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试图开发这样的结构：(a)跨分析单元连接，(b)适用于已建立的诊断标准，(c)是提供可测量结构的出发点，这将有助于更深入地了解精神疾病。然而，缺乏可靠的，稳健的潜在结构，从实验措施是组织沿维度精神障碍的一个关键障碍，可以映射到多个分析单位。我们关注RDoC提出的正效价和负效价系统域，使用自我报告、行为、生理和神经回路分析单元测量，并将其应用于从初级保健招募的焦虑或抑郁个体的临床人群