Consortium for Longitudinal behavioral and Social Science data Integration and Coordination (CLASSIC) - PROJECT SUMMARY/ABSTRACT NIA has a rich portfolio of “deeply phenotyped” small- to mid-sized longitudinal studies which are an underutilized resource of psychosocial, behavioral, and biomarker data. The long-term goal is to leverage these single studies through collaboration and coordination in order to address replication, extend findings to new contexts, and identify important factors that moderate healthspan and lifespan. The overall objectives of this application are to address critical human and technological barriers to collaboration and coordination in these deeply phenotyped studies. The central hypothesis is that these barriers relate to meta-data sharing (inputs) and multi-study analysis (outputs). The rationale for this project is that addressing “input” barriers such as PI reluctance and study team burden of meta-data sharing and “output” barriers such as difficulty accessing data and lack of training in multi-study analysis will lower the burden for successful coordination across studies, address broader replication questions, and empower smaller studies to fuel discoveries beyond their initially funded aims. These objectives will be pursued by four specific aims: development of both technological infrastructure (i.e., central distribution hub with publicly available meta-data catalog and collaboration/coordination resources [Aim 1]) and human infrastructure (i.e., incentivizing study PIs and engaging early career researchers [Aim 2], methodological support through workshops [Aim 3.1] and consulting [Aim 3.2], and financial support [Aim 4] for multi-study analysis). The proposed research is innovative, in the applicants’ opinion, because it develops tools and provides resources that reduce barriers for both PIs (e.g., dashboard for tracking and attribution, incentivizing meta-data sharing) and early career analysts (e.g., cross-study search and comparison tools, streamlined data requests). The proposed project is significant because the resulting collaborations and multi-study analyses will systematically test whether findings hold when tested in a diversity of sample characteristics, conditions, and across time. Ultimately, this will provide more rigorous tests of aging theories and their boundary conditions, which will improve understanding of aging and health.
