Sleep disturbance and other co-occurring conditions in autistic children: A network approach to understanding their inter-relationships.

Amanda L Richdale, Amy M Shui, Linnea A Lampinen, Terry Katz
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Abstract

Autistic children frequently have one or more co-occurring psychological, behavioral, or medical conditions. We examined relationships between child behaviors, sleep, adaptive behavior, autistic traits, mental health conditions, and health in autistic children using network analysis. Network analysis is hypothesis generating and can inform our understanding of relationships between multiple conditions and behaviors, directing the development of transdiagnostic treatments for co-occurring conditions. Participants were two child cohorts from the Autism Treatment Network registry: ages 2-5 years (n = 2372) and 6-17 years (n = 1553). Least absolute-shrinkage and selection operator (LASSO) regularized partial correlation network analysis was performed in the 2-5 years cohort (35 items) and the 6-17 years cohort (36 items). The Spinglass algorithm determined communities within each network. Two-step expected influence (EI2) determined the importance of network variables. The most influential network items were sleep difficulties (2 items) and aggressive behaviors for young children and aggressive behaviors, social problems, and anxious/depressed behavior for older children. Five communities were found for younger children and seven for older children. Of the top three most important bridge variables, night-waking/parasomnias and anxious/depressed behavior were in both age-groups, and somatic complaints and sleep initiation/duration were in younger and older cohorts respectively. Despite cohort differences, sleep disturbances were prominent in all networks, indicating they are a transdiagnostic feature across many clinical conditions, and thus a target for intervention and monitoring. Aggressive behavior was influential in the partial correlation networks, indicating a potential red flag for clinical monitoring. Other items of strong network importance may also be intervention targets or screening flags.

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自闭症儿童的睡眠障碍和其他并发症:通过网络了解它们之间的相互关系。
自闭症儿童经常同时患有一种或多种心理、行为或医疗疾病。我们利用网络分析法研究了自闭症儿童的儿童行为、睡眠、适应行为、自闭症特征、心理健康状况和健康之间的关系。网络分析是一种假设生成方法,可以帮助我们了解多种病症和行为之间的关系,指导开发针对共存病症的跨诊断治疗方法。研究对象是自闭症治疗网络登记处的两组儿童:2-5 岁(n = 2372)和 6-17 岁(n = 1553)。对 2-5 岁队列(35 个项目)和 6-17 岁队列(36 个项目)进行了最小绝对收缩和选择算子(LASSO)正则化偏相关网络分析。Spinglass 算法确定了每个网络中的群落。两步预期影响(EI2)确定了网络变量的重要性。对幼儿影响最大的网络项目是睡眠困难(2 个项目)和攻击行为,对年长儿童影响最大的网络项目是攻击行为、社交问题和焦虑/抑郁行为。年幼儿童有五个社区,年长儿童有七个社区。在前三个最重要的桥梁变量中,夜醒/parasomnias 和焦虑/抑郁行为在两个年龄组中都存在,而躯体不适和睡眠开始/持续时间则分别在年幼组和年长组中存在。尽管各年龄组之间存在差异,但睡眠障碍在所有网络中都很突出,这表明睡眠障碍是许多临床疾病的一个跨诊断特征,因此也是干预和监测的目标。攻击性行为在部分相关网络中很有影响力,表明这是临床监测的一个潜在信号。其他具有较强网络重要性的项目也可能是干预目标或筛查标志。
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