Early Intensive Behavioral Intervention for Autism

自闭症早期强化行为干预

基本信息

批准号：
9294110
负责人：
TRISTRAM H SMITH
金额：
$ 31.96万
依托单位：
UNIVERSITY OF ROCHESTER
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-07-01 至 2019-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9294110
关键词：
Academic achievement Adaptive Behaviors Address Affect Age Autistic Disorder Behavior Therapy Caregivers Characteristics Child Clinical Cognitive Communication Communities Complex Control Groups Development Diagnosis Effectiveness Equation Evaluation Family Family Characteristics Funding Funding Agency Future Hour Individual Individual Differences Intelligence Intervention Intervention Studies Knowledge Language Linear Regressions Longitudinal Studies Measures Modeling Motor Nursery Schools Outcome Outcome Measure Outcome Study Participant Patients Probability Protocols documentation Psychopathology Reporting Research Research Design Research Personnel Research Priority Research Support Sampling Selection for Treatments Severities Social Functioning Social Interaction Structural Models Symptoms Techniques Testing Time Transcend Treatment outcome Validation Weight Work autism spectrum disorder cognitive ability cognitive function community setting comparison group cost effective intervention follow-up group intervention improved indexing individualized medicine outcome forecast outcome prediction primary outcome public health relevance skills social social engagement social skills stereotypy symptomatology teacher therapy design treatment as usual treatment site

项目摘要

DESCRIPTION (provided by applicant): We propose to study the long term outcome of Early Intensive Behavioral Intervention (EIBI) for children with autism spectrum disorder (ASD and to test promising predictors of outcome. We will follow up at age 14-15 71 children treated in the preschool years with EIBI in publicly funded community agencies and 65 children contemporaneously diagnosed with autism but who did not receive EIBI (Treatment as Usual, TAU). ABA intervention models such as EIBI have empirical support from many studies, but it remains important to assess their long term impact, particularly when delivered in community agencies, where most intervention is administered. Previous studies have evaluated outcome primarily with respect to IQ and academic functioning. Therefore, we will compare the outcome of EIBI and TAU with a comprehensive battery that includes measures of ASD symptoms, intellectual function, adaptive skills, social competence, language, academic achievement, and psychopathology. These variables not only have empirical support as being core and associated features of ASD, but are related to the skills acquired in EIBI. We expect children with EIBI to have better outcome than the TAU sample overall. We will use marginal structural models (MSMs) to examine group differences; MSM uses the probability of treatment selection as a weight to adjust for the bias in treatment selection, a technique known as the inverse probability weighting. Finally, noting the labor intensiveness and expense of EIBI, we will test pre-treatment predictor variables with some empirical support from prior studies by our research group and other investigators: social engagement and stereotypy. We will use multiple linear regression to test the hypothesized predictors. To improve robustness, we will use the generalized estimating equations (GEE) for inference. Identifying predictors of outcome of EIBI will permit therapists to avoid focusing on children unlikely to benefit from this treatment and facilitate future efforts to develop effective interventions for these children. The proposed study represents the longest follow-up of large EIBI and TAU samples, such that we would have a unique opportunity to examine long-term outcomes and the prediction of outcomes for EIBI.

DESCRIPTION (provided by applicable): We propose to study the long term outcome of Early Intensive Behavioral Intervention (EIBI) for children with autism spectrum disorder (ASD and to test promising predictors of outcome. We will follow up at age 14-15 71 children treated in the preschool years with EIBI in publicly funded community agencies and 65 children contemporaneously diagnosed with autism but who did not receive EIBI (Treatment as Usual, TAU).诸如EIBI之类的ABA干预模型具有许多研究的经验支持，但在社区机构中进行了长期影响，尤其是在社区机构中进行的大多数干预措施都评估了有关智商和学术功能的主要研究。和心理病理学。这些变量不仅具有ASD的核心和相关特征，而且与EIBI中获得的技能有关。我们希望患有EIBI的儿童总体上比TAU样本更好。我们将使用边缘结构模型（MSM）来检查群体差异。 MSM使用治疗的可能性。选择作为调整治疗选择偏差的重量，这是一种称为反概率加权的技术。最后，指出EIBI的劳动力和费用，我们将在我们的研究小组和其他研究者先前研究的一些经验支持下测试预处理预测变量：社会参与和刻板印象。我们将使用多个线性回归来测试假设的预测因子。为了提高鲁棒性，我们将使用广义估计方程（GEE）进行推理。确定EIBI结果的预测因素将使治疗师避免专注于儿童不太可能从这种治疗中受益，并促进未来的努力为这些孩子制定有效的干预措施。拟议的研究代表了大型EIBI和TAU样品的最长随访，因此我们将有一个独特的机会来检查长期结果和EIBI结果的预测。