High-functioning children with autism were compared with two control groups on measures of anxiety and social worries. Comparison control groups consisted of children with specific language impairment (SLI) and normally developing children. Each group consisted of 15 children between the ages of 8 and 12 years and were matched for age and gender. Children with autism were found to be most anxious on both measures. High anxiety subscale scores for the autism group were separation anxiety and obsessive-compulsive disorder. These findings are discussed within the context of theories of autism and anxiety in the general population of children. Suggestions for future research are made.

Clinical reports suggest that anxiety is a pertinent issue for adults with autism. We compared 34 adults with autism with 20 adults with intellectual disabilities, utilizing informant-based measures of anxiety and stress. Groups were matched by age, gender and intellectual ability. Adults with autism were almost three times more anxious than the comparison group and gained significantly higher scores on the anxiety subscales of panic and agoraphobia, separation anxiety, obsessive-compulsive disorder and generalized anxiety disorder. In terms of sources of stress, significant differences between the two groups were also found, and stress was found to correlate with high anxiety levels for the autism group, particularly the ability to cope with change, anticipation, sensory stimuli and unpleasant events. That is, the more anxious the individual with autism, the less likely they were able to cope with these demands. This has important implications for clinicians in terms of both assessment and treatment.

Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) are neurodevelopmental conditions which impact on a significant number of children and adults. Currently, the diagnosis of such disorders is done by experts who employ standard questionnaires and look for certain behavioural markers through manual observation. Such methods for their diagnosis are not only subjective, difficult to repeat, and costly but also extremely time consuming. In this work, we present a novel methodology to aid diagnostic predictions about the presence/absence of ADHD and ASD by automatic visual analysis of a persons behaviour. To do so, we conduct the questionnaires in a computer-mediated way while recording participants with modern RGBD (Colour+Depth) sensors. In contrast to previous automatic approaches which have focussed only detecting certain behavioural markers, our approach provides a fully automatic end-to-end system for directly predicting ADHD and ASD in adults. Using state of the art facial expression analysis based on Dynamic Deep Learning and 3D analysis of behaviour, we attain classification rates of 96% for Controls vs Condition (ADHD/ASD) group and 94% for Comorbid (ADHD+ASD) vs ASD only group. We show that our system is a potentially useful time saving contribution to the diagnostic field of ADHD and ASD.

There is a clinical need for objective evidence-based measures that are sensitive and specific to ADHD when compared with other neurodevelopmental disorders. This study evaluated the incremental validity of adding an objective measure of activity and computerised cognitive assessment to clinical rating scales to differentiate adult ADHD from Autism spectrum disorders (ASD).Adults with ADHD (n=33) or ASD (n=25) performed the QbTest, comprising a Continuous Performance Test with motion-tracker to record physical activity. QbTest parameters measuring inattention, impulsivity and hyperactivity were combined to provide a summary score ('QbTotal'). Binary stepwise logistic regression measured the probability of assignment to the ADHD or ASD group based on scores on the Conners Adult ADHD Rating Scalesubscale E (CAARS-E) and Autism Quotient (AQ10) in the first step and then QbTotal added in the second step. The model fit was significant at step 1 (CAARS-E, AQ10) with good group classification accuracy. These predictors were retained and QbTotal was added, resulting in a significant improvement in model fit and group classification accuracy. All predictors were significant. ROC curves indicated superior specificity of QbTotal. The findings present preliminary evidence that adding QbTest to clinical rating scales may improve the differentiation of ADHD and ASD in adults.

Whilst evidence of theory of mind impairments in children with autism is well established, possible impairments in children with language disorder have only recently been investigated. Children with specific language impairment aged between eight and 12 years were matched by age and gender to high functioning children with autism and normally developing peers. The theory of mind abilities of the groups were compared using the strange stories task. Both the children with specific language impairment and the children with autism gave fewer correct mental state answers than normally developing children, but whereas the children with autism gave more inappropriate mental state answers than the children who were developing normally, the children who were developing normally and the children with language disorders did not differ in this respect. These findings are discussed within the context of theory of mind issues in autism and the classification of language disorders.