Harnessing Network Science to Personalize Scalable Interventions for Adolescent Depression

利用网络科学对青少年抑郁症进行个性化的可扩展干预措施

• 批准号: 10225538
• 负责人: Jessica Lee Schleider
• 金额: $ 40.28万
• 依托单位: STATE UNIVERSITY NEW YORK STONY BROOK
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-16 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10225538
• 关键词: Achievement; Address; Adolescent; Age; Anhedonia; Anxiety; Area; Behavioral; Behavioral Symptoms; Belief; Clinical; Clinical Psychology; Cognitive; Complex; Data; Data Collection; Department chair; Development; Diagnosis; Disease; Economic Burden; Educational process of instructing; Feeling hopeless; Funding; Goals; Growth; Guidelines; Health Services Accessibility; Heterogeneity; Individual; Infrastructure; Intervention; Intervention Studies; Intervention Trial; Leadership; Link; Major Depressive Disorder; Mental Depression; Mental disorders; Mentors; Mentorship; Meta-Analysis; Methods; National Research Service Awards; Nature; Neurobehavioral Manifestations; Occupations; Online Systems; Paper; Parents; Pathway Analysis; Physiological; Positioning Attribute; Psychological Theory; Psychology; Psychopathology; Publishing; Randomized; Recovery; Research; Research Personnel; Research Project Grants; Sampling; Schools; Science; Secure; Services; Statistical Methods; Stress; Structure; Support System; Symptoms; Techniques; Testing; Time; Training; Universities; Withdrawal; Work; Youth; base; career; child depression; college; depressive symptoms; design; disability; doctoral student; evidence base; experience; faculty mentor; follow-up; improved; innovation; medical schools; multilevel analysis; novel; outcome prediction; pleasure; posters; predicting response; professor; programs; prospective; randomized trial; response; senior faculty; single episode major depressive disorder; social; stem; teacher; tenure track; therapy design; tool; trait; vector

Project Summary/Abstract Major depression (MD) is the leading cause of disability in youth, with a global economic burden of >$210 billion annually. However, up to 70% of youth with MD do not receive services. Even among those who do access treatment, 30-65% fail to respond, demonstrating a need for more potent, accessible interventions. A challenge underlying limited treatment potency is MD's heterogeneity: An MD diagnosis reflects >1400 symptom combinations, creating a need for treatments matched to personal clinical need. Separately, low treatment accessibility stems from the structure of existing interventions. Most span many weeks and are designed for delivery by highly trained clinicians , making them difficult to scale. This proposal aims to address the need for accessible, potent youth MD interventions by integrating methods and findings from previously separate areas: single-session intervention (SSI) research and network science. In a meta-analysis of 50 randomized trials, the investigator has found that SSIs can reduce diverse youth psychiatric problems, including MD. The investigator also found that a web-based SSI teaching growth mindset (the belief that personal traits are malleable) reduced depression and anxiety in high-symptom youth across 9 months. Thus, well-targeted SSIs can yield lasting benefits—but given MD's heterogeneity, there is a need for tools that can match youth to SSIs optimized for personal symptom structures. The proposed project harnesses computational advances from the network approach to psychopathology, which views psychiatric disorders as causal interactions between symptoms, to evaluate such a tool. The first goal is to establish a new method of characterizing MD symptom structures; the second is to test parameters from these structures as predictors of response to two SSIs targeting distinct MD features (behavioral vs. cognitive symptoms). Specifically, Aim 1 is to establish guidelines for computing personalized symptom networks using experience sampling method (ESM) data from youth with MD collected 7x/day for 3 weeks (N=50, ages 11-16; 147 time-points each). This will include a comparison of two leading approaches for computing network parameters, such as outward centrality (the degree to which a symptom prospectively predicts other symptoms). Aim 2 is to test network parameters as SSI outcome predictors among youth with MD (N=180). Youth will be randomized to a behavioral activation (BA) SSI (adapted from evidence-based BA SSIs); the mindset SSI noted above; or a control SSI. Network parameters will be tested as predictors of SSI response. For instance, youth with stronger centrality on a behavioral symptom (e.g. withdrawal from pleasurable activities) may respond more favorably to the BA SSI, and youth with stronger centrality on a cognitive symptom (e.g. hopelessness) to the mindset SSI. Results may identify a novel means of matching youth to targeted MD SSIs by personal need. The project will also include the first RCT comparing two youth MD SSIs, with the longest follow-up of any SSI trial to date (2 years), gauging their relative promise to reduce youth MD.

项目摘要/摘要 严重抑郁症(MD)是导致青年残疾的主要原因，全球经济负担达210美元 每年10亿美元。然而，高达70%的患有MD的青年没有得到服务。即使是在那些这样做的人中 在接近治疗的情况下，30%-65%没有反应，这表明需要更有力、更容易接近的干预措施。一个 治疗能力有限的挑战是MD的异质性：MD的诊断反映了&gt；1400； 症状组合，创造了与个人临床需求相匹配的治疗需求。单独，低 治疗可及性源于现有干预措施的结构。大多数跨越数周，并且是 专为训练有素的临床医生提供而设计，使其难以扩展。这项提案旨在解决 通过整合以前的方法和结果，需要可获得的、有效的青年MD干预措施 不同领域：单次干预(SSI)研究和网络科学。在一项关于50人的荟萃分析中 通过随机试验，研究人员发现SSI可以减少不同的青少年精神问题， 包括医学博士。研究人员还发现，基于网络的SSI教学成长心态(相信 个人特征是可塑性的)在9个月的时间里，高症状青年的抑郁和焦虑程度有所降低。 因此，目标明确的SSI可以产生持久的好处--但考虑到MD的异构性，需要工具 这可以将年轻人与针对个人症状结构进行优化的SSI相匹配。拟议中的项目利用 从网络方法到精神病理学的计算进展，它将精神障碍视为 症状之间的因果交互作用，来评估这样一个工具。第一个目标是建立一种新的方法 表征MD症状结构；第二是测试来自这些结构的参数作为预测 对两个针对不同MD特征的SSI的反应(行为症状与认知症状)。具体地说，目标1是 建立使用经验抽样方法计算个性化症状网络的指南 青年MD患者(ESM)每天收集7次，共3周(N=50，年龄11-16岁；每个时间点147个时间点)。这 将比较两种主要的计算网络参数的方法，例如向外 中心性(一种症状预测其他症状的程度)。目标2是测试网络 作为青年MD(N=180)SSI结果预测因素的参数。青年将被随机分配到 行为激活(BA)SSI(改编自循证BA SSI)；上述心态SSI；或 控制SSI。网络参数将作为SSI响应的预测因子进行测试。例如，年轻人有更强的 行为症状的中心性(例如，从愉快的活动中撤出)可能对 BA SSI，以及在认知症状(如绝望)上具有较强中心性的年轻人对心态SSI的影响。 结果可能确定一种根据个人需求将年轻人与目标MD SSI相匹配的新方法。该项目将 还包括对两个青年MD SSI进行的第一次随机对照试验，是迄今为止SSI试验中随访时间最长的(2 几年)，评估他们在减少青年MD方面的相对承诺。