Sex differences in predictors and outcomes of camouflaging: Comparing diagnosed autistic, high autistic trait and low autistic trait young adults

LAY ABSTRACT: Many autistic people use strategies that help them adapt in social situations and hide behaviours that may seem different to non-autistic individuals - this is called camouflaging. Camouflaging may help autistic people fit in socially; however, it might also lead to poorer well-being. It has been suggested that autistic females camouflage more than autistic males. This article explored differences between males and females who have an autism diagnosis, have characteristics of autism but no diagnosis and those with few autistic characteristics. It is important to include these groups as camouflaging may make it more difficult to get an autism diagnosis and therefore make it less likely a person will receive support. We found that autistic women camouflaged more than all other groups. The group with few autistic characteristics (males and females) camouflaged the least. Loneliness was found to be a possible reason for camouflaging for the diagnosed autistic group only. In terms of outcomes related to camouflaging, it was found that those who camouflaged most had a lower quality of life; this was true of all groups. This tells us that there may be different reasons to camouflage, and different outcomes related to camouflaging for those with many characteristics of autism (including those with a diagnosis), and those with few. It is important that clinicians, teachers, parents and other stakeholders are aware of the negative outcomes associated with camouflaging so that more support can be provided for those who need it

A comparison of self-report and discrepancy measures of camouflaging: Exploring sex differences in diagnosed autistic versus high autistic trait young adults

Camouflaging describes masking or compensating for autistic traits and/or related difficulties. Some evidence suggests autistic females camouflage more than autistic males, potentially contributing to delayed or missed diagnosis. Studies predominantly adopt self-report measures of camouflaging, potentially reflecting a person's intent to camouflage without accurately measuring effectiveness (i.e., success in fulfilling the intended effect of minimizing the appearance of autistic traits) of camouflaging. Discrepancy scores between underlying cognitive difficulties (e.g., theory of mind) and observed autistic traits (henceforth camoToM ), or between self-reported autistic traits and observed autistic traits (henceforth camoSRS ), may provide a more accurate measure of camouflaging effectiveness. Three measures of camouflaging administered to autistic males (n = 46) and females (n = 40), and adults with equally high levels of autistic traits but no diagnosis (n = 45 males, n = 43 females) recruited from a large population-based sample were compared. Self-report measures of camouflaging were significantly correlated with camoSRS scores only. Both discrepancy scores were correlated with each other. Adults with high autistic traits, but no diagnosis, had higher discrepancy camouflaging scores than diagnosed adults, but self-reported scores were similar. Diagnosed females scored higher than diagnosed males across all camouflaging measures, but no sex difference occurred in the high trait group. This might indicate that autistic females have higher intentions and greater effectiveness when camouflaging, compared with autistic males. For camoSRS only, high trait males scored significantly higher than diagnosed males; no group difference occurred for females. These results suggest that, despite all participants intending to camouflage to some extent, effective camouflaging as measured by discrepancy scores is higher in undiagnosed high autistic trait individuals. One interpretation is that effective camouflaging reduces the likelihood of autism diagnosis in males and females with high autistic traits

Good social skills despite poor theory of mind: Exploring compensation in autism spectrum disorder

Background It is proposed that some individuals with Autism Spectrum Disorder (ASD) can ‘compensate’ for their underlying difficulties (e.g. in theory of mind; ToM), thus demonstrating relatively few behavioural symptoms, despite continued core cognitive deficits. The mechanisms underpinning compensation are largely unexplored, as is its potential impact on mental health. This study aimed to estimate compensation patterns in ASD, by contrasting overt social behaviour with ToM task performance, in order to compare the characteristics of ‘Low’ and ‘High’ Compensators. Methods A total of 136 autistic adolescents, from the ongoing Social Relationships Study, completed a range of cognitive tasks, the Autistic Diagnostic Observation Schedule (ADOS) and a self‐report anxiety questionnaire. Participants were assigned compensation group status; High Compensators demonstrated good ADOS scores despite poor ToM performance, while Low Compensators demonstrated similarly poor ToM, accompanied by poor ADOS scores. Results High Compensators demonstrated better IQ and executive function (EF), but greater self‐reported anxiety, compared with Low Compensators. Such differences were not found when comparing individuals who had good versus poor ADOS scores, when ToM performance was good. Other core autistic characteristics (weak central coherence, nonsocial symptoms) did not differentiate the High and Low Compensators. Conclusions IQ, EF and anxiety appear to be implicated in the processes by which certain autistic young people can compensate for their underlying ToM difficulties. This tendency to compensate does not appear to reflect the severity of ‘hit’ for ASD per se, suggesting that well‐compensated individuals are not experiencing a milder form of ASD. The construct of compensation in ASD has implications for research and clinical practice

Statement: Industrial development at Whyalla

A randomly selected sample of 165 children from Romania (of whom 144 had been reared in institutions) who were adopted by UK families, with placement before the age of 42 months, was studied at 4, 6, and 11 years of age. Comparisons were made with a sample of 52 non-institutionalized UK children adopted before the age of 6 months, who were studied in the same way. The paper briefly summarizes circumstances at the time of adoption and then reports findings at age 11, focusing on changes between 6 and 11. Marked catch-up in psychological functioning was evident following adoption, but significant problems continued in a substantial minority of the children placed after the age of 6 months. The theoretical implications of the findings are considered, and the policy implications are noted

A novel guide for assessing Non-Traditional Autism Presentations: piloting the N-TAP

Subtler and non-traditional presentations of autism have been found to contribute to delayed, mis- and missed diagnosis. Late diagnosis can have significant impact on an individual's well-being and access to support. There is currently no clear guide for clinicians to use to identify such subtler or non-traditional presentations of autism during the diagnostic process. This paper describes the development and initial piloting of the Non-Traditional Autism Presentation guide (N-TAP). The items in the N-TAP were derived from current evidence and clinician experience and they include both non-verbal and verbal differences such as nonconventional use of gesture and facial expression and sameness in description of emotions. The N-TAP was applied to videos of a current “gold standard” autism assessment (n=40). The N-TAP was found to be user-friendly and have good inter-rater reliability. Future research is needed to determine the psychometric properties of this tool. However, the authors put forward the N-TAP as a useful clinician guide to facilitate timely autism diagnosis for all

Cognitive phenotypes in typical development and Autism Spectrum Disorder

Objective: To investigate if different cognitive subtypes occur within typical development and Autism Spectrum Disorder (ASD). Cognitive atypicalities in central coherence (CC), executive function (EF) and theory of mind (ToM) are highly prevalent in ASD. These cognitive atypicalities could potentially be cognitive endophenotypes of ASD. Latent class analysis (LCA) was used to identify more homogenous cognitive subgroups in typical development and ASD based on cognitive task performance. 158 adolescents diagnosed with ASD, 71 of their unaffected co-twins, and 159 controls completed twelve cognitive tasks to assess cognitive domains of local processing, central coherence (CC), executive function (EF) and theory of mind (ToM). Performance on cognitive tasks was used to index if a participant had an atypicality in a cognitive domain, defined as atypical performance in at least one task in that cognitive domain. This index was used in 6 LCAs conducted separately for each participant group. The best LCA model had 4 subgroups for ASD, 3 subgroups for co-twins and 4 subgroups for the control group. For ASD; subgroup 1 had CC, EF, ToM atypicalities, subgroup 2 had CC atypicalities, subgroup 3 had no atypicalities, and subgroup 4 had multiple atypicalities. Few individuals had cognitive atypicalities in typical development. However, multiple cognitive atypicalities were highly prevalent in ASD. These cognitive subgroups may useful for informing diagnosis and treatment options

Genetic and environmental overlap between cognitive atypicalities and autism spectrum disorder

Purpose: To examine the heritability of cognitive atypicalities and the genetic and environmental overlap between cognitive atypicalities and ASD. Background: Cognitive atypicalities in central coherence (CC), executive function (EF) and theory of mind (ToM) are highly prevalent in ASD. These cognitive atypicalities could potentially be cognitive endophenotypes of ASD. However, there have been few twin studies into the heritability of these cognitive atypicalities, with no studies in ASD. Method: Joint continuous-ordinal liability threshold model fitting was used to estimate the genetic and environmental contributions of the (co)variance of the best-estimate diagnosis (no ASD, broad spectrum or ASD) and each separate cognitive factor (local processing, executive functioning, theory of mind, global processing) in a sample of 127 ASD twin pairs and 80 control twin pairs. Results: Global processing, EF and ToM were modestly associated with ASD. The local processing factor showed moderate genetic influence. All other cognitive factors showed low genetic influence. All cognitive factors showed substantial unique environmental influence. A modest shared genetic contribution between global processing and ASD. Conclusion: This was the first study to examine the genetic overlap between cognition and ASD. There appears to be distinct aetiological influences on cognitive atypicalities and ASD. These bivariate genetic findings have implications for the biological basis of cognitive atypicalities and ASD

Trying to make sense of a heterogeneous disorder: A factor mixture modelling approach to autism spectrum disorder

Background: Autism spectrum disorder (ASD) is behaviourally defined by the presence of social and communication impairments and restricted and repetitive behaviours. The clinical phenotype is characterised by considerable heterogeneity, with individuals presenting with severe impairments through to more subtle deficits. This heterogeneity is often considered as a hindrance in the study of the aetiology and genetics of ASD. Objectives: (1) To identify homogeneous subgroups within ASD using a Factor Mixture Modelling (FMM) approach. (2) To explore the similarities/differences of individuals assigned to each subgroup in terms of age, gender, diagnosis, and their symptom and cognitive profiles. Methods: Participants were drawn from a large population-based sample of adolescent twins. The sample consisted of 251 individuals (M=13.5, SD=0.68; 174 males). 137 participants had a diagnosis of ASD (M=13.51 years, SD=0.73; 118 males), 40 had a diagnosis of broad spectrum autism (M=13.40 years, SD=0.56; 30 males), and 72 were unaffected co-twins (M=13.49 years, SD=0.65; 26 males). All twin pairs were behaviourally assessed for ASD symptomatology using parent report (Autism Diagnostic Interview-Revised, ADI-R) and direct observation (Autism Diagnostic Observation Schedule-Generic, ADOS-G). All twin pairs were also administered an extensive cognitive battery to measure IQ, language ability, theory of mind ability, executive functioning, and central coherence. Analyses: FMM combines latent class analysis and confirmatory factor analysis to stratify individuals into relatively more homogeneous subgroups. Factor mixture models were tested using the raw subscale scores of the 37 items from the ADI-R. To guide the choice of the number of classes and factors for the FMMs, six latent class analyses (one-to-six classes) and three confirmatory factor analyses (one-to-three factors) were carried out. The fit of these models was assessed using goodness-of-fit criteria. Results: Overall, a ‘two-factor, five classes’ FMM was chosen as the best fit of the data. According to this final FMM, individuals could be classified into five relatively homogeneous classes (C1: 23%, C2: 18%, C3: 17%, C4: 29%, C5: 13%, of the sample). A two factor solution fitted the data best; one factor corresponding to social/communication deficits, and a second factor corresponding to restricted and repetitive behaviour impairments. Age did not differ across the five classes. There were a higher proportion of females in C1 and C2, with a higher proportion of males in C3, C4, and C5. The proportion of ASD diagnosis differed across the five classes, with C5 comprising only of ASD diagnoses. IQ also differed across classes. Individuals assigned to C1 had the lowest social and communication impairments, with few restricted and repetitive behaviours. The severity of ASD symptoms significantly increased through C3 to C5, with individuals assigned to C5 showing the most severe impairments. However, the cognitive profile across the five classes was similar. Conclusions: Five subgroups were identified using an FMM approach, which were largely based on symptom severity. Across the subgroups, individuals received different diagnoses, had a differing IQ profile, and a differing symptom profile. Age and cognitive profile was stable across subgroups. The findings also support the two symptom dimensions of ASD, as proposed in the DSM-5