scholarly journals The Alert Collector: Autism Spectrum Disorder: A Guide to the Latest Resources

2015 ◽  
Vol 55 (2) ◽  
pp. 113
Author(s):  
Michele Frasier-Robinson
Keyword(s):  
Autism Spectrum Disorder ◽  
Social Communication ◽  
Neurodevelopmental Disorders ◽  
The United States ◽  
Autism Spectrum ◽  
Repetitive Behaviors ◽  
Spectrum Disorder ◽  
Statistical Manual ◽  
Diagnostic And Statistical Manual ◽  
Dsm 5

Since the early 1990s there has been a steady escalation in the numbers of children diagnosed with autism spectrum disorder (ASD)—today it is considered the fastest growing developmental disability in the United States. In 2010, it was estimated that 1 in 68 children were affected by autism spectrum disorder. This is an increase of approximately 120 percent from the data collected ten years earlier. Identifying it as one of six neurodevelopmental disorders, the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders (DSM-5) describes autism spectrum disorder as “a series of developmental disabilities characterized by impaired social communication and interaction skills, accompanied by the existence of repetitive behaviors or activities, such as rocking movements, hand clapping or obsessively arranging personal belongings.”

Autism Spectrum Disorder: Past, Present, and Future

2013 ◽  
Vol 22 (3) ◽  
pp. 131-138 ◽  
Author(s):  
Pat Mirenda
Keyword(s):  
Autism Spectrum Disorder ◽  
Social Communication ◽  
Diagnostic Category ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Communication Disorder ◽  
Statistical Manual ◽  
Diagnostic And Statistical Manual ◽  
Dsm 5 ◽  
Social Communication Disorder

Abstract This paper describes recent changes to the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association, 2013) that may affect AAC service availability to individuals with Autism Spectrum Disorder (ASD) and Social Communication Disorder, a new diagnostic category. In addition, it provides a summary of research on the proportion of individuals with ASD who do not develop functional speech and, thus, rely on AAC. Finally, it emphasizes the importance of conventional literacy instruction for this population, with specific attention to the need to provide alternatives to handwriting, based on recent research.

Neurodevelopmental Disorders (ASD and ADHD): DSM-5, ICD-10, and ICD-11

CNS Spectrums ◽  
2016 ◽  
Vol 21 (4) ◽  
pp. 295-299 ◽  
Author(s):  
Ellen Doernberg ◽  
Eric Hollander
Keyword(s):  
Mental Disorders ◽  
Neurodevelopmental Disorders ◽  
Neurodevelopmental Disorder ◽  
The United States ◽  
Autism Spectrum ◽  
Classification Systems ◽  
Statistical Manual ◽  
Diagnostic And Statistical Manual ◽  
Dsm 5 ◽  
Icd 10

Neurodevelopmental disorders, specifically autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) have undergone considerable diagnostic evolution in the past decade. In the United States, the current system in place is the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), whereas worldwide, the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) serves as a general medical system. This review will examine the differences in neurodevelopmental disorders between these two systems. First, we will review the important revisions made from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) to the DSM-5, with respect to ASD and ADHD. Next, we will cover the similarities and differences between ASD and ADHD classification in the DSM-5 and the ICD-10, and how these differences may have an effect on neurodevelopmental disorder diagnostics and classification. By examining the changes made for the DSM-5 in 2013, and critiquing the current ICD-10 system, we can help to anticipate and advise on the upcoming ICD-11, due to come online in 2017. Overall, this review serves to highlight the importance of progress towards complementary diagnostic classification systems, keeping in mind the difference in tradition and purpose of the DSM and the ICD, and that these systems are dynamic and changing as more is learned about neurodevelopmental disorders and their underlying etiology. Finally this review will discuss alternative diagnostic approaches, such as the Research Domain Criteria (RDoC) initiative, which links symptom domains to underlying biological and neurological mechanisms. The incorporation of new diagnostic directions could have a great effect on treatment development and insurance coverage for neurodevelopmental disorders worldwide.

Emotion Dysregulation in Autism Spectrum Disorder

2018 ◽  
pp. 282-298
Author(s):  
Emily Neuhaus
Keyword(s):  
Autism Spectrum Disorder ◽  
Social Communication ◽  
Educational Outcomes ◽  
Emotion Dysregulation ◽  
Research Priorities ◽  
Theoretical Models ◽  
Autism Spectrum ◽  
Repetitive Behaviors ◽  
Spectrum Disorder

Autism spectrum disorder (ASD) is defined by deficits in social communication and interaction, and restricted and repetitive behaviors and interests. Although current diagnostic conceptualizations of ASD do not include emotional difficulties as core deficits, the disorder is associated with emotion dysregulation across the lifespan, with considerable implications for long-term psychological, social, and educational outcomes. The overarching goal of this chapter is to integrate existing knowledge of emotion dysregulation in ASD and identify areas for further investigation. The chapter reviews the prevalence and expressions of emotion dysregulation in ASD, discusses emerging theoretical models that frame emotion dysregulation as an inherent (rather than associated) feature of ASD, presents neurobiological findings and mechanisms related to emotion dysregulation in ASD, and identifies continuing controversies and resulting research priorities.

scholarly journals Cariprazine alleviates core behavioral deficits in the prenatal valproic acid exposure model of autism spectrum disorder

2021 ◽  
Author(s):  
Viktor Román ◽  
Nika Adham ◽  
Andrew G. Foley ◽  
Lynsey Hanratty ◽  
Bence Farkas ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Social Communication ◽  
Partial Agonist ◽  
Social Play ◽  
Autism Spectrum ◽  
Social Recognition ◽  
Repetitive Behaviors ◽  
Spectrum Disorder ◽  
Exposure Model ◽  
Behavioral Deficits

Abstract Rationale Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits in social communication and interaction and restricted, repetitive behaviors. The unmet medical need in ASD is considerable since there is no approved pharmacotherapy for the treatment of these deficits in social communication, interaction, and behavior. Cariprazine, a dopamine D3-preferring D3/D2 receptor partial agonist, is already approved for the treatment of schizophrenia and bipolar I disorder in adults; investigation in patients with ASD is warranted. Objectives The aim of this study was to investigate the effects of cariprazine, compared with risperidone and aripiprazole, in the rat prenatal valporic acid (VPA) exposure model on behavioral endpoints representing the core and associated symptoms of ASD. Methods To induce the ASD model, time-mated Wistar rat dams were treated with VPA during pregnancy. Male offspring were assigned to groups and studied in a behavioral test battery at different ages, employing social play, open field, social approach-avoidance, and social recognition memory tests. Animals were dosed orally, once a day for 8 days, with test compounds (cariprazine, risperidone, aripiprazole) or vehicle before behavioral assessment. Results Cariprazine showed dose-dependent efficacy on all behavioral endpoints. In the social play paradigm, only cariprazine was effective. On the remaining behavioral endpoints, including the reversal of hyperactivity, risperidone and aripiprazole displayed similar efficacy to cariprazine. Conclusions In the present study, cariprazine effectively reversed core behavioral deficits and hyperactivity present in juvenile and young adult autistic-like rats. These findings indicate that cariprazine may be useful in the treatment of ASD symptoms.

RELATIONSHIP AMONG SENSORY ISSUES AND REPETITIVE BEHAVIORS IN CHILDREN WITH AUTISM SPECTRUM DISORDER

2020 ◽  
pp. 59-64
Author(s):  
OJS Admin
Keyword(s):  
Autism Spectrum Disorder ◽  
Social Communication ◽  
Children With Autism ◽  
Autism Spectrum ◽  
Repetitive Behaviors ◽  
Spectrum Disorder ◽  
Sensory Stimuli ◽  
Key Features ◽  
Communication Impairments ◽  
Autism Disorder

Sensory issues and Repetitive Behaviors are the key features of Autism Disorder Syndrome (ASD). This is a neurodevelopmental condition marked by social communication impairments and the occurrence ofrestricted and repeated behavioral habits and desires, including irregular responses to sensory stimuli.

scholarly journals Genotype-Based Deep Learning in Autism Spectrum Disorder: Diagnostic Classification and Prognostic Prediction Using Common Genetic Variants (Preprint)

2020 ◽  
Author(s):  
Haishuai Wang ◽  
Paul Avillach
Keyword(s):  
Machine Learning ◽  
Autism Spectrum Disorder ◽  
Deep Learning ◽  
The United States ◽  
Autism Spectrum ◽  
Repetitive Behaviors ◽  
Spectrum Disorder ◽  
Screening Tools ◽  
Common Variants ◽  
Autism Screening

BACKGROUND In the United States, about 3 million people have autism spectrum disorder (ASD), and around 1 out of 59 children are diagnosed with ASD. People with ASD have characteristic social communication deficits and repetitive behaviors. The causes of this disorder remain unknown; however, in up to 25% of cases, a genetic cause can be identified. Detecting ASD as early as possible is desirable because early detection of ASD enables timely interventions in children with ASD. Identification of ASD based on objective pathogenic mutation screening is the major first step toward early intervention and effective treatment of affected children. OBJECTIVE Recent investigation interrogated genomics data for detecting and treating autism disorders, in addition to the conventional clinical interview as a diagnostic test. Since deep neural networks perform better than shallow machine learning models on complex and high-dimensional data, in this study, we sought to apply deep learning to genetic data obtained across thousands of simplex families at risk for ASD to identify contributory mutations and to create an advanced diagnostic classifier for autism screening. METHODS After preprocessing the genomics data from the Simons Simplex Collection, we extracted top ranking common variants that may be protective or pathogenic for autism based on a chi-square test. A convolutional neural network–based diagnostic classifier was then designed using the identified significant common variants to predict autism. The performance was then compared with shallow machine learning–based classifiers and randomly selected common variants. RESULTS The selected contributory common variants were significantly enriched in chromosome X while chromosome Y was also discriminatory in determining the identification of autistic from nonautistic individuals. The ARSD, MAGEB16, and MXRA5 genes had the largest effect in the contributory variants. Thus, screening algorithms were adapted to include these common variants. The deep learning model yielded an area under the receiver operating characteristic curve of 0.955 and an accuracy of 88% for identifying autistic from nonautistic individuals. Our classifier demonstrated a significant improvement over standard autism screening tools by average 13% in terms of classification accuracy. CONCLUSIONS Common variants are informative for autism identification. Our findings also suggest that the deep learning process is a reliable method for distinguishing the diseased group from the control group based on the common variants of autism.

Autism spectrum disorder

2018 ◽  
Author(s):  
Sven Bölte ◽  
Luise Poustka ◽  
Hilde M. Geurts
Keyword(s):  
Autism Spectrum Disorder ◽  
Dual Diagnosis ◽  
Social Communication ◽  
Autism Spectrum ◽  
Intervention Strategies ◽  
Clinical Impact ◽  
Spectrum Disorder ◽  
Dsm 5 ◽  
Individual Outcomes ◽  
Dsm Iv

Autism spectrum disorder (ASD) is an early onset and persistent condition defined by alterations in social communication and social interation alongside repetitive, restricted stereotypic behaviours and interests causing disabilities. Until recently, research on the co-occurrence of ADHD with ASD has been limited by DSM-IV criteria, allowing no dual diagnosis of these two neurodevelopmental disorders. Since the DSM-5 permits a double diagnosis of ADHD plus ASD, research on their comorbidity has substantially increased. In addition to shared and distinct aetiological factors, studies have revealed a high clinical impact of the combined symptomatology on individual outcomes. This chapter provides a selective overview of behavioural, cognitive, and biological findings as well as intervention strategies in combined ADHD/ASD phenotypes.

Structure, longitudinal invariance, and stability of the Child Behavior Checklist 1½–5’s Diagnostic and Statistical Manual of Mental Disorders–Autism Spectrum Disorder scale: Findings from Generation R (Rotterdam)

Autism ◽  
2017 ◽  
Vol 23 (1) ◽  
pp. 223-235 ◽  
Author(s):  
Leslie A Rescorla ◽  
Akhgar Ghassabian ◽  
Masha Y Ivanova ◽  
Vincent WV Jaddoe ◽  
Frank C Verhulst ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Mental Disorders ◽  
Child Behavior ◽  
Child Behavior Checklist ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Statistical Manual ◽  
Diagnostic And Statistical Manual ◽  
Base Rates ◽  
Over Time

Although the Child Behavior Checklist 1½–5’s 12-item Diagnostic and Statistical Manual of Mental Disorders-Autism Spectrum Problems Scale (formerly called Pervasive Developmental Problems scale) has been used in several studies as an autism spectrum disorder screener, the base rate and stability of its items and its measurement model have not been previously studied. We therefore examined the structure, longitudinal invariance, and stability of the Child Behavior Checklist 1½–5’s Diagnostic and Statistical Manual of Mental Disorders-Autism Spectrum Problems Scale in the diverse Generation R (Rotterdam) sample based on mothers’ ratings at 18 months ( n = 4695), 3 years ( n = 4571), and 5 years ( n = 5752). Five items that seemed especially characteristic of autism spectrum disorder had low base rates at all three ages. The rank order of base rates for the 12 items was highly correlated over time ( Qs ⩾ 0.86), but the longitudinal stability of individual items was modest (phi coefficients = 0.15–0.34). Confirmatory factor analyses indicated that the autism spectrum disorder scale model manifested configural, metric, and scalar longitudinal invariance over the time period from 18 months to 5 years, with large factor loadings. Correlations over time for observed autism spectrum disorder scale scores (0.25–0.50) were generally lower than the correlations across time of the latent factors (0.45–0.68). Results indicated significant associations of the autism spectrum disorder scale with later autism spectrum disorder diagnoses.

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