This is a competing continuation R01 proposal to support new biostatistical methodologic development and application of these new methods to individual level data on 11,939 adolescents in 42 existing or ongoing prevention and treatment intervention randomized trials aimed at depression. The central goal of our proposed work is the development and application of novel quantitative methods necessary to integrate findings across trials on preventing and treating depression in adolescence and their relevance for building and testing the next generation of comprehensive intervention strategies. Built on the past 22 years of NIH funding for the Prevention Science and Methodology Group (PSMG), this collaborative synthesis project will bring together expert methodologists and intervention scientists with the guidance of an external scientific advisory committee. The 42 prevention (n=24) and treatment (n=18) intervention trials we will use in this proposal focus on the child (e.g., cognitive behavioral, interpersonal therapy), parent/family (e.g., parent training), and/or antidepressants, each class known to have beneficial impact on adolescent depression. Our work will focus on examining the shared and unique mediators and moderators over these trials. Building on our data sharing agreements, we will conduct new cross-trial analyses of moderator effects involving demographic characteristics, symptomatology, and adversity across different clusters of prevention or treatment interventions. We will also examine the shared and unique mediational pathways of these interventions involving adherence/compliance, cognitive processes, and family processes. We propose new methodologic approaches to distinguish these shared and unique mediators and mediators using individual data across multiple trials. To minimize biases and maximize analytic comparability across trials, these new methods will account for individual and trial level differences in population/person level risk and protective factors, differences in the interventions including exposure, fidelity, or adherence, and differences in trial design including follow-up period, and assessment instruments. These new methodologic approaches are necessary because nearly all randomized trials are severely underpowered to address mediation or moderation within their own studies, and the statistical methods now available for data synthesis (e.g., meta-analysis), are not adequate for complex multi-trial analyses.
In Aim 1 we develop new biostatistical multilevel, longitudinal models to synthesize cross-trial analyses on mediation and moderation across related randomized trials.
In Aim 2 we apply these methods to trials on depression interventions for adolescents.
In Aim 3 we identify key gaps in our understanding of intervention efficacy to be addressed in the next generation of intervention trials, and develop scientific guidelines.

Public Health Relevance

Depression is the single leading cause of disability, and from a developmental perspective, its prevention or treatment during adolescence can provide lifelong benefits. Despite the existence of generally efficacious prevention and treatment interventions for depression, we have yet to assimilate this knowledge into personalized strategies that meet the public health needs of diverse populations to meet their acute as well as longer term risk for recurrence. This work will specify who can benefit from different intervention options across time and provide the knowledge to build effective personalized as well as contextualized interventions to address depression in adolescence.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH040859-24
Application #
8288163
Study Section
Special Emphasis Panel (ZRG1-RPHB-A (03))
Program Officer
Goldstein, Amy B
Project Start
1986-02-01
Project End
2015-03-31
Budget Start
2012-04-01
Budget End
2013-03-31
Support Year
24
Fiscal Year
2012
Total Cost
$603,660
Indirect Cost
$168,967
Name
University of Miami School of Medicine
Department
Public Health & Prev Medicine
Type
Schools of Medicine
DUNS #
052780918
City
Coral Gables
State
FL
Country
United States
Zip Code
33146
MacKinnon, David P; Valente, Matthew J; Wurpts, Ingrid C (2018) Benchmark validation of statistical models: Application to mediation analysis of imagery and memory. Psychol Methods 23:654-671
Mio?evi?, Milica; O'Rourke, Holly P; MacKinnon, David P et al. (2018) Statistical properties of four effect-size measures for mediation models. Behav Res Methods 50:285-301
Siddique, Juned; de Chavez, Peter J; Howe, George et al. (2018) Limitations in Using Multiple Imputation to Harmonize Individual Participant Data for Meta-Analysis. Prev Sci 19:95-108
Brincks, Ahnalee; Perrino, Tatiana; Howe, George et al. (2018) Preventing Youth Internalizing Symptoms Through the Familias Unidas Intervention: Examining Variation in Response. Prev Sci 19:49-59
Howe, George W; Pantin, Hilda; Perrino, Tatiana (2018) Programs for Preventing Depression in Adolescence: Who Benefits and Who Does Not? An Introduction to the Supplemental Issue. Prev Sci 19:1-5
Brown, C Hendricks; Brincks, Ahnalee; Huang, Shi et al. (2018) Two-Year Impact of Prevention Programs on Adolescent Depression: an Integrative Data Analysis Approach. Prev Sci 19:74-94
Brincks, Ahnalee; Montag, Samantha; Howe, George W et al. (2018) Addressing Methodologic Challenges and Minimizing Threats to Validity in Synthesizing Findings from Individual-Level Data Across Longitudinal Randomized Trials. Prev Sci 19:60-73
Smith, Matthew J; Smith, Justin D; Fleming, Michael F et al. (2017) Mechanism of Action for Obtaining Job Offers With Virtual Reality Job Interview Training. Psychiatr Serv 68:747-750
Dagne, Getachew A; Brown, C Hendricks; Howe, George et al. (2016) Testing moderation in network meta-analysis with individual participant data. Stat Med 35:2485-502
Perrino, Tatiana; Pantin, Hilda; Huang, Shi et al. (2016) Reducing the Risk of Internalizing Symptoms among High-risk Hispanic Youth through a Family Intervention: A Randomized Controlled Trial. Fam Process 55:91-106

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