Autistic Behavior Checklist (ABC) and Its Applications

Oro, Antonio Bravo; Navarro-Calvillo, María E.; Esmer, Carmen

doi:10.1007/978-1-4614-4788-7_164

Cited by 12 publications

(12 citation statements)

References 19 publications

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“…ABC was developed to identify autistic behaviours in intellectually disabled and severely disabled children. ABC is easy to use and can be applied by parents, but cut-off needs to be set 17 . Various authors have suggested a different cut-off score.…”

Section: Discussionmentioning

confidence: 99%

Development of a screening instrument for autism spectrum disorder

Arun¹,

Chavan²

2018

Indian Journal of Medical Research

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Background & objectives:There is a paucity of trained professionals for the diagnosis of autism spectrum disorder (ASD), and a large number of cases go undetected and are diagnosed only during adolescence. There is no screening instrument specifically developed for screening of Indian population for ASD. This study was undertaken to develop a screening instrument to screen ASD in north Indian Hindi speaking population by multipurpose health workers.Methods:A 37-item instrument in Hindi with dichotomous yes/no responses [Chandigarh Autism Screening Instrument (CASI)] was developed to be applied on children aged 1.5-10 yr. The instrument was pilot tested and then reliability and validity of this instrument were tested. The sample included children with intellectual disability (n=75), ASD (n=83), other developmental disorders (n=87) and typically developing children (n=160).Results:Reliability, construct and content validity testing of the instrument were performed, and a score of 10 as cut-off had sensitivity of 89.16 per cent, specificity of 89.13 per cent, positive predictive value of 67.89 per cent and negative predictive value of 96.96 per cent. A shorter four-item version (CASI Bref) has also been developed with good sensitivity (73.49%) and specificity (90.68%) at a cut-off score of 2.Interpretation & conclusions:CASI was found to be a valid instrument for screening general Hindi speaking population of north India with adequate sensitivity and specificity.

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Section: Discussionmentioning

confidence: 99%

Development of a screening instrument for autism spectrum disorder

Arun¹,

Chavan²

2018

Indian Journal of Medical Research

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“…In 2012, Allison et al create a new version of Autism-Spectrum Quotient (AQ) for adults consisted of 10-items only to make it simpler and more timesaving. AQ-10 has a predictive power similar to the origin AQ version [5,18]. Later on, Allison created shorter versions for adolescents and children with ten items too.…”

Section: E Short Autism Quantitative (Aq-10)mentioning

confidence: 93%

“…Based on autism speaks organization in USA, ASD diagnoses by applying behavioral exams or questionnaires, which require a lot of time and effort provided from parents and clinicians [12]. Therefore, this work shows the power of machine learning algorithms in detecting individuals with specific Autistic Spectrum Disorder symptoms [5].…”

Section: Introductionmentioning

confidence: 93%

“…The method combines different scales, such as language, object recognition, body, sensory, social, and daily use skills [10]. The item scores are mostly from 1-5 based on the impairment degree [2,5]. The ABC has been in use for more than 30 years as a rapid tool for diagnosing autism in early stages [7,13].…”

Section: A Autism Behavior Checklist (Abc)mentioning

confidence: 99%

“…Machine learning can be sorted as unsupervised and supervised learning. ASD diagnosing is a supervised machine learning that has a dependent variable to be predicted, which is the result of the diagnosis [5,24]. A successful supervised machine-learning model is the one that can predict the target correctly and generalize new instances predicts.…”

Section: H Recent Machine Learning Research On Asd Screening and Diamentioning

confidence: 99%

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Autism Spectrum Disorder Diagnosis using Optimal Machine Learning Methods

Alteneiji¹,

Mohammed²,

Usman³

2020

IJACSA

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Autism spectrum disorder (ASD) is the disorder of communication and behavior that affects children and adults. It can be diagnosed at any stage of life. Most importantly, the first two years of life, regardless of ethnicity, race, or economic groups. There are different variations of ASD according to the severity and type of symptoms experienced by people. It is a lifelong disorder, but treatment and services can improve the symptoms. The literature focuses on one of the main methods used by physicians to diagnose ASD. Many types of research and medical reports have been reviewed; however, a few of them only give good medical results for the strong differentiation of ASD from healthy people. This paper focuses on using machine learning algorithms to predict an individual with specific ASD symptoms. The target is to predict an individual with specific ASD symptoms and finding the best machine learning model for diagnosis. Further, the paper aims to make the autism diagnosis faster to deliver the required treatment at an early stage of child development.

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Prenatal maternal stress and autistic‐like behaviours in Chinese preschoolers

Chen

Strodl

et al. 2020

Stress and Health

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Exposure to prenatal maternal stress (PNMS) has been implicated as a risk factor for a range of psychiatric disorders in children. However, there have been a few studies showing inconsistent associations between PNMS and offspring autistic‐like behaviours. We therefore aimed to examine whether trimester‐specific PNMS exposure might be related to an increased risk of autistic‐like behaviours among preschoolers. Using data from Longhua Children Cohort Study, mothers of 65,931 preschool children were asked to recall their level of PNMS in each of the three trimesters of pregnancy, while children's current autistic‐like behaviours were assessed using the Autism Behaviour Checklist. A series of Cox regression models were fitted to assess the association between PNMS exposure and autistic‐like behaviours. After adjusting for potential confounders, the Cox regression models showed that PNMS exposure, especially during the second pregnant trimester, was significantly and positively associated with the presence of children's autistic‐like behaviours. The strength of these associations was enhanced with the increase of PNMS exposure level. Furthermore, based on different permutations of exposure versus no exposure in each trimester, the participants were divided into eight groups. A cross‐over analysis confirmed the aforementioned finding that the second pregnant trimester might be the sensitive period for PNMS exposure increasing the risk of autistic‐like behaviours. Our findings supported the hypothesis of an association between PNMS exposure and autistic‐like behaviours among preschoolers. Preventive interventions should be trialled to examine whether minimizing maternal psychological stress during pregnancy, especially the second trimester, may reduce the risk of offspring autistic‐like behaviours.

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Autistic Behavior Checklist (ABC) and Its Applications

Cited by 12 publications

References 19 publications

Development of a screening instrument for autism spectrum disorder

Development of a screening instrument for autism spectrum disorder

Autism Spectrum Disorder Diagnosis using Optimal Machine Learning Methods

Prenatal maternal stress and autistic‐like behaviours in Chinese preschoolers

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