Autism incidence and spatial analysis in more than 7 million pupils in English schools: a retrospective, longitudinal, school registry study

Román-Urrestarazu, Andrés; Yang, Justin; Kessel, Robin van; Warrier, Varun; Dumas, Guillaume; Jongsma, Hannah E; Gatica-Bahamonde, Gabriel; Allison, Carrie; Matthews, Fiona; Baron‐Cohen, Simon; Brayne, Carol

doi:10.1016/s2352-4642(22)00247-4

Cited by 12 publications

(6 citation statements)

References 26 publications

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Section: Mainmentioning

confidence: 99%

“…Autism spectrum disorder (henceforth autism) is a neurodevelopmental condition that affects social interaction and communication and affects 1-2% of the global population 1,2 . Recently, there has been a growing interest in understanding autism prevalence, particularly using large research designs such as school registries and access to special educational needs (SEN) services from school registry data 1,2 . However, little is known about how this relates to clinical prevalence, and few studies have linked national registries to electronic health records 3 to study the gap between those diagnosed and those receiving support at school [4][5][6] .…”

Section: Mainmentioning

confidence: 99%

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Autism Prevalence in Chile: Unmet Special Education Needs using Data Linkage and Bayesian Analysis of Three Million School-Aged Children

Roman-Urrestarazu,

Tyson,

Gatica-Bahamonde

et al. 2024

Preprint

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Prevalence estimates of autism spectrum disorder (henceforth autism) in Latin America thus far have been limited by a lack of reliable population-level data. We analyzed autism school prevalence across 29 Chilean health service regions for students aged 6–18 years, standardized by age and sex. We validated these results using electronic health records from one of Chile’s largest regional health service, the Servicio de Salud Araucania Sur (SSAS). We then projected Bayesian prevalences, reporting nationally, and by health service, ethnicity, immigration background, and rurality. We found a standardized national school autism prevalence of 0.46% (95% CI, 0.46%-0.47%), with boys having six times higher odds of autism than girls (OR 6.10 [95%CI: 5.82–6.41]). The sex - and age-adjusted clinical prevalence in the SSAS trust was 1.22% (95% CI: 1.16%-1.28%) and the projected Bayesian national autism prevalence was 1.31% (95% Credible Interval: 1.25%-1.38%). Our results indicate a higher autism prevalence than previously reported in the south of the Araucania region with observed disparities in prevalence across sex, ethnic groups, and health services.

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Section: Mainmentioning

confidence: 99%

Section: Mainmentioning

confidence: 99%

Autism Prevalence in Chile: Unmet Special Education Needs using Data Linkage and Bayesian Analysis of Three Million School-Aged Children

Roman-Urrestarazu,

Tyson,

Gatica-Bahamonde

et al. 2024

Preprint

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“…One such disability is Autism spectrum disorder (ASD) a neurobiological disease impacting social relationships, interactions, and behaviour [1]. If it is not diagnosed in early childhood it affects later in future, and its prevalence is higher in boys [2], [3], [4]. Certain individuals having ASD can live independently, whereas others require lifelong care.…”

Section: Introductionmentioning

confidence: 99%

A Survey on E-Learning Recommendation Systems for Autistic People

Rathod,

Goudar,

Kulkarni

et al. 2024

IEEE Access

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Autism, also known as Autism Spectrum Disorder (ASD) or Asperger's syndrome, has an impact on cognition, social relationships, and behaviour. Based on these characteristics and their learning interests, e-learning recommendation systems attempt to provide personalized recommendations. This may enhance the learning ability of individuals with ASD. However, some technological challenges limit the ability of the population to use support scenarios and prevent efficient learning. This study tries to review elearning recommender systems for individuals with ASD. The main identified aspects are 1) a lack of design principles while building customized e-learning platforms for those with ASD, 2) technological limitations to developing recommender systems for e-learning, and 3) suggestions that reduce field limitations. The studies additionally discovered that social communication and psychological abilities had the greatest focus of study. A small number of studies mentioned the participant's ASD level, the majority of the articles highlighted the beneficial effects of designing a content-based recommender system specifically for those with ASD.

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“…The associate editor coordinating the review of this manuscript and approving it for publication was Meriel Huggard . and it is four times more common in boys than in girls [4], [5]. People with this syndrome are mainly affected by three aspects, known as the Triad of Impairments [6]: social relationships, communication, and behavior [7].…”

Section: Introductionmentioning

confidence: 99%

E-Learning Ecosystems for People With Autism Spectrum Disorder: A Systematic Review

2023

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E-Learning Ecosystems (ELE) offer excellent opportunities to manage teaching activities by incorporating state-of-the-art technologies, practices, and professional support, as well as learning and assessment resources that can be adaptive. Therefore, it can help people with disabilities or conditions such as Autism Spectrum Disorder (ASD) to develop skills. However, some technological factors prevent this population's implementation of support scenarios and hinder the proper learning process. This paper systematically reviews relevant studies on E-Learning Ecosystems for people with ASD, identifying the influence of Information and Communication Technologies (ICT) on forming ELE and the technological barriers that affect their development and appropriate use on people with ASD. This work conducted a systematic review using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, including a search of five scientific literature databases from 2017 to 2022. The main aspects identified were 1) a shortage in design guides for the implementation of e-learning ecosystems adapted for people with ASD, 2) technological barriers that prevent the development of ELE, and 3) recommendations that help to mitigate the limitations of this field. In addition, the authors identified that the skills with the most significant focus of interest were social, communicative, and cognitive. The most implemented technologies include virtual and augmented reality or mobile applications. Most studies involved children with ASD between 8 and 15 years, followed by works with children between 5 to 8 years. Very few researches linked adults with ASD. Very few studies mention the ASD level of the participants, but most highlight the positive results of implementing ICT in training processes.

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Autism incidence and spatial analysis in more than 7 million pupils in English schools: a retrospective, longitudinal, school registry study

Cited by 12 publications

References 26 publications

Autism Prevalence in Chile: Unmet Special Education Needs using Data Linkage and Bayesian Analysis of Three Million School-Aged Children

Autism Prevalence in Chile: Unmet Special Education Needs using Data Linkage and Bayesian Analysis of Three Million School-Aged Children

A Survey on E-Learning Recommendation Systems for Autistic People

E-Learning Ecosystems for People With Autism Spectrum Disorder: A Systematic Review

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