A multi-method assessment of error sensitivity and anxiety in childhood and adolescence

描述(申请人提供)：据估计，15%-20%的儿童和青少年受到焦虑症的影响，使焦虑症成为该人群中最常见的精神病理学诊断形式。因此，迫切需要识别标记 这些标记物可以预测正常和焦虑的发展轨迹，从而为病因提供信息，并预测随后的结果；这些标记物对于确定个人进行干预和预防工作也可能至关重要。在Hajcak Proudfit博士的指导下，目前的提案旨在调查核心风险时期的大样本儿童和青春期女性中与错误相关的大脑活动，这是一个有前景的焦虑生物标记物。目前正在收集事件相关电位和功能磁共振数据以及诊断性访谈和自我报告措施，对8至14岁的女孩进行由NIMH资助的关于8至14岁女孩的大规模(N=150)和正在进行的纵向R01研究；焦虑症状和诊断将在初次就诊约2年后进行评估。使用错误处理(两项ERP任务和一项功能磁共振成像)和焦虑(自我报告和访谈)的多个衡量标准，我将把错误敏感性和特质焦虑建模为潜在变量，并检查横断面和前瞻性关系，以便进行分析，以确定不同的神经衡量标准是否捕捉到与焦虑相关的独特和重叠的差异，以及错误敏感性是否可以预测青少年发展过程中焦虑的增加，从而控制最初的焦虑症状。目前的培训计划将把我的方法论技能扩展到fMRI，这样我就可以检查错误处理的多种神经测量；此外，我 将学习先进的统计学方法，将错误处理和焦虑之间的横截面和预期关系建模为潜在特征。目前的建议建立在先前工作的基础上，以解决文献中关于错误处理的不同神经测量对焦虑的特异性的空白，以及错误处理作为风险标记的有效性，可以前瞻性地预测增加的焦虑。

DESCRIPTION (provided by applicant): Between 15 - 20% of children and adolescents are estimated to be affected by anxiety disorders, making anxiety the most frequently diagnosed form of psychopathology in this population. Therefore, there is a critical need to identify markers of risk that predict normative versus anxious trajectories of development that could inform etiopathogenesis, and predict subsequent outcomes; such markers could also be critical for identifying individuals for intervention and prevention efforts. Under the guidance of Dr. Hajcak Proudfit, the current proposal aims to investigate error related brain activity, a promising biomarker of anxiety, in a large sample of children and adolescent females during a core risk period. ERPs and fMRI data, as well as diagnostic interviews, and self-report measures are currently being collected in a large (N=150) and longitudinal ongoing NIMH-funded R01 study on girls ranging from 8 to 14 years of age, oversampled based on risk for anxiety; anxiety symptoms and diagnoses will be assessed approximately 2 years after the initial visit. Using multiple measures of error processing (2 ERP tasks and 1 fMRI) and anxiety (self-report and interview), I will model error sensitivity and trait anxiety as latent variables and examine both cross-sectional and prospective relationships, allowing for analyses to determine whether different neural measures capture both unique and overlapping variance related to anxiety and whether error sensitivity can predict increased anxiety across adolescent development, controlling for initial anxiety symptoms. The current training plan will expand my methodological skills to fMRI, so that I can examine multiple neural measures of error-processing; additionally, I will learn advanced statistical approaches to model cross-sectional and prospective relationships between error processing and anxiety as latent traits. The current proposal builds on prior work to address a gap in the literature regarding the specificity of different neural measures of error processing to anxiety, as well as the validity of error processing as a risk marker that can predict increased anxiety prospectively.