8
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      Child-Robot Interaction in a Musical Dance Game: An Exploratory Comparison Study between Typically Developing Children and Children with Autism

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Related collections

          Most cited references43

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years — Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2016

          Problem/Condition Autism spectrum disorder (ASD). Period Covered 2016. Description of System The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance program that provides estimates of the prevalence of ASD among children aged 8 years whose parents or guardians live in 11 ADDM Network sites in the United States (Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin). Surveillance is conducted in two phases. The first phase involves review and abstraction of comprehensive evaluations that were completed by medical and educational service providers in the community. In the second phase, experienced clinicians who systematically review all abstracted information determine ASD case status. The case definition is based on ASD criteria described in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Results For 2016, across all 11 sites, ASD prevalence was 18.5 per 1,000 (one in 54) children aged 8 years, and ASD was 4.3 times as prevalent among boys as among girls. ASD prevalence varied by site, ranging from 13.1 (Colorado) to 31.4 (New Jersey). Prevalence estimates were approximately identical for non-Hispanic white (white), non-Hispanic black (black), and Asian/Pacific Islander children (18.5, 18.3, and 17.9, respectively) but lower for Hispanic children (15.4). Among children with ASD for whom data on intellectual or cognitive functioning were available, 33% were classified as having intellectual disability (intelligence quotient [IQ] ≤70); this percentage was higher among girls than boys (40% versus 32%) and among black and Hispanic than white children (47%, 36%, and 27%, respectively). Black children with ASD were less likely to have a first evaluation by age 36 months than were white children with ASD (40% versus 45%). The overall median age at earliest known ASD diagnosis (51 months) was similar by sex and racial and ethnic groups; however, black children with IQ ≤70 had a later median age at ASD diagnosis than white children with IQ ≤70 (48 months versus 42 months). Interpretation The prevalence of ASD varied considerably across sites and was higher than previous estimates since 2014. Although no overall difference in ASD prevalence between black and white children aged 8 years was observed, the disparities for black children persisted in early evaluation and diagnosis of ASD. Hispanic children also continue to be identified as having ASD less frequently than white or black children. Public Health Action These findings highlight the variability in the evaluation and detection of ASD across communities and between sociodemographic groups. Continued efforts are needed for early and equitable identification of ASD and timely enrollment in services.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found

            Which terms should be used to describe autism? Perspectives from the UK autism community.

            Recent public discussions suggest that there is much disagreement about the way autism is and should be described. This study sought to elicit the views and preferences of UK autism community members - autistic people, parents and their broader support network - about the terms they use to describe autism. In all, 3470 UK residents responded to an online survey on their preferred ways of describing autism and their rationale for such preferences. The results clearly show that people use many terms to describe autism. The most highly endorsed terms were 'autism' and 'on the autism spectrum', and to a lesser extent, 'autism spectrum disorder', for which there was consensus across community groups. The groups disagreed, however, on the use of several terms. The term 'autistic' was endorsed by a large percentage of autistic adults, family members/friends and parents but by considerably fewer professionals; 'person with autism' was endorsed by almost half of professionals but by fewer autistic adults and parents. Qualitative analysis of an open-ended question revealed the reasons underlying respondents' preferences. These findings demonstrate that there is no single way of describing autism that is universally accepted and preferred by the UK's autism community and that some disagreements appear deeply entrenched.
              Bookmark
              • Record: found
              • Abstract: not found
              • Book: not found

              Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR)

              (2000)
                Bookmark

                Author and article information

                Journal
                International Journal of Human–Computer Interaction
                International Journal of Human–Computer Interaction
                Informa UK Limited
                1044-7318
                1532-7590
                February 07 2021
                September 14 2020
                February 07 2021
                : 37
                : 3
                : 249-266
                Affiliations
                [1 ]Department of Computer Science, Michigan Technological University, Houghton, MI, USA
                [2 ]Department of Biomedical Engineering, The George Washington University, Washington, DC, USA
                [3 ]School of Interactive Computing, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
                [4 ]Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
                Article
                10.1080/10447318.2020.1819667
                e94f744b-191d-4336-8257-e192a88b6442
                © 2021
                History

                Comments

                Comment on this article

                scite_
                0
                0
                0
                0
                Smart Citations
                0
                0
                0
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content1,820

                Cited by12

                Most referenced authors631