Netting prevention intervention butterfly effects: An integrative data analysis investigating the long-term and cross-over effects of randomized,school-based prevention programs on adult mental health

网络预防干预蝴蝶效应：综合数据分析，调查随机、基于学校​​的预防计划对成人心理健康的长期和交叉影响

• 批准号: 9924013
• 负责人: Rashelle Jean Musci
• 金额: $ 78.96万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-01 至 2022-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9924013
• 关键词: Accounting; Adult; Aggressive behavior; Anxiety; Attention; Behavior; Behavior Therapy; Butterflies; Cessation of life; Childhood; Complex; Data; Data Aggregation; Data Analyses; Data Linkages; Data Set; Diagnosis; Disease; Distal; Early Intervention; Educational workshop; Ethnic group; Family; Feeling suicidal; Goals; Heterogeneity; Intervention; Intervention Trial; Link; Mediation; Mediator of activation protein; Mental Depression; Mental Health; Mental disorders; Methodology; Modeling; National Institute of Mental Health; Nature; Outcome; Participant; Pathway interactions; Prevention; Prevention program; Prevention trial; Preventive Intervention; Primary Schools; Principal Investigator; Process; Psychotic Disorders; Randomized; Randomized Controlled Trials; Risk Factors; Schools; Science; Sex Orientation; Social support; Structure; Students; Suicide prevention; Symptoms; United States National Institutes of Health; Youth; alcohol misuse; anxiety symptoms; base; data archive; data harmonization; depressive symptoms; deviant; drug misuse; early childhood; elementary school; emerging adult; follow-up; interest; knowledge base; longitudinal analysis; member; multilevel analysis; novel; peer; prevent; programs; psychotic symptoms; racial and ethnic; response; sex; social integration; suicidal behavior; teacher; treatment effect; universal prevention

Project Summary The goal of this application, submitted in response to RFA-MH-20-110, “Secondary Data Analysis to Examine Long-Term and/or Potential Cross-Over Effects of Prevention Interventions: What are the Benefits for Preventing Mental Health Disorders?,” is to leverage data from existing prevention intervention trials with longitudinal follow-up to answer key questions about the long-term impacts of prevention intervention trials. Aggregating these data sets will allow for novel secondary data analyses which will enhance our understanding of intervention impacts on 1) suicidal behaviors, 2) depression and anxiety symtoms and diagnoses, and 3) psychosis symptoms. There is a pressing need to link and harmonize data from primary school universal prevention trials with longitudinal follow-up including suicide (ideation, attempt, and death) and mental health diagnoses (including depression, anxiety, and psychosis) to understand how changing trajectories of key risk factors for these outcomes (social support, deviant peer affiliation) prevents the occurrence of the negative outcomes described above. Many of the existing prevention trials are not large enough to find an impact on rare outcomes, and even less powered to explore treatment effect heterogeneity. Our objective is to link and harmonize data from six randomized controlled trials with preventive interventions focused on reducing disruptive and aggressive behavior in early childhood to understand the long-term impacts of universal prevention programs on key outcomes in early adulthood including suicidal behaviors, depression and anxiety symtoms and diagnoses, and psychosis symptoms. Data will be utilized from the Fast Track Project (Bierman et al., 2004), the Good Behavior Game trials (Kellam et al., 2008; Ialongo et al., 1999; Ialongo et al., 2019), the SAFEChildren Trial (Tolan et al., 2004), and the Linking the Interests of Families and Teachers Study (LIFT; Eddy et al., 2000; Reid et al., 1999). Our hypothesis is that with a harmonized dataset, there will be sufficient power to identify prevention program impacts into adulthood and as such we will find impacts of these programs beyond what was originally targeted. Our rationale is that with at least 10,000 participants across all studies, linkage and harmonizing data will allow for more complex, multifactorial, multi-level analyses to explore intervention impact on suicidal behaviors, depression and anxiety symtoms and diagnoses, and psychosis symptoms as well as potential mediators and moderators of impact.

项目摘要 本申请的目的是响应RFA-MH-20-110“二级数据分析， 检查预防干预措施的长期和/或潜在交叉效应： 预防精神疾病的好处？”是利用现有预防措施中的数据 干预试验与纵向随访，以回答有关长期影响的关键问题， 预防干预试验。汇总这些数据集将允许进行新的二次数据分析， 将加强我们对干预影响的理解1）自杀行为，2）抑郁和焦虑 症状与诊断; 3）精神病症状。目前迫切需要将数据从 小学普遍预防试验与纵向随访，包括自杀（意念，企图， 死亡）和心理健康诊断（包括抑郁症，焦虑症和精神病），以了解如何改变 这些结果的关键风险因素的轨迹（社会支持，越轨的同伴关系）阻止了 出现上述负面结果。许多现有的预防试验规模并不大 足以发现对罕见结果的影响，甚至更不足以探索治疗效果异质性。 我们的目标是将六项随机对照试验的数据与预防性试验联系起来并协调一致 干预措施的重点是减少儿童早期的破坏性和攻击性行为， 普遍预防方案对成年早期关键结果的长期影响，包括 自杀行为、抑郁和焦虑症状和诊断以及精神病症状。数据将 可以从Fast Track Project（Bierman等人，2004）、良好行为游戏试验（Kellam等人， 2008; Ialongo等人，1999; Ialongo等人，2019），SAFE儿童试验（Tolan等人，2004年），以及 家庭和教师的利益研究（LIFT; Eddy等人，2000年; Reid等人，1999年）。我们的假设是 一个统一的数据集，将有足够的力量来确定预防计划对成年的影响， 因此，我们会发现这些方案的影响超出了最初的目标。我们的理由是， 所有研究至少有10 000名参与者，联系和协调数据将允许更复杂， 多因素、多水平分析，探讨干预对自杀行为、抑郁和 焦虑症状和诊断，精神病症状以及潜在的介质， 影响的调节器。