Publication Date:
Author(s): Sy-Miin Chow, I Nahum-Shani, Justin Baker, Donna Spruijt-Metz, Nicholas Allen, Ryan Auerbach, Genevieve Dunton, Naomi Friedman, Stephen Intille, Predrag Klasnja, Benjamin Marlin, Matthew Nock, Scott Rauch, Misha Pavel, Scott Vrieze, David Wetter, Evan Kleiman, Timothy R. Brick, Heather Perry, Dana Wolff-Hughes, ILHBN
Publisher: Springer Publishing Company
Publication Type: Journal Article
Journal Title: Translational Behavioral Medicine
Volume: 13
Issue: 1
Page Range: 7-16
Abstract:

The ILHBN is funded by the National Institutes of Health to collaboratively study the interactive dynamics of behavior, health, and the environment using Intensive Longitudinal Data (ILD) to (a) understand and intervene on behavior and health and (b) develop new analytic methods to innovate behavioral theories and interventions. The heterogenous study designs, populations, and measurement protocols adopted by the seven studies within the ILHBN created practical challenges, but also unprecedented opportunities to capitalize on data harmonization to provide comparable views of data from different studies, enhance the quality and utility of expensive and hard-won ILD, and amplify scientific yield. The purpose of this article is to provide a brief report of the challenges, opportunities, and solutions from some of the ILHBN's cross-study data harmonization efforts. We review the process through which harmonization challenges and opportunities motivated the development of tools and collection of metadata within the ILHBN. A variety of strategies have been adopted within the ILHBN to facilitate harmonization of ecological momentary assessment, location, accelerometer, and participant engagement data while preserving theory-driven heterogeneity and data privacy considerations. Several tools have been developed by the ILHBN to resolve challenges in integrating ILD across multiple data streams and time scales both within and across studies. Harmonization of distinct longitudinal measures, measurement tools, and sampling rates across studies is challenging, but also opens up new opportunities to address cross-cutting scientific themes of interest.