在具有代表性的人群样本中采用跨诊断方法研究神经多样性:N+ 4 模型

JCPP advances Pub Date : 2024-02-01 DOI:10.1002/jcv2.12219
Ian A. Apperly, Robert Lee, Sanne W. van der Kleij, R. Devine
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引用次数: 0

摘要

神经多样性的概念借鉴了科学研究以及实践和生活经验中的教训,提出了思考神经发育状况的新方法。在这些形成性观察中,与神经发育状况相关的特征是整个人群变异的 "更广泛表型 "的一部分,而且这些特征似乎存在 "跨诊断 "的相似性和差异性。本研究使用七种广泛使用的自我报告评估方法,对自闭症、多动症、阅读障碍、发育协调障碍/肢体瘫痪、抽搐症/妥瑞氏症、与亚临床癫痫相关的皮质过度兴奋以及感觉敏感性的相关特征进行了广泛的表型研究。我们使用确证因子分析来检验变异和共变的特征是(1)传统的诊断标签,还是(2)根据功能、行为或现象的相似性进行跨诊断。结果表明,神经多样性特征的最佳解释方法是双因子模型,即一个通用的 "N "因子和四个特定条件因子。这是迄今为止对与神经发育状况相关的更广泛表型的因子结构进行的最大规模的研究。它提供了重要的基准数据,并提供了一种框架方法,用于系统地询问在整个人群中以及在有一种或多种诊断的人群中出现的神经认知多样性的结构问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A transdiagnostic approach to neurodiversity in a representative population sample: The N+ 4 model
The concept of neurodiversity draws upon scientific research, and lessons from practice and lived experience to suggest new ways of thinking about neurodevelopmental conditions. Among the formative observations are that characteristics associated with neurodevelopmental conditions are part of a “broader phenotype” of variation across the whole population, and that there appear to be “transdiagnostic” similarities as well as differences in these characteristics. These observations raise important questions that have implications for understanding diversity in neurodevelopmental conditions and in neurocognitive phenotypes across the whole population.The present work examines broader phenotypes using seven widely used self‐report assessments of traits associated with autism, ADHD, dyslexia, Developmental Coordination Disorder/dyspraxia, tic disorders/Tourette's, cortical hyperexcitability associated with subclinical epilepsy, and sensory sensitivities. A representative sample of 995 adults (aged 17–77) in the UK completed self‐report measures of neurodiversity, wellbeing, generalized anxiety, and depression, and cognitive abilities (nonverbal intelligence and executive functioning).We used confirmatory factor analysis to test whether variation and covariation was better characterized (1) by traditional diagnostic labels, or (2) transdiagnostically according to similarities in functions, behaviours, or phenomena. Results indicated that neurodiversity characteristics were best explained using a bifactor model with one general “N” factor and four condition‐specific factors.This was the largest examination to date of the factor structure of broader phenotypes relevant to neurodevelopmental conditions. It provides critical benchmark data, and a framework approach for asking systematic questions about the structure of neurocognitive diversities seen in the whole population and in people with one or more diagnoses.
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