自闭症智能应用行为分析(Smart ABA)中离散试验训练(DTT)程序的开发

Arneliza Anwar, Rudy Sutadi, Chairita Miranda
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引用次数: 0

摘要

洛瓦斯是第一个将行为矫正原理应用于自闭症的专业人士,他称之为DTT(离散试验训练)技术,后来被称为ABA(应用行为分析)。通过他的研究,洛瓦斯发现47%的科目取得了优异的成绩。而42%的人有不同程度的进步,另外11%的人几乎没有进步。在数字地面电视中,有两种可能的反应,但研究人员的观察似乎不只是两种可能。本研究的目的是改进离散试验训练(DTT)程序,以提高智能应用行为分析治疗自闭症谱系障碍的有效性。本研究采用定量研究方法,采用文献回顾研究设计。研究数据是通过访谈、文献研究和文献综述(期刊和网站)获得的。这项研究的重点是研究人员的发现,这些发现适用于早期的理论。这项研究是在研究人员的自闭症诊所进行的。在使用DTT治疗的实施过程中,研究者观察到孩子的反应不仅只有2种,即正确和不正确。根据所进行的研究,得出了5种可能的反应:正确、不正确、部分正确、偏离任务和无反应。每一种都需要不同的反馈及其后续序列,以及不同致病因素的可能性,需要不同的干预措施。进一步的大样本和多中心样本研究将进一步提高DTT在自闭症智能ABA中的应用效果。这项研究是基于研究人员在观察、指导和监督自闭症治疗师时的发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of Discrete Trial Training (DTT) Procedure in Smart Applied Behavior Analysis (Smart ABA) for Autism
Lovaas was the first professional to use the principle of behavior modification for autism with a technique he called DTT (Discrete Trial Training), which later to be known as ABA (Applied Behavior Analysis). Through his study, Lovaas found that 47% of subjects had excellent results. While 42% with varying degrees, and the other 11% of subjects very little progress. In DTT, there are 2 possible responses, but the researchers' observations do not seem to be just 2 possibilities. This study's goal is to improve discrete trial training (DTT) procedures to increase the effectiveness of Smart Applied Behavior Analysis therapy for autism spectrum disorder. This study uses quantitative methods with a literature review research design. Research data is obtained through interviews, document studies, and literature reviews (journals and websites). The study focused on the researchers' findings that were adapted to earlier theories. The study was conducted at the researchers' autism clinic. During the implementation of therapy using DTT, the researchers observed that the child's response is not only 2, namely correct and incorrect. Based on the study conducted, it was obtained that there were 5 possible responses: Correct, incorrect, partial-correct, off-task, and no-response. Each of which required different feedback and its subsequent sequences, as well as the possibility of different causative factors which require different interventions. Further research with large and multi-center samples will further increase the effectiveness of DTT applications in Smart ABA for autism. This study was based on the researchers' findings while observing, mentoring, and supervising autism therapists.
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