Nationwide Children's Hospital, Columbus, OH, USA.
Ohio State University, Columbus, OH, USA.
J Autism Dev Disord. 2019 Nov;49(11):4674-4680. doi: 10.1007/s10803-019-04153-3.
We investigated the clinical validity of the BADEC, an abbreviated, five-item version of the Autism Detection in Early Childhood, level-2 screening tool for autism. Initially developed by Nah et al. (2019) using a research sample, the present study replicated Nah et al. (2019) procedures in a clinical population. Using a cutoff score of five, five items were identified as most effective in discriminating children who later received an ASD diagnosis by an interdisciplinary team. This algorithm had improved validity compared to the original research algorithm. Results supported the efficacy of a very brief, easy to administer ASD screening tool in identifying children under three who are likely to have ASD.
我们研究了 BADEC 的临床有效性,这是自闭症早期检测(Autism Detection in Early Childhood)二级筛查工具的一个缩写的、五个项目的版本,用于自闭症的筛查。该工具最初由 Nah 等人(2019 年)在研究样本中开发,本研究在临床人群中复制了 Nah 等人(2019 年)的程序。使用五分制的截断分数,确定了五个项目作为区分后来由跨学科团队诊断为自闭症谱系障碍(ASD)的儿童的最有效项目。与原始研究算法相比,该算法提高了有效性。结果支持了一种非常简短、易于实施的自闭症筛查工具的功效,该工具可以识别三岁以下可能患有自闭症的儿童。