JCPP advances Pub Date : 2024-06-28 DOI:10.1002/jcv2.12259
Tracey Chau, Jeggan Tiego, Louise E. Brown, Olivia J. Mellahn, Beth P. Johnson, Mark A. Bellgrove
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摘要

背景自闭症儿童往往同时患有注意力缺陷/多动障碍(ADHD)。亚临床 ADHD 特征的存在会对日常生活的各个方面产生重大影响。因此,了解这些特质在自闭症儿童中的分布情况可能会对诊断工具的有效性和后续干预措施的选择产生重要影响。本研究在以往家长报告的自闭症和多动症特质潜模型的基础上,提出了自闭症和多动症特质在两个独立的自闭症和神经症儿童样本中分布的初步模型。 方法 对参加澳大利亚或美国两项研究之一的 4-18 岁参与者的社会反应量表(第 2 版)和多动症症状和正常行为的强项和弱项量表(SWAN)的照顾者反应进行因子混合建模。 结果 在两个独立样本中,2因素3类因素混合模型与数据的拟合度最高。这些因子代表了 "自闭症 "和 "多动症 "的潜在结构。潜在类别代表了具有不同程度自闭症特质的儿童亚型,随着自闭症特质认可度的增加,多动症特质的水平也随之增加。每个模型的项目阈值和因子协方差矩阵都存在一些特定样本的差异。 结论 我们的研究结果表明,在神经畸形和自闭症患者中,亚临床ADHD特质的认可度往往会随着自闭症特质认可度的增加而增加。对临床上自闭症特质水平升高的儿童进行多动症特质常规筛查可能具有临床实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The distribution of parent-reported autistic and subclinical ADHD traits in children with and without an autism diagnosis

The distribution of parent-reported autistic and subclinical ADHD traits in children with and without an autism diagnosis

Background

Attention-deficit/hyperactivity disorder (ADHD) traits often co-occur in autistic children. The presence of subclinical ADHD traits can significantly impact upon different aspects of daily living. As such, understanding the distribution of these traits in autistic children may have important implications for the validity of diagnostic tools and subsequent intervention choices. This study builds on previous latent models of parent-reported autistic and ADHD traits to propose a preliminary model of their distribution in two independent samples of autistic and neurotypical children.

Methods

Factor mixture modelling was applied to caregiver responses to the Social Responsiveness Scale - 2nd edition and the Strengths and Weaknesses of ADHD Symptoms and Normal Behaviour Scale (SWAN) of participants aged 4–18 years who participated in one of two studies in Australia or in the United States.

Results

A 2-factor, 3-class factor mixture model demonstrated the best fit to the data across both independent samples. The factors represented the latent constructs of ‘autism’ and ‘ADHD’. The latent classes represented subtypes of children with different levels of autistic traits, with higher levels of ADHD traits as autistic trait endorsement increased. Some sample-specific differences were observed for each model's item thresholds and factor covariance matrices.

Conclusions

Our findings suggest that the endorsement of subclinical ADHD traits tends to increase alongside autistic trait endorsement across neurotypical and autistic presentations. There may be clinical utility in routinely screening for ADHD traits in children with clinically elevated levels of autistic traits.

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