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A primer on using secondary data for mental health research, including: what secondary data is, the value these sources offer, and misconceptions about their utility.

Secondary data is an extremely valuable tool for mental health research; however choosing a secondary data source can be a complicated task. This visual guide summarizes the major domains of 21 valuable data sources for mental health research to help you get started.

This webinar walks you through how to get grant funding without collecting a single data point. Briana Mezuk, Ph.D., Professor of Epidemiology, and Data & Design Core Faculty Co-Lead, and Eric Simon, Ph.D., Senior Technical Writer at the Depression Center, discuss strategies for writing compelling and successful grant proposals using secondary data, including novel approaches to data analysis, writing a budget and working with a grant writer.

This article provides a step-by-step guide to navigating University of Michigan's IRB when using de-identified secondary data sources.

This article offers a step-by-step guide to navigating the IRB for secondary data projects that use identifying information.

In this presentation, Matt Davis, Ph.D., Associate Professor in the U-M School of Nursing provides an overview of the strengths and drawbacks of several types of secondary data sources (including surveys, electronic health records and medical claims data), points to valuable data options for mental health research, and offers several practical examples to help you get started.

The University of Michigan's DataDirect tool offers U-M researchers customized, user-friendly access to Michigan Medicine clinical data. With options for cohort discovery, recruitment, and de-identified data output, DataDirect is a highly valuable resource for mental health research. In this article, we will walk through an example project showcasing how DataDirect can be used for clinical research at U-M.