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.

项目总结