scholarly journals Technology-Supported Models for Individuals with Autism Spectrum Disorder

2020 ◽  
Vol 15 (23) ◽  
pp. 74
Author(s):  
Beria Gokaydin ◽  
Anna V. Filippova ◽  
Natalia E. Sudakova ◽  
Victoriya V. Sadovaya ◽  
Irina V. Kochova ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Age Groups ◽  
The United States ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Use Of Technology ◽  
Conference Announcement ◽  
Qualitative Research Methodology ◽  
Subject Areas ◽  
The Individual

Autism can be defined as a common developmental disorder that manifests itself as a disconnection in social communication. In individuals with autism, sometimes speech does not develop at all, and even if it develops, the individual does not prefer to communicate by talking. Thus, other ways are needed to communicate with individuals with autism. Today, the most important of these ways is technology, especially educational technology. The use of technology for individuals with Autism spectrum disorder (ASD) is on the rise today. The purpose of this study was to present up-to-date information on research using technology-based intervention methods in teaching skills in different developmental areas to individuals from different age groups with ASD and to reveal whether this intervention method is effective. This study was carried out using qualitative research methodology, document analysis and related content analysis. Scopus is based on the analysis of published documents searched with the keywords ‘autism and technology-based’ in the database. All articles published in Scopus were examined. The distribution of affiliated universities by years, subject areas, document types, country/regions and author themes were examined. Various findings emerged in terms of determining the importance of the analysis of technology-supported applications in terms of content of individuals published in the Scopus database on individuals with ASD. A total of 95 studies were examined. It was concluded that most of the studies were conducted in 2016 and 2019. It revealed that the first study was conducted in 2008. It was mostly published as a conference announcement. The United States and United Kingdom are among the countries with the most research. The research topics were written mostly in English, and two were published in French.

Specialized Diet Therapies: Exploration for Improving Behavior in Autism Spectrum Disorder (ASD)

2020 ◽  
Vol 27 (40) ◽  
pp. 6771-6786
Author(s):  
Geir Bjørklund ◽  
Nagwa Abdel Meguid ◽  
Maryam Dadar ◽  
Lyudmila Pivina ◽  
Joanna Kałużna-Czaplińska ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Neurodevelopmental Disorder ◽  
Caloric Intake ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Nutritional Deficiencies ◽  
Childhood And Adolescence ◽  
Restricted Interests ◽  
Balanced Diet ◽  
The Individual

As a major neurodevelopmental disorder, Autism Spectrum Disorder (ASD) encompasses deficits in communication and repetitive and restricted interests or behaviors in childhood and adolescence. Its etiology may come from either a genetic, epigenetic, neurological, hormonal, or an environmental cause, generating pathways that often altogether play a synergistic role in the development of ASD pathogenesis. Furthermore, the metabolic origin of ASD should be important as well. A balanced diet consisting of the essential and special nutrients, alongside the recommended caloric intake, is highly recommended to promote growth and development that withstand the physiologic and behavioral challenges experienced by ASD children. In this review paper, we evaluated many studies that show a relationship between ASD and diet to develop a better understanding of the specific effects of the overall diet and the individual nutrients required for this population. This review will add a comprehensive update of knowledge in the field and shed light on the possible nutritional deficiencies, metabolic impairments (particularly in the gut microbiome), and malnutrition in individuals with ASD, which should be recognized in order to maintain the improved socio-behavioral habit and physical health.

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.

Engaging Parents in the Development and Testing of a Website to Support Social-Communication and Play Development for Preschoolers with Autism Spectrum Disorder

2021 ◽  
pp. 016264342110558
Author(s):  
Jessica Amsbary ◽  
Mei-Ling Lin ◽  
Melissa N. Savage ◽  
Leslie Fanning ◽  
Stephanie Reszka ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Social Communication ◽  
Child Outcomes ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Developmental Processes ◽  
Website Usability ◽  
Website Development ◽  
School Collaboration ◽  
Use Of Technology

Preschoolers with autism spectrum disorder (ASD) present with social-communication and play challenges and would benefit from interventions targeting these skills. One way to ensure this is by engaging parents in technological supports to learn about an intervention and increase home-school collaboration. Thus, a website could potentially address both needs. This study describes the initial developmental processes of one such website. Specifically, we describe how engaging parents as stakeholders in the website development enhanced its future usability and feasibility. Data were collected through focus groups, interviews, and surveys to obtain parent feedback about website usability and applicability and about the intervention. Survey data were descriptively analyzed. Focus group and interview data were analyzed using systematic qualitative analysis. Parents perceived the website to be useful in helping them target social-communication and play with their preschoolers with ASD and highlighted specific aspects of the website and intervention they perceived as effective. Child outcomes and parent fidelity to the intervention supported these perceived developmental gains. Findings suggest that engaging parents in developmental processes may help ensure usability and applicability of resources and interventions. Furthermore, findings support the use of technology to help parents learn to use an intervention with their preschoolers with ASD. Implications for research and practice are discussed.

scholarly journals The earlier, the better? Diagnostic experiences of parents in a community-based early intervention system for preschool children with autism

2019 ◽  
Vol 4 ◽  
pp. 239694151984520
Author(s):  
Mitsuaki Iwasa ◽  
Yasuo Shimizu ◽  
Ikuko Hara ◽  
Miho Imai ◽  
Hideo Honda
Keyword(s):  
Autism Spectrum Disorder ◽  
Preschool Children ◽  
Early Intervention ◽  
Individual Case ◽  
Autism Spectrum ◽  
Parental Satisfaction ◽  
Spectrum Disorder ◽  
Diagnostic Process ◽  
Diagnostic Disclosure ◽  
The Individual

Background and aims In many countries, early detection and diagnosis of autism spectrum disorder is largely dependent on parents’ initial concern with early symptoms of autism spectrum disorder. Previous research on parental perceptions of the autism spectrum disorder diagnostic process indicates that parental satisfaction may be due to either the timing of the diagnostic notification or the provision of post-diagnostic support. The objective of this research is to study the diagnostic notification process and its impact on parents who are informed of their young child’s diagnosis before they notice a problem and whose child undergoes early intervention therapy. Methods Eighty parents of preschool children diagnosed and undergoing early intervention for autism were surveyed to examine their experience of the diagnostic disclosure process. Results Of 68 respondents, 39 (58.2%) approved of the timing of diagnostic notification, while 10 of 13 dissatisfied respondents indicated that the diagnosis was communicated too late. However, there was no correlation between a higher degree of parental satisfaction with the diagnostic notification process and earlier timing of notification. Conclusions Although it is preferable to communicate a diagnosis of childhood autism as soon as possible, findings suggest that a highly individualized approach, allowing a degree of latitude in the timing of notification, may be permissible, depending on the individual case and parental readiness to receive the diagnosis. Implications Findings have clinical implications related to the concept of optimality of diagnostic disclosure as related to the diagnostic notification process, though later notification tends to lead to more dissatisfaction.

scholarly journals The Impact of Technology on People with Autism Spectrum Disorder: A Systematic Literature Review

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4485 ◽  
Author(s):  
Katherine Valencia ◽  
Cristian Rusu ◽  
Daniela Quiñones ◽  
Erick Jamet
Keyword(s):  
Autism Spectrum Disorder ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Virtual Agents ◽  
Use Of Technology ◽  
Impact Of Technology ◽  
Game Elements ◽  
The Impact

People with autism spectrum disorder (ASD) tend to enjoy themselves and be engaged when interacting with computers, as these interactions occur in a safe and trustworthy environment. In this paper, we present a systematic literature review on the state of the research on the use of technology to teach people with ASD. We reviewed 94 studies that show how the use of technology in educational contexts helps people with ASD develop several skills, how these approaches consider aspects of user experience, usability and accessibility, and how game elements are used to enrich learning environments. This systematic literature review shows that the development and evaluation of systems and applications for users with ASD is very promising. The use of technological advancements such as virtual agents, artificial intelligence, virtual reality, and augmented reality undoubtedly provides a comfortable environment that promotes constant learning for people with ASD.

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