Interrelations between Perceptive-Cognitive Factors and Behavioural Variables to Level Diagnosis of People with Autism Spectrum Disorder

M. Rúa
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Abstract

Relationships analysis between perceptual-cognitive factors and behavioural variables it makes up autism spectrum disorder (ASD) differential specific diagnosis, constitute a fundamental recurrent of currently research, then found data allow the construction of integrated evaluation scales to validate more complete and reliable diagnosis of people with ASD. The interdimensional diagnostic Scale has been applied and coded for 10 dimensions: 1) conceptual units, 2) signifiers, 3) hierarchy, 4) nodal relationships, 5) categorical relationships, 6) Recovery, 7) social interaction, 8) social communication, 9) stereotypical behaviours, and 10) restrictive behaviours. A total of 75 participants with ASD have participated in this study of three ASD´ intensity levels and different age intervals, from 3 years old. Data analyses focused along study the factorial analysis determinant (KMO and Bartlett's test) statistic, as well as, bivariate correlations analysis for three dimensions calculated statistically: "processing", "social" and "behaviours", show significant critical inter-relational levels (sig: .00), which allows conclude to existence of highly relationships between both variables group and their practical applications for consequent, reliable and valid diagnosis process. Finally, the statistical data of your application to perform the level diagnostic analysis is completed, through corresponding statistical percentage, means and standard deviations, to facilitate the ASD level 1-2-3 diagnostic way.
感知认知因素与行为变量之间的相互关系对自闭症谱系障碍患者的诊断水平的影响
感知-认知因素与行为变量之间的关系分析构成了自闭症谱系障碍(ASD)的差异化具体诊断,是当前研究的一项基本的经常性工作。跨维度诊断量表已应用于 10 个维度并进行了编码:1)概念单位;2)标志物;3)层次结构;4)节点关系;5)分类关系;6)恢复;7)社会交往;8)社会交流;9)刻板行为;10)限制行为。共有 75 名患有自闭症的参与者参加了这项研究,他们的自闭症强度分为三个等级,年龄也从 3 岁开始不同。数据分析的重点是研究因子分析决定因素(KMO 和 Bartlett 检验)统计,以及统计计算出的三个维度的双变量相关分析:"处理"、"社会 "和 "行为 "这三个维度显示出显著的临界相互关系水平(sig:.00),从而得出这两个变量组之间存在高度关系的结论,并将其实际应用于相应的、可靠和有效的诊断过程。最后,通过相应的统计百分比、平均值和标准偏差,完成了对您的应用程序进行水平诊断分析的统计数据,以促进 ASD 1-2-3 水平诊断方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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