deviations of ADOS severity score

Variable Girls Boys


(n=13) (n=12) (n=13) (n=11)

M SD M SD M SD M SD

ADOS 5,54 2,70 3,25 1,96 5,77 1,43 4,27 2,65

severity

ADOS cut-off for ASD. There is a significant effect of diagnosis (p = .01*) on the

ADOS cut-off. There is no effect of gender (p = .345).

32

Table 11

Cross tabulation of diagnosis and ADOS cut-off

ADOS cut-off

Diagnosis

ASD No ASD

Below Count 3 11

% within ADOS cut-off 21,4% 78,6%

Above Count 23 12


ADOS algorithm topics.

(A) Unusual eye contact: No effect of gender is found (p = .072) and no effect of

diagnosis is found (p = .382).

(B) Quality of social overtures: No effect of gender is found (p = .013), but a significant

effect of diagnosis is found (p = .013*). Children who have received an ASD diagnosis

show significant more problems in the quality of social overtures.

Table 12

Cross tabulation of diagnosis and ADOS algorithm topic (B)

ADOS algorithm topic (B)

Diagnosis

ASD No ASD

No problem Count 4 12

% within ADOS (B) 25,0% 75,0%

Challenges Count 22 11

% within ADOS (B) 66,7% 33,3%

(C) Amount of reciprocal social communication: A significant effect of gender (p

= .025*) is found. Boys show more problems in reciprocal social communication.

No effect of diagnosis is found (p = .205). But when looked at this gender difference in

diagnosed children only, this effect is not significant (p =.332).

33

Table 13

Cross tabulation of gender and ADOS algorithm topic (C)

ADOS algorithm topic (C)

Gender

Girl Boy


% within ADOS (C) 78,6% 21,4%


% within ADOS (C) 40,0% 60,0%

(D) Overall quality of rapport: No effect of gender is found (p = .189) and no effect of


(E) Stereotyped/idiosyncratic use of words or phrases: No effect of gender is found (p =

1) and no effect of diagnosis is found (p = .154).

(F) Unusual sensory interest in play matter/person: No effect of gender is found (p

= .289) and no effect of diagnosis is found (p = .145).

(G) Hand and finger and other complex mannerism: No effect of gender is found (p = 1)

and no effect of diagnosis is found (p = .706).

(H) Excessive interest in unusual or highly specific topics/objects or repetitive

behaviours: No effect of gender is found (p = .754) and no effect of diagnosis is found (p

= .057).

ADOS social communication and social interaction (A+B+C+D): No effect of gender

is found (F(3, 45) = 2,315, p = .135). No effect of diagnosis is found (F(3, 45) = 3,667, p

= .062). No interaction effect of gender x diagnosis is found (F(3, 45) = 0,783, p = .381).

34

ADOS restricted repetitive behaviour (E+F+G+H): No effect of gender is found (F(3,

45) = 0,292, p = .591). A significant effect of diagnosis is found (F(3, 45) = 9,634, p

= .003*). No interaction effect of gender x diagnosis is found (F(3, 45) = 0,023, p = .901).

Table 14

Means and Standard Deviations of ADOS S and ADOS R

Variables Girls Boys


(n=13) (n=12) (n=13) (n=11)

M SD M SD M SD M SD

ADOS S 3,69 2,39 2,00 1,91 4,08 1,89 3,45 2,21

ADOS R 1,62 1,50 0,58 0,90 1,85 1,35 0,73 0,91

ADOS S: ADOS social communication and social interaction

ADOS R: ADOS restricted repetitive behaviour

Language Ability

Receptive language. No effect of gender is found (p = .347) and no effect of diagnosis

is found (p = 1).

Expressive language. No effect of gender is found (p = 1) and no effect of diagnosis is

found (p = .154).

Thematic Items

Eye contact. No effect of gender is found (p = .165) and no effect of diagnosis is found

(p = .165).

Body language (facial expression, gestures). No effect of gender is found (p = .776)

and no effect of diagnosis is found (p = .393).

35

Speech (accent, intonation, rhythm). No effect of gender is found (p = .565), but a

significant effect of diagnosis is found (p= .003*).

Table 15

Cross tabulation of diagnosis and speech

Speech

Diagnosis

ASD No ASD


% within speech 33,3% 66,7%



Stereotyped language. No effect of gender is found (p = 1), but a significant effect of

diagnosis is found (p= .048*).

Table 16

Cross tabulation of diagnosis and stereotyped language

Stereotyped language

Diagnosis

ASD No ASD


% within stereotyped language 36,7% 63,3%



Relationships with peers. No effect of gender is found (p = .368) and no effect of


Reciprocity. No effect of gender is found (p = .726) and no effect of diagnosis is found

(p = .075).

36

Social acceptable behaviour. No effect of gender is found (p = 1) and no effect of


Emotion regulation. No effect of gender is found (p = .771) and no effect of diagnosis

is found (p = .382).

Fantasy play. No effect of gender is found (p = .743) and no effect of diagnosis is found

(p = .743).

Play with others. No effect of gender is found (p = .083) and no effect of diagnosis is

found (p = .083).

Stereotyped behaviour. No effect of gender is found (p = .726) and no effect of


Stereotyped body movement. No effect of gender is found (p = .726) and no effect of


Preoccupation. No effect of gender is found (p = .349) and no effect of diagnosis is

found (p = .116).

Sameness (routines, patterns). A significant effect of gender is found (p= .012*), but

no effect of diagnosis (p = .164). When looked at diagnosed children only, this effect of

gender is not significant anymore (p = .096).

37

Table 17

Cross tabulation of gender and sameness

Sameness

Gender

Girl Boy


% within sameness 70,8% 29,2%



Sensory aspects (pain, sounds, light, textures, smelling, touching, food). No effect of

gender is found (p = 1) and no effect of diagnosis is found (p = 1).

Behavioural problems. No effect of gender is found (p = 1) and no effect of diagnosis

is found (p = .577).

Impairment in functioning. No effect of gender is found (p = .565) and no effect of


Early development (<3 years). No effect of gender is found (p = .400) and no effect of

diagnosis is found (p = 1).

Familial occurrence (siblings/parents vs. family). No effect of gender is found (p

= .083) and no effect of diagnosis is found (p = .565).

Total score on 17 categories. No effect of gender is found (F(3, 48) = 2,197, p = .145),

but a significant effect of diagnosis is found (F(3, 48) = 18,535, p= .00*). No interaction

effect is found (F(3, 48) = 0,125, p = .726).

38

Table 18

Means and Standard Deviations of total score

Variable Girls Boys


(n=13) (n=13) (n=13) (n=13)

M SD M SD M SD M SD

Total 12,62 3,40 7,54 3,73 13,85 4,90 9,54 3,50

Diagnostic Criteria in DSM-5

A. Social communication and social interaction. No effect of gender is found (p

= .400), but a significant effect of diagnosis is found (p= .000*).

Table 19

Cross tabulation of diagnosis and DSM-5 A

DSM-5 A

Diagnosis

ASD No ASD

Criteria not met Count 7 23

% within DSM-5 A 23,3% 76,7%

Criteria met Count 19 3

% within DSM-5 A 86,4% 13,6%

When looked at diagnosed children only, no effect of gender is found (p = 1). When

looked at girls only, a significant effect of diagnosis is found (p = .000*).

39

Table 20

Cross tabulation of diagnosis and DSM-5 A in girls

DSM-5 A

Diagnosis

ASD No ASD


% within DSM-5 A 23,5% 76,5%


% within DSM-5 A 100,0% 0,0%

When looked at boys only, a significant effect of diagnosis is found (p = .017*).

Table 21

Cross tabulation of diagnosis and DSM-5 A in boys

DSM-5 A

Diagnosis

ASD No ASD


% within DSM-5 A 23,1% 76,9%


% within DSM-5 A 76,9% 23,1%

B. Restricted, repetitive patterns of behaviour, interests or activities. No effect of

gender is found (p = .579), but a significant effect of diagnosis is found (p= .000*).

40

Table 22

Cross tabulation of diagnosis and DSM-5 B

DSM-5 B

Diagnosis

ASD No ASD


% within DSM-5 B 16,0% 84,0%


% within DSM-5 B 81,5% 18,5%

When looked at diagnosed children only, no effect of gender (p = .096). When looked at

girls only, a significant effect of diagnosis is found (p = .047*).

Table 23

Cross tabulation of diagnosis and DSM-5 B in girls

DSM-5 B

Diagnosis

ASD No ASD


% within DSM-5 B 28,6% 71,4%


% within DSM-5 B 75,0% 25,0%


41

Table 24

Cross tabulation of diagnosis and DSM-5 B in boys

DSM-5 B

Diagnosis

ASD No ASD


% within DSM-5 B 0,0% 100,0%


% within DSM-5 B 86,7% 13,3%

Similarly, for A and B together, no effect of gender (p = .368), but a significant effect of

diagnosis is found (p= .000*).

Table 25

Cross tabulation of diagnosis and DSM-5 A+B

DSM-5 A+B

Diagnosis

ASD No ASD


% within DSM-5 A+B 27,8% 72,2%


% within DSM-5 A+B 100,0% 0,0%

When looked at diagnosed children only, no effect of gender is found (p = .226). When

looked at girls only, a significant effect of diagnosis is found (p = .015*).

42

Table 26

Cross tabulation of diagnosis and DSM-5 A+B in girls

DSM-5 A+B

Diagnosis

ASD No ASD


% within DSM-5 A+B 35,0% 65,0%


% within DSM-5 A+B 100,0% 0,0%


Table 27

Cross tabulation of diagnosis and DSM-5 A+B in boys

DSM-5 A+B

Diagnosis

ASD No ASD


% within DSM-5 A+B 18,8% 81,3%


% within DSM-5 A+B 100,0% 0,0%

Discussion

The aim of this study was to explore the role of gender on the evaluation and diagnosis

of ASD in young girls and boys and in particular, to gain insight in factors that might

differentially impact whether girls or boys meet diagnostic criteria for ASD.

The results are discussed, in order to answer the formulated research questions.

The first research question addresses cognitive ability: Is there a difference in cognitive

ability (VIQ and PIQ) between girls and boys/between diagnosed and not diagnosed with

43

ASD/between girls and boys diagnosed with ASD? No significant effects of gender or

diagnosis are found in relation to VIQ and PIQ. It has to be taken into account of course

that participants are matched on TIQ.

The second research question addresses ADOS scores: Is there a difference in ADOS

(severity score, cut-off, algorithm items, social communication and social interaction and

restricted repetitive behaviour) between girls and boys/between diagnosed and not

diagnosed with ASD/between girls and boys diagnosed with ASD? Firstly, a significant

difference on the ADOS severity score between children who are diagnosed with ASD and

children who are not diagnosed with ASD is found. The ADOS is often described as the

“gold standard” (Molloy, et al., 2011; Falkmer, et al., 2013) for assessing individuals with

suspected ASD and in this study it can be concluded that the evaluation of an ASD

diagnosis depends, to a large extent, on the score on ADOS.

Furthermore, a significant effect of the ADOS cut-off on diagnosis of ASD was found.

23 of the 26 participants, diagnosed with ASD, had a score on or above the cut-off for

Autism Spectrum Disorder on the ADOS. Only 12 of the 26 participants, who did not

receive an ASD diagnosis, had a score on or above the cut-off. Once more, the significance

of the ADOS in the diagnostic process of ASD is illustrated. No interaction-effect of

diagnosis x gender is found, so this means the diagnostic evaluation of ASD, in regard to

the ADOS, is similar for girls and boys. This is in accordance with Carter, et al. (2007) and

Holtman, et al. (2007) who did not find any gender differences on the ADOS.

When looked into the ADOS algorithm items in particular, children who have received

an ASD diagnosis show significant more problems in the quality of social overtures. Next,

boys show more problems in reciprocal social communication. This can be explained by the

hypothesis that girls are better at camouflaging their impairments in social interaction

(Hiller, et al., 2014).

For the combined item ‘ADOS Restricted Repetitive Behaviour’ a significant effect of

diagnosis is found. When children show persistent deficits in this area, the decision for an

ASD diagnosis is clear. There is no difference between girls or boys in this domain, which

is not in line with the results in Hartley and Sikora (2008) indicating that boys have higher

scores for RRB in comparison to girls.

The third research question addresses language ability: Is there a difference in

language ability (receptive and expressive language) between girls and boys/between

44

diagnosed and not diagnosed with ASD/between girls and boys diagnosed with ASD? No

effects of gender or diagnosis are found in this study.

The fourth research question is about the 19 thematic items: Is there a difference in the

thematic items, present in the descriptive reports between girls and boys/between

diagnosed and not diagnosed with ASD/between girls and boys diagnosed with ASD?

For all 19 thematic items, a first significant effect of diagnosis on ‘speech’ is found.

When looked at the qualitative information, this reason for this deficit in speech was

namely a Dutch accent. This can be explained by the idea that lots of children watch

cartoons and programmes on Dutch television channels and imitate this accent. Also for

‘stereotyped language’, a significant effect of diagnosis is found. For ‘sameness’ a

significant effect of gender is found. Boys face more problems when it comes to flexibility

in routines and activities. However, when looked at diagnosed children only, this effect of

gender is not significant anymore (p = .096). So girls and boys with ASD are equally

impaired in sameness.

A significant effect of diagnosis on the total score on 17 themes is found as well.

Logically, the combination of more items can be of meaning when looking at the difference

between children with ASD diagnosis and without ASD diagnosis.

The main tendency towards gender differences is also explored. It is often stated that

girls, in comparison to boys, show equal problems in social interaction and communication,

but less problems in restricted, repetitive patterns of behaviour, interests or activities. This

matter is examined based on the fulfilment of DSM-5 diagnostic criteria.

As expected, a significant effect of diagnosis is found for the current DSM-5 diagnostic

criteria. No gender differences are found, not for ‘social communication and social

interaction’, neither for ‘restricted, repetitive patterns of behaviour, interests or activities’.

When looked at diagnosed children only, again no significant effect of gender is found. Yet,

4 of the 13 girls diagnosed with ASD do not meet all diagnostic criteria for ‘social

communication and social interaction’. Similar for ‘RRB’; 4 of the 13 girls, diagnosed with

ASD do not meet the diagnostic criteria for RRB. They meet no or only 1 of the RRB

criteria. Whereas all 13 boys, diagnosed with ASD do meet the criteria (see Table 8). This

means the girls are diagnosed with ASD although they don’t meet all criteria for an ASD

diagnosis. This results in overdiagnosis.

It can be said that some uncertainties in current practice, in regard to diagnosing girls

45

with ASD, exist to date. Half of the girls, who were diagnosed with ASD, did not meet the

current diagnostic criteria for ASD. Of course, this is the strict application of criterion A

and B as described in the DSM-5. In addition, when girls do not meet the RRB criteria, this

does not necessarily mean that girls with ASD do not have impairments in this domain, but

instead that symptoms may not be as clinically identifiable. Furthermore, as Charman and

Baird (2002) stated, it is important to be careful with the strict application of DSM

diagnostic criteria, because an expert clinical view has shown to be more accurate. In this

study, all participants are diagnosed in a centre, specialised in the diagnostic process of

ASD.

Possible explanations for these uncertainties are put forward. Firstly, the main gender

difference that is often presented is about girls with ASD who have similar problems with

social interaction, but less problems with restricted, repetitive behaviours. Therefore, it is

possible that, when girls show persistent and severe deficits and impairment in social

interaction, but only meet 1 out of 4 RRB criteria, the diagnosis of ASD is eventually

decided on.

This discrepancy can also be understood as a result of the transition from DSM-IV

criteria to DSM-5 criteria. The English edition of the DSM-5 was released in May 2013.

The translated Dutch version was published in 2014. In this study, some participants had

been diagnosed in 2013, against DSM-IV criteria. Furthermore, not all protocols,

instruments… are directly replaced since the coming of the DSM-5 criteria. Logically,

a certain approach endures in some way.

Some changes from DSM-IV to DSM-5 have been made, such as the umbrella term

‘Autism spectrum disorder’ and only two domains instead of three domains. Furthermore,

for the three domains in DSM-IV, other minimum criteria were described: A. Qualitative

impairment in social interaction, manifested by at least two; B.Qualitative impairments in

communication, manifested by at least one; C. Restricted, repetitive, and stereotyped

patterns of behaviour, interests, and activities, manifested by at least one (APA, 1994).

This can also explain why girls are ‘overdiagnosed’ in this study, in particular on the RRB

criteria.

46

In what follows, limitations, suggestions for further research and implications for

practice are noted.

Limitations

These findings should be interpreted in the context of a number of limitations. First, the

sample cannot be considered representative of the general population of children with ASD.

Most participants are from one region in Belgium, namely Flanders.

Second, the tests and observations, that are part of the diagnostic process, were not

carried out by one and the same psychologist, child psychiatrist or speech and language

therapist for all participants. All of them are professionals, specialised in the diagnostic

process of ASD, yet some personal or subjective bias may possibly be included in the

diagnostic process.

Next, the children in this study were already referred to the diagnostic centre with a

suspicion of ASD. This could possibly mean it was more likely to name a diagnosis. In

other words, these children all showed some typical characteristics of ASD, and thus the

group of ‘no ASD’ cannot be seen as typically developing children. Some of these children

who did not receive the diagnosis of Autism Spectrum Disorder, did however receive a

diagnosis of Anxiety Disorder or Multiple-Complex Developmental Disorder.

Another limitation encompasses some missing values such as no severity score on

ADOS or no available information from any language assessment.

Next, the scoring of the themes present in the descriptive reports cannot be seen as facts.

Some caution in interpreting these is advisable, because these scores are decided on

information from parents, teachers and professionals. Also the testing environment versus

natural setting plays a role. Furthermore, when the evaluation of an item was ‘not known’

or ‘not given’, this was scored as code 0 ‘no problem’. It is possible that the item could not

be observed during testing, for example relationships with peers, and parents did not

mention it, although it may be challenging for the child.

Lastly, due to statistical issues such as cell counts in chi-square analysis, the researcher

opted for only 2x2 Fisher’s Exact tests. This way the categories were converted from 3 to 2

categories, and thus subtle differences between score 0, 1 and 2 disappeared. However,

because of the small amount of codes 2, the information was not that rich. It can be

interesting though, when analysed in qualitative way (in further research), to look for

problems that are always present or that are varying in presence or more subtle.

47

Suggestions for Further Research

Further research can focus on the comparison of both genders with ASD, because

research in which girls and boys with ASD are compared is scarce. Replication of this study

with a greater sample can be of added value for further elaboration and can provide more

insight into potential gender differences. Furthermore, the distinction between typically

developing children and children with ASD can be essential to decide on what behaviours,

traits or symptoms are decisive to speak of normal functioning or impairment in

functioning and thus disorder.

Next to this, the participants in this study had already finished the whole diagnostic

process and for this reason, it was not possible to compare them at the moment itself. All

comparisons were done afterwards, on the basis of test results and document analysis of the

descriptive reports. Therefore, research in which the diagnostic process is included as part

of the data collection, can be more explicit with regard to the scoring of items in the

descriptive reports.

Furthermore, more investigation is needed to investigate if gender specific criteria for

ASD are required. Namely, it should be examined which criteria are most likely to have an

impact on the evaluation of ASD for girls, apart from boys. Further research is necessary to

identify what current criteria can still be of use, what current criteria can be adjusted for

girls or what new criteria can be added, which can help to overcome the uncertainties in

diagnosing girls with ASD. Because the following can be questioned: Do females present

an altered phenotype that is more difficult to diagnose? Or do current diagnostic

instruments not adequately capture this phenotype?

For instance, since the revision of the DSM, a new criterion for ASD was included:

hypo- and hypersensitivity. Although no effect of gender was found, some girls face major

problems for ‘sensory aspects’ (and were given a code ‘2’), which severely effect their

functioning. Particularly, sounds, scents, lightning and clothing, but food as well. More

investigation into this criterion can perhaps outline a new version of criteria for girls.

Another suggestion for future research is related to social interaction. As mentioned

before, social cognition forms the basis for adjusted social behaviour (Duijkers, et al.,

2014). The ability to navigate social interactions appears to require high levels of social

cognition. In this study, most children have been tested on the self-developed social

48

cognition test (see Measures). For multiple reasons, no data-analysis for the social

cognition test was carried out, but when browsing through the reports, it becomes clear that

a lot of children have difficulties with perspective taking, interpretation of feelings, …

Therefore it can be interesting to undertake more research on social cognition, as an

explanatory model. Suggestions for new assessments or criteria can be based on this.

Implications for Practice

To conclude with, challenges and uncertainties related to ASD in girls exist to date, even

in specialised clinical practice. As clinical practice depends on broadly excepted diagnostic

criteria, such as DSM criteria (APA) or ICD criteria (WHO), these uncertainties will

remain as long as there are no gender-specific criteria for ASD. Therefore, the fundamental

basis for a diagnosis should be whether this is in favour of the well-being and Quality of

Life of the child. A diagnosis is often a gateway for specialised treatment and intervention.

ASD cannot be cured, but life prognosis and quality of life can be improved by this

specialised care, if they meet existing needs. In my opinion, as a Master of Science in

Special Education, Disability studies and Behavioural disorders, a world that is ruled by

thinking in diagnoses, labels and disorders is not a desirable world. It is important to

identify girls in need of support, but a careful approach is also needed to not pathologize

those who are managing, even if they have high-level autistic traits. I would like to end

with some questions for reflection: In this study, all participants show some characteristics

of ASD, yet not all of them got a diagnosis. Why or when is the decision for a diagnosis

ought to be necessary? When do we decide that a girl or boy cannot manage, and thus needs

this diagnosis?

Conclusion

The present study has shed some light onto current practice in the evaluation of ASD. In

particular, the results demonstrated that girls and boys are evaluated similarly. No

significant gender differences between girls and boys with ASD were found. Furthermore,

uncertainties are present in evaluation of ASD in girls, because a discrepancy was

discovered between the DSM-5 diagnostic criteria and the decision for ASD. In this regard,

the decision on diagnosis for girls can be challenging. Sometimes girls show as much or

more impairments in social interaction, which eventually pleads for an ASD diagnosis,

49

although they do not show a lot of deficits in restricted repetitive behaviours. The opposite

occurs as well, whereas for boys this presentation of impairments is more obvious. To

conclude with, further research into ASD gender differences is needed to answer if gender

differences in ASD exist, and if so, what the differences are.

Acknowledgements

The author wishes to thank Prof. Dr. Herbert Roeyers for his useful guidance during the

process of writing this report. Next, the author wishes to thank the mentor from the

diagnostic centre for her guidance through the electronic patient database, the insightful

comments during data collection and the offer and possibility to do research in the

diagnostic centre.

50

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Appendix A Coding scheme

Theme Colour/Symbol

Eye contact _______________*

Body language (facial expression, gestures) _______________

Speech (intonation, rhythm) _______________

Stereotyped language _______________

Relationships with peers _______________

Reciprocity _______________

Social acceptable behaviour _______________

Emotion regulation _______________

Fantasy play _______________

Play with others _______________

Stereotyped behaviour _______________

Stereotyped body movement _______________

Sameness (routines, patterns) _______________

Preoccupation _______________

Sensory aspects _______________ (pain, sounds, light, textures, smelling, touching, food)

Behavioural problems n

Impairment in functioning ★

Early development (<3 years) �

Familial occurrence (siblings/parents vs. family) p

59

Appendix B

Table 28

Cross tabulation of gender and ADOS cut-off

ADOS cut-off

Gender

Girl Boy

Below Count 9 5


Above Count 16 19


Table 29

Cross tabulation of gender and ADOS algorithm topic (A)

ADOS algorithm topic (A)

Gender

Girl Boy


% within ADOS (A) 60,6% 39,4%


% within ADOS (A) 31,3% 68,8%

Table 30

Cross tabulation of diagnosis and ADOS algorithm topic (A)

ADOS algorithm topic (A)

Diagnosis

ASD No ASD


% within ADOS (A) 48,5% 51,5%


% within ADOS (A) 62,5% 37,5%

60

Table 31

Cross tabulation of gender and ADOS algorithm topic (B)

ADOS algorithm topic (B)

Gender

Girl Boy


% within ADOS (B) 56,3% 43,8%


% within ADOS (B) 48,5% 51,5%

Table 32

Cross tabulation of diagnosis and ADOS algorithm topic (C)

ADOS algorithm topic (C)

Diagnosis

ASD No ASD


% within ADOS (C) 35,7% 64,3%


% within ADOS (C) 60,0% 40,0%

Table 33

Cross tabulation of gender and ADOS algorithm topic (D)

ADOS algorithm topic (D)

Gender

Girl Boy


% within ADOS (D) 83,3% 16,7%


% within ADOS (D) 46,5% 53,5%

61

Table 34

Cross tabulation of diagnosis and ADOS algorithm topic (D)

ADOS algorithm topic (D)

Diagnosis

ASD No ASD


% within ADOS (D) 33,3% 66,7%


% within ADOS (D) 55,8% 44,2%

Table 35

Cross tabulation of gender and ADOS algorithm topic (E)

ADOS algorithm topic (E)

Gender

Girl Boy


% within ADOS (E) 50,0% 50,0%


% within ADOS (E) 52,2% 47,8%

Table 36

Cross tabulation of diagnosis and ADOS algorithm topic (E)

ADOS algorithm topic (E)

Diagnosis

ASD No ASD


% within ADOS (E) 42,3% 57,7%


% within ADOS (E) 65,2% 34,8%

62

Table 37

Cross tabulation of gender and ADOS algorithm topic (F)

ADOS algorithm topic (F)

Gender

Girl Boy


% within ADOS (F) 55,0% 45,0%


% within ADOS (F) 33,3% 66,7%

Table 38

Cross tabulation of diagnosis and ADOS algorithm topic (F)

ADOS algorithm topic (F)

Diagnosis

ASD No ASD


% within ADOS (F) 47,5% 52,5%


% within ADOS (F) 77,8% 22,2%

Table 39

Cross tabulation of gender and ADOS algorithm topic (G)

ADOS algorithm topic (G)

Gender

Girl Boy


% within ADOS (G) 51,2% 48,8%


% within ADOS (G) 50,0% 50,0%

63

Table 40

Cross tabulation of diagnosis and ADOS algorithm topic (G)

ADOS algorithm topic (G)

Diagnosis

ASD No ASD


% within ADOS (G) 51,2% 48,8%


% within ADOS (G) 62,5% 37,5%

Table 41

Cross tabulation of gender and ADOS algorithm topic (H)

ADOS algorithm topic (H)

Gender

Girl Boy


% within ADOS (H) 52,8% 47,2%


% within ADOS (H) 46,2% 53,8%

Table 42

Cross tabulation of diagnosis and ADOS algorithm topic (H)

ADOS algorithm topic (H)

Diagnosis

ASD No ASD


% within ADOS (H) 44,4% 55,6%


% within ADOS (H) 76,9% 23,1%

64

Table 43

Cross tabulation of gender and receptive language

Receptive language

Gender

Girl Boy

Below average Count 6 10

% within receptive language 37,5% 62,5%

Average Count 16 12


Table 44

Cross tabulation of diagnosis and receptive language

Receptive language

Diagnosis

ASD No ASD



Average Count 12 16


Table 45

Cross tabulation of gender and expressive language

Expressive language

Gender

Girl Boy


% within expressive language 50,0% 50,0%

Average Count 18 17


65

Table 46

Cross tabulation of diagnosis and expressive language

Expressive language

Diagnosis

ASD No ASD



Average Count 17 18


Table 47

Cross tabulation of gender and eye contact

Eye contact

Gender

Girl Boy


% within eye contact 61,5% 38,5%



Table 48

Cross tabulation of diagnosis and eye contact

Eye contact

Diagnosis

ASD No ASD





66

Table 49

Cross tabulation of gender and body language

Body language

Gender

Girl Boy


% within body language 55,0% 45,0%



Table 50

Cross tabulation of diagnosis and body language

Body language

Diagnosis

ASD No ASD





Table 51

Cross tabulation of gender and speech

Speech

Gender

Girl Boy





67

Table 52

Cross tabulation of gender and stereotyped language

Stereotyped language

Gender

Girl Boy





Table 53

Cross tabulation of gender and relationships with peers

Relationships with peers

Gender

Girl Boy


% within relationships with

peers

62,5% 37,5%


% within relationships with

peers

44,4% 55,6%

Table 54

Cross tabulation of diagnosis and relationships with peers

Relationships with peers

Diagnosis

ASD No ASD


% within relationships 37,5% 62,5%


% within relationships 55,6% 44,4%

68

Table 55

Cross tabulation of gender and reciprocity

Reciprocity

Gender

Girl Boy


% within reciprocity 60,0% 40,0%



Table 56

Cross tabulation of diagnosis and reciprocity

Reciprocity

Diagnosis

ASD No ASD





Table 57

Cross tabulation of gender and social acceptable behaviour

Social acceptable behaviour

Gender

Girl Boy


% within social acceptable

behaviour

51,5% 48,5%



behaviour

47,4% 52,6%

69

Table 58

Cross tabulation of diagnosis and social acceptable behaviour

Social acceptable behaviour

Diagnosis

ASD No ASD



behaviour

45,5% 54,5%



behaviour

57,9% 42,1%

Table 59

Cross tabulation of gender and emotion regulation

Emotion regulation

Gender

Girl Boy


% within emotion regulation 44,4% 55,6%



Table 60

Cross tabulation of diagnosis and emotion regulation

Emotion regulation

Diagnosis

ASD No ASD





70

Table 61

Cross tabulation of gender and fantasy play

Fantasy play

Gender

Girl Boy


% within fantasy play 58,3% 41,7%



Table 62

Cross tabulation of diagnosis and fantasy play

Fantasy play

Diagnosis

ASD No ASD





Table 63

Cross tabulation of gender and play with others

Play with others

Gender

Girl Boy


% within play with others 68,4% 31,6%



71

Table 64

Cross tabulation of diagnosis and play with others

Play with others

Diagnosis

ASD No ASD





Table 65

Cross tabulation of gender and stereotyped behaviour

Stereotyped behaviour

Gender

Girl Boy


% within stereotyped behaviour 47,6% 52,4%



Table 66

Cross tabulation of diagnosis and stereotyped behaviour

Stereotyped behaviour

Diagnosis

ASD No ASD





72

Table 67

Cross tabulation of gender and stereotyped body movement

Stereotyped body movement

Gender

Girl Boy


% within stereotyped body

movement

47,6% 52,4%



movement

60,0% 40,0%

Table 68

Cross tabulation of diagnosis and stereotyped body movement

Stereotyped body movement

Diagnosis

ASD No ASD



movement

47,6% 52,4%



movement

60,0% 40,0%

73

Table 69

Cross tabulation of gender and preoccupation

Preoccupation

Gender

Girl Boy


% within preoccupation 55,3% 44,7%



Table 70

Cross tabulation of diagnosis and preoccupation

Preoccupation

Diagnosis

ASD No ASD





Table 71

Cross tabulation of diagnosis and sameness

Sameness

Diagnosis

ASD No ASD





74

Table 72

Cross tabulation of gender and sensory aspect

Sensory aspect

Gender

Girl Boy


% within sensory aspect 52,6% 47,4%



Table 73

Cross tabulation of diagnosis and sensory aspect

Sensory aspect

Diagnosis

ASD No ASD





Table 74

Cross tabulation of gender and behavioural problems

Behavioural problems

Gender

Girl Boy


% within behavioural problems 51,7% 48,3%



75

Table 75

Cross tabulation of diagnosis and behavioural problems

Behavioural problems

Diagnosis

ASD No ASD





Table 76

Cross tabulation of gender and impairment functioning

Impairment functioning

Gender

Girl Boy


% within impairment

functioning

57,9% 42,1%


% within impairment

functioning

45,5% 54,5%

76

Table 77

Cross tabulation of diagnosis and impairment functioning

Impairment functioning

Diagnosis

ASD No ASD


% within impairment

functioning

31,6% 68,4%


% within impairment

functioning

60,6% 39,4%

Table 78

Cross tabulation of gender and early development

Early development

Gender

Girl Boy


% within early development 59,1% 40,9%



Table 79

Cross tabulation of diagnosis and early development

Early development

Diagnosis

ASD No ASD





77

Table 80

Cross tabulation of gender and familial occurrence

Familial occurrence

Gender

Girl Boy

No Count 13 20

% within familial occurrence 39,4% 60,6%

Yes Count 13 6


Table 81

Cross tabulation of diagnosis and familial occurrence

Familial occurrence

Diagnosis

ASD No ASD

No Count 18 15


Yes Count 8 11


Table 82

Cross tabulation of gender and DSM-5 A

DSM-5 A

Gender

Girl Boy


% within DSM-5 A 56,7% 43,3%


% within DSM-5 A 40,9% 59,1%

78

Table 83

Cross tabulation of gender and DSM-5 A in diagnosed children

DSM-5 A

Gender

Girl Boy


% within DSM-5 A 57,1% 42,9%


% within DSM-5 A 47,4% 52,6%

Table 84

Cross tabulation of gender and DSM-5 B

DSM-5 B

Gender

Girl Boy


% within DSM-5 B 56,0% 44,0%


% within DSM-5 B 44,4% 55,6%

Table 85

Cross tabulation of gender and DSM-5 B in diagnosed children

DSM-5 B

Gender

Girl Boy


% within DSM-5 B 100,0% 0,0%


% within DSM-5 B 40,9% 59,1%

79

Table 86

Cross tabulation of gender and DSM-5 A+B

DSM-5 A+B

Gender

Girl Boy


% within DSM-5 A+B 55,6% 44,4%


% within DSM-5 A+B 37,5% 62,5%

Table 87

Cross tabulation of gender and DSM-5 A+B in diagnosed children

DSM-5 A+B

Gender

Girl Boy


% within DSM-5 A+B 70,0% 30,0%


% within DSM-5 A+B 37,5% 62,5%

does gender influence the evaluation and diagnosis …€¦ · 3 al., 2014). the few studies, in...

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