New Hampshire commission on autism spectrum disorders, findings and recommendations

Report of the New Hampshire Commission on Autism Spectrum Disorders\u27 findings, as well as goals and recommendations to improve detection and treatment of autism disorders

Autism spectrum disorders

The earlier that children with an Autism Spectrum Disorder (ASD) receive referral, diagnosis and intervention, the better the long-term results are for those children and their families (Barbaro & Dissanyake, 2009; Wiggins et al., 2006; Mandell et al., 2005). Primary health care professionals, such as child and family health nurses and GPs, can listen to parent concerns and be alert to the signs of developmental delay in infancy and early childhood to facilitate early referral and diagnosis. Indeed, Barbaro & Dissanayake state that primary health care professionals, given their extensive knowledge and training on developmental milestones, are the best placed – and most expert – to observe young children’s development and to identify early signs of ASDs (2010, p. 377). ASD IN AUSTRALIA: AN OVERVIEW ASD is the term used to refer to three types of developmental disorder: Autism, Asperger’s Syndrome and Pervasive Developmental Disorder – Not Otherwise Specified (PDD-NOS). A diagnosis of one of the three indicates a developmental deficit of varying severity in the areas of: communication social skills and/or behaviour No two children with an ASD are the same, as they each have varying degrees of developmental deficit in the above three areas. This is why the term ‘spectrum’ is used when describing the disorder. In this article we will use the term ASD when referring to the all three of the disorders. Diagnoses of ASD have increased markedly since the 1990s. Prior to this, children were generally diagnosed with Global Developmental Delay or intellectual disability. Williams et al. (2008) found that: The current rate of prevalence in Australia is estimated at 1 in 160. Rates of diagnosis vary by state and territory due to differences in the way a diagnosis can be reached. Australian data show that about four boys are diagnosed with ASD for every one girl. The cause of ASD is not known, but is thought to be a combination of genetic and environmental factors. It is not caused by anything the family does or does not do. Despite the recognition that signs of ASD can appear in infancy, one study from America found that the average age of diagnosis is around three or four years old (Mandell et al., 2005). In specialist centres, diagnoses can be made for some children as early as 24 months, and rarely earlier. Significant research is being done to try and reduce the average age of diagnosis as this may lead to an earlier intervention. In turn, earlier intervention could help improve developmental outcomes for children and their families and lessen the long-term impact of an ASD for an individual child (Barbaro & Dissanyake, 2009)

Inter-rater reliability of treatment fidelity and therapeutic alliance measures for psychological therapies for anxiety in young people with autism spectrum disorders

Objectives: This article presents work undertaken to establish inter-rater reliability for a measure of treatment fidelity and a measure of therapeutic alliance for therapies for anxiety for young people with autism spectrum disorders. The discussion and decision-making processes behind achieving consensus of raters are rarely published. Margolin et al. (1998) have highlighted this issue and called for researchers to communicate the details of their observational and rating procedures. This article is a response to their call for greater transparency so that these methods are readily accessible for comparison with other studies. Methods: Participants were young people with autism spectrum disorders receiving treatment for anxiety, clinical staff treating these young people and the independent raters assessing the treatment sessions. We report: (i) the processes involved in establishing inter-rater reliability for two instruments, (ii) the results obtained with a sample of young people with autism spectrum disorders using these instruments. Results and conclusions: Results demonstrate that it was possible to attain satisfactory inter-rater reliability with each of these two instruments with a client group with autism spectrum disorders, even though the instruments were originally designed for typically-developing populations

Inter-rater reliability of treatment fidelity and therapeutic alliance measures for psychological therapies for anxiety in young people with autism spectrum disorders

Objectives: This article presents work undertaken to establish inter-rater reliability for a measure of treatment fidelity and a measure of therapeutic alliance for therapies for anxiety for young people with autism spectrum disorders. The discussion and decision-making processes behind achieving consensus of raters are rarely published. Margolin et al. (1998) have highlighted this issue and called for researchers to communicate the details of their observational and rating procedures. This article is a response to their call for greater transparency so that these methods are readily accessible for comparison with other studies. Methods: Participants were young people with autism spectrum disorders receiving treatment for anxiety, clinical staff treating these young people and the independent raters assessing the treatment sessions. We report: (i) the processes involved in establishing inter-rater reliability for two instruments, (ii) the results obtained with a sample of young people with autism spectrum disorders using these instruments. Results and conclusions: Results demonstrate that it was possible to attain satisfactory inter-rater reliability with each of these two instruments with a client group with autism spectrum disorders, even though the instruments were originally designed for typically-developing populations

Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia

Background: Over the past decade genome-wide association studies (GWAS) have been applied to aid in the understanding of the biology of traits. The success of this approach is governed by the underlying effect sizes carried by the true risk variants and the corresponding statistical power to observe such effects given the study design and sample size under investigation. Previous ASD GWAS have identified genome-wide significant (GWS) risk loci; however, these studies were of only of low statistical power to identify GWS loci at the lower effect sizes (odds ratio (OR) <1.15). Methods: We conducted a large-scale coordinated international collaboration to combine independent genotyping data to improve the statistical power and aid in robust discovery of GWS loci. This study uses genome-wide genotyping data from a discovery sample (7387 ASD cases and 8567 controls) followed by meta-analysis of summary statistics from two replication sets (7783 ASD cases and 11359 controls; and 1369 ASD cases and 137308 controls). Results: We observe a GWS locus at 10q24.32 that overlaps several genes including PITX3, which encodes a transcription factor identified as playing a role in neuronal differentiation and CUEDC2 previously reported to be associated with social skills in an independent population cohort. We also observe overlap with regions previously implicated in schizophrenia which was further supported by a strong genetic correlation between these disorders (Rg = 0.23; P=9 ×10−6). We further combined these Psychiatric Genomics Consortium (PGC) ASD GWAS data with the recent PGC schizophrenia GWAS to identify additional regions which may be important in a common neurodevelopmental phenotype and identified 12 novel GWS loci. These include loci previously implicated in ASD such as FOXP1 at 3p13, ATP2B2 at 3p25.3, and a ‘neurodevelopmental hub’ on chromosome 8p11.23. Conclusions: This study is an important step in the ongoing endeavour to identify the loci which underpin the common variant signal in ASD. In addition to novel GWS loci, we have identified a significant genetic correlation with schizophrenia and association of ASD with several neurodevelopmental-related genes such as EXT1, ASTN2, MACROD2, and HDAC4

KLASIFIKASI AUTISM SPECTRUM DISORDER MENGGUNAKAN ALGORITMA NAIVE BAYES

Autism Spectrum Disorders (ASD) merupakan suatu kelainan pada otak manusia yang mengakibatkan seseorang mengalami gangguan dalam melakukan komunikasi dan interaksi terhadap sosial. Meningkatnya penderita Autism Spectrum Disorders di dunia memerlukan deteksi dini terhadap kelainan tersebut untuk mengurangi risiko negatif yang ditimbulkan dan memberikan perawatan yang tepat untuk penderitanya. Beberapa peneliti telah melakukan klasifikasi Autism Spectrum Disorders, namun belum ada yang mengklasifikasikan Autism Spectrum Disorders dengan algoritma Naive Bayes. Sehingga pada penelitian ini klasifikasi Autism Spectrum Disorders dilakukan berdasarkan Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-5) dengan algoritma Naive Bayes. Dalam dataset terdapat 292 anak dengan dua kelas yaitu normal dan Autism Spectrum Disorders yang diperoleh dari UCI Machine Learning Repository. Terdapat 20 atribut yang digunakan untuk mengklasifikasikan Autism Spectrum Disorders pada anak. Data yang ada dibagi menjadi data latih dan data uji berdasarkan hold out validation. Berdasarkan hasil klasifikasi, Naive Bayes dengan rasio data latih dan uji 1:1 menghasilkan akurasi tertinggi sebesar 98.6301%

Prenatal Neurogenesis in Autism Spectrum Disorders.

An ever-increasing body of literature describes compelling evidence that a subset of young children on the autism spectrum show abnormal cerebral growth trajectories. In these cases, normal cerebral size at birth is followed by a period of abnormal growth and starting in late childhood often by regression compared to unaffected controls. Recent work has demonstrated an abnormal increase in the number of neurons of the prefrontal cortex suggesting that cerebral size increase in autism is driven by excess neuronal production. In addition, some affected children display patches of abnormal laminar positioning of cortical projection neurons. As both cortical projection neuron numbers and their correct layering within the developing cortex requires the undisturbed proliferation of neural progenitors, it appears that neural progenitors lie in the center of the autism pathology associated with early brain overgrowth. Consequently, autism spectrum disorders associated with cerebral enlargement should be viewed as birth defects of an early embryonic origin with profound implications for their early diagnosis, preventive strategies, and therapeutic intervention

Reflections on diagnosing autism spectrum disorders

Personal reflections on the issue of labelling children as being on the autism spectrum

Autism spectrum disorders

Autism is one of the most hotly debated disorders listed in the current Diagnostic and Statistical Manual (DSM), eliciting passionate and often conflicting opinions among health professionals, medical practitioners, parents and researchers. Despite moving on from the early and notorious 'refrigerator mother' pathogenic theories (where autism was said to be caused by emotionally distant parents) to more modem epigenetic conceptualisations (where autism is viewed as being caused by an interaction between a genetic susceptibility and an environmental trigger), surprisingly little has changed in regards to autism as a diagnostic construct. The exclusive use of a triad of behavioural indicators (impaired social interaction and communication, and restricted and repetitive behaviour) to diagnose autism appears to be increasingly out of step with contemporary research into 'biomarkers' or biomedical aspects of the condition. An understanding of the tensions and conflicts surrounding autism is critical in order to fully appreciate tlte conservative nature of information provided in the DSM. This chapter will touch on some of the controversies as they apply to the inclusion of autism in the DSM, ultimately, leading us to consider the most controversial question of all: Does autism belong in the DSM at all

Michelle Grenier, Associate Professor of Kinesiology, travels to Scotland

Professor Grenier travelled to Scotland to continue her research on physical education teacher practices for students with autism spectrum disorders in the Scottish system