Latent Constructs: Negative-Positive Valence Domains in Anxiety and Depression

潜在结构：焦虑和抑郁中的负正价域

• 批准号: 8573425
• 负责人: MARTIN P. PAULUS
• 金额: $ 46.66万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-09 至 2017-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8573425
• 关键词: Adopted; Amygdaloid structure; Anxiety; Behavior; Behavior Therapy; Behavioral; Brain imaging; Categories; Clinic; Clinical; Data Analyses; Depressed mood; Diagnostic; Diagnostic and Statistical Manual; Dimensions; Disease; Emotional disorder; Facial Expression; Factor Analysis; Fright; Functional disorder; Galvanic Skin Response; Heart Rate; Individual; Maps; Measurable; Measurement; Measures; Mental Depression; Mental disorders; Modeling; National Institute of Mental Health; Neurobiology; Neurosciences; Online Systems; Pathology; Patient Self-Report; Patients; Pharmacological Treatment; Physiological; Physiology; Population; Primary Health Care; Principal Component Analysis; Process; Psychopathology; Psychophysiology; Recruitment Activity; Relative (related person); Reporting; Reproducibility; Research; Research Personnel; Resources; Rewards; Sample Size; Sampling; Sinus Arrhythmia; Site; Societies; Specific qualifier value; Staging; Stimulus; System; Testing; Time; Treatment outcome; Ventral Striatum; Work; approach behavior; avoidance behavior; base; clinical research site; cohort; conditioned fear; design; falls; heuristics; improved; indexing; neural circuit; outcome forecast; public health relevance; relating to nervous system; repository; respiratory; reward processing; self reported behavior; two-dimensional

DESCRIPTION (provided by applicant): The NIMH Research Domain Criteria (RDoC) framework is a heuristic approach to integrate neuroscience with psychopathology. Thus, RDoC is the attempt to develop constructs that (a) connect across units of analysis, (b) are applicable across established diagnostic criteria, and (c) are a point of departure to provide measurable constructs that will be useful to gain a deeper understanding of psychiatric conditions. However, the lack of reliable, robust latent constructs derived from experimental measures is a critical barrier to organizing mental disorders along dimensions that can be mapped onto multiple units of analysis. We focus on the positive and negative valence system domains proposed by the RDoC using self-report, behavior, physiology, and neural circuit unit of analysis measures, apply them to a clinical population of individuals with anxiety or depression recruited from primary care clinics across two sites, and apply latent variable analysis to derive latent constructs of positiv and negative valence systems functioning that cut across units of analyses. The specific aims of the proposal are: (1) To recruit, assess, and analyze self-report, behavioral, physiological, and neural circuit unit of analysis data in an exploratory sample from a cohort of n=100 treatment seeking individuals presenting to primary care clinics at UCSD and UCLA. (2) To obtain a confirmatory sample of n=100 subjects at both sites using the same measurement approaches to determine the reproducibility and robustness of the latent constructs obtained from the exploratory sample. (3) To obtain a reliability sample of n=50 individuals at UCSD and UCLA that will be re-tested within a month to determine the reliability of the latent constructs. This wll be the first time neural indices of positive valence and negative valence are investigated within the same broadly defined sample of anxious or depressed patients. Extant studies of neural processes in emotional disorders are limited to relatively small sample sizes. By combining resources across two sites, we will recruit a large enough sample to conduct more comprehensive analyses than ever before achieved. Once the proposed aims are completed, we will have a robust and reliable dimensional set of variables that quantify the positive and negative valence domains based on a latent variable approach. These variables capture clinical variance and will have been obtained from two different clinical sites to provide empirical evidence of the generality of the negative and positive valence domains. These variables will subsequently be used to determine whether (a) they can be used as predictors for how well an individual will respond to pharmacological or behavioral treatment; (b) they can be differentially responsive to therapies that are specifically aimed at modifying the positive or negative valence systems, and (c) they can be used in subsequent computational and/or neural process models of anxiety and depression to gain a more fundamental understanding of the pathology that occurs in these individuals.

描述（由申请人提供）：NIMH 研究领域标准 (RDoC) 框架是一种将神经科学与精神病理学相结合的启发式方法。因此，RDoC 试图开发一些结构，这些结构（a）跨分析单元连接，（b）适用于既定的诊断标准，（c）是提供可测量结构的出发点，这些结构将有助于获得更深入的了解。了解精神状况。然而，缺乏从实验测量中得出的可靠、稳健的潜在结构是沿着可以映射到多个分析单元的维度组织精神障碍的关键障碍。我们使用自我报告、行为、生理学和神经回路分析单元来关注 RDoC 提出的正价和负价系统域，并将其应用于从初级保健中招募的焦虑或抑郁个体的临床人群 跨两个地点的诊所，并应用潜在变量分析来导出跨分析单元运行的正价和负价系统的潜在结构。该提案的具体目标是：(1) 招募、评估和分析来自 n=100 名寻求治疗的个体的探索性样本中的自我报告、行为、生理和神经回路分析数据单元。加州大学圣地亚哥分校和加州大学洛杉矶分校的护理诊所。 (2) 使用相同的测量方法在两个地点获得 n=100 名受试者的验证样本，以确定从探索性样本中获得的潜在构建体的再现性和稳健性。 (3) 获得 UCSD 和 UCLA 的 n=50 个人的可靠性样本，该样本将在一个月内重新测试，以确定潜在结构的可靠性。这将是第一次在同一广泛定义的焦虑或抑郁患者样本中研究正价和负价的神经指数。现有的情绪障碍神经过程研究仅限于相对较小的样本量。通过整合两个站点的资源，我们将招募足够大的样本来进行比以往更全面的分析。一旦完成所提出的目标，我们将拥有一组稳健且可靠的维度变量，可以基于潜在变量方法量化正价域和负价域。这些变量捕获临床差异，并将从两个不同的临床部位获得，以提供负价域和正价域的普遍性的经验证据。这些变量随后将用于确定（a）它们是否可以用作个体对药物或行为治疗的反应程度的预测因子； （b）它们可以对专门针对改变正价或负价系统的疗法产生不同的反应，并且（c）它们可以用于随后的焦虑和抑郁的计算和/或神经过程模型，以获得更基本的理解这些个体中发生的病理学。