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抽取社会沟通的潜在子维度:跨测量因子分析。

Extracting Latent Subdimensions of Social Communication: A Cross-Measure Factor Analysis.

机构信息

UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA.

Feinberg School of Medicine, Northwestern University, Chicago, Illinois.

出版信息

J Am Acad Child Adolesc Psychiatry. 2021 Jun;60(6):768-782.e6. doi: 10.1016/j.jaac.2020.08.444. Epub 2020 Oct 4.

Abstract

OBJECTIVE

Social communication deficits associated with autism spectrum disorder (ASD) are commonly represented as a single behavioral domain. However, increased precision of measurement of social communication is needed to promote more nuanced phenotyping, both within the autism spectrum and across diagnostic boundaries.

METHOD

A large sample (N = 1,470) of 4- to 10-year-old children was aggregated from across 4 data sources, and then randomly split into testing and validation samples. A total of 57 selected social communication items from 3 widely used autism symptom measures (the Autism Diagnostic Observation Scale [ADOS], Autism Diagnostic Interview-Revised [ADI-R], and Social Responsiveness Scale [SRS]) were analyzed in the multi-trait/multi-method factor analysis framework. The selected model was then confirmed with the validation sample.

RESULTS

The 4-substantive factor model, with 3 orthogonal method factors, was selected using the testing sample based on fit indices and then confirmed with the validation sample. Two of the factors, "Basic Social Communication Skills" and "Interaction Quality," were similar to those identified in a previous analysis of the ADOS, Module 3. Two additional factors, "Peer Interaction and Modification of Behavior" and "Social Initiation and Affiliation," also emerged. Factor scores showed nominal correlations with age and verbal IQ.

CONCLUSION

Identification of subdimensions could inform the creation of better conceptual models of social communication impairments, including mapping of how the cascading effects of social communication deficits unfold in ASD versus other disorders. Especially if extended to include both older and younger age cohorts and individuals with more varying developmental levels, these efforts could inform phenotype-based exploration for biological and genetic mechanisms by pinpointing specific mechanisms that contribute to various types of social communication deficits.

摘要

目的

自闭症谱系障碍(ASD)相关的社交沟通缺陷通常表现为单一行为领域。然而,需要更精确地测量社交沟通,以促进自闭症谱系内和跨诊断边界的更细致表型分析。

方法

从四个数据来源汇总了一个包含 4 至 10 岁儿童的大样本(N=1470),然后随机分为测试和验证样本。从三个广泛使用的自闭症症状测量工具(自闭症诊断观察量表[ADOS]、自闭症诊断访谈修订版[ADI-R]和社交反应量表[SRS])中选择了 57 个社交沟通项目,在多特质/多方法因素分析框架中进行分析。然后使用验证样本确认所选模型。

结果

基于拟合指数,使用测试样本选择了 4 个实质性因素模型和 3 个正交方法因素,然后使用验证样本进行了确认。其中两个因素,“基本社交沟通技能”和“互动质量”与之前对 ADOS,模块 3 的分析中确定的因素相似。另外两个因素,“同伴互动和行为修正”和“社交发起和隶属关系”也出现了。因子得分与年龄和语言智商呈名义相关。

结论

亚维度的识别可以为社交沟通障碍的更好概念模型提供信息,包括描绘社交沟通缺陷的级联效应如何在 ASD 与其他障碍中展开。特别是如果将其扩展到包括年龄较大和较小的年龄组以及具有更不同发育水平的个体,这些努力可以通过指出导致各种类型社交沟通缺陷的特定机制,为基于表型的生物和遗传机制探索提供信息。

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