Embracing complexity in the characterisation and trcking of individual wellbeing across development

“包括多动症、自闭症、发展性语言障碍和特殊学习障碍在内的神经发育障碍（ndd）是最常被诊断的儿科疾病。这些ndd往往会对受影响的个人及其生活的社会产生不利的长期影响。目前通过各种教育、卫生和医疗服务途径评估ndd，每种途径通常采用不同的证据基础和相关措施来得出分类诊断。然而，越来越多的研究证据表明，这种传统方法无法充分捕捉到ndd在潜在症状维度（基因、大脑、认知）上的个体差异或重叠。该项目将建立在新兴研究领域标准框架的基础上，以测量和表征认知、情感和情感处理维度的复杂性，这些维度支持广泛抽样的儿童和年轻人的ndd。前沿的分析方法和创新的采样和数据收集协议（包括远程测试）的独特组合，将用于利用初级和次级研究数据，以提高诊断灵敏度，以检测、跟踪、预测和评估NDD集群。根据已发表的跨诊断协议和对一系列ndd样本数据结果的新分析，将制定和汇编一套评估措施，以评估关键的认知和心理健康领域。随后将使用使用评估组创建的新数据，从因疑似或先前诊断的困难而被转介到评估和支持服务机构的儿童和成人的跨诊断样本中获取数据。为了从更广阔的角度研究神经发育和疾病，该项目将探索和验证一系列定制的数据分析管道，包括潜在变量和基于集群的方法以及动态网络建模。这些技术先验地非常适合数据驱动的维度框架，并提供了在连续的、多元数据中描述复杂性的潜力，超越了更传统的病例对照设计。”

"Neurodevelopmental disorders (NDDs) including ADHD, autism, developmental language disorder and specific learning disabilities are among the most frequently diagnosed paediatric conditions. These NDDs may often have an adverse, long-term impact for the individuals affected and the societies in which they live. NDDs are currently assessed through a variety of educational, health and medical service pathways, each of which typically applies a different evidence base and associated measures to derive categorical diagnoses. However, converging research evidence shows that this conventional approach inadequately captures either individual variation or overlaps between NDDs in their underlying symptom dimensions (genes, brains, cognition).This project will build upon the emerging research domain criterion framework, to measure and characterise the complexity of the cognitive, affective and emotional processing dimensions that underpin broadly sampled NDDs, in both children and young adults. The unique combination of leading-edge analytic methods and innovative protocols for sampling and data collection (incl. remote testing), will be used to exploit both primary and secondary research data to enhance diagnostic sensitivity to detect, track, predict, and evaluate NDD clusters. Based on published transdiagnostic protocols and new analyses of outcomes of data, sampled across a range of NDDs, a set of assessment measures will be developed and compiled to assess key cognitive and mental health domains. New data using the assessment batteries created will subsequently be used to obtain data from transdiagnostic samples of children and adults who have been referred to assessment and support services for suspected or previously diagnosed difficulties. Toward the objective to study neurodevelopment and disorders from a broader perspective, the project will explore and validate a range of bespoke pipelines for data analyses, including latent variable and cluster-based approaches and dynamic network modelling. These techniques are, a priori, well-suited for the data-driven, dimensional frameworks proposed, and afford the potential to characterise complexity in continuous, multivariate data, beyond that offered by more traditional case-control designs."