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

“神经发育障碍（NDD）包括ADHD、自闭症、发育性语言障碍和特殊学习障碍是最常诊断的儿科疾病。这些国家荒漠化往往会对受影响的个人及其所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对NDD进行评估，每种途径通常都采用不同的证据基础和相关措施来得出分类诊断。然而，融合的研究证据表明，这种传统的方法不足以捕捉个体差异或NDD之间的重叠在其潜在的症状维度（基因，大脑，认知）。本项目将建立在新兴的研究领域标准框架，测量和验证的认知，情感和情绪处理维度的复杂性，支持广泛抽样的NDD，在儿童和年轻人。领先的分析方法和创新的采样和数据收集协议的独特组合（包括远程测试），将用于利用初级和二级研究数据，以提高诊断灵敏度，以检测，跟踪，预测和评估NDD集群。根据已公布的跨诊断协议和对数据结果的新分析，在一系列NDD中进行采样，将制定和编制一套评估措施，以评估关键的认知和心理健康领域。随后，将使用使用创建的评估组合的新数据，从因疑似或先前诊断出的困难而被转介到评估和支持服务的儿童和成人的跨诊断样本中获取数据。为了从更广泛的角度研究神经发育和疾病，该项目将探索和验证一系列用于数据分析的定制管道，包括潜在变量和基于聚类的方法以及动态网络建模。这些技术是，先验的，非常适合于数据驱动的，提出的维度框架，并提供了潜在的连续，多变量数据的复杂性，超越了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."