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Addressing Suicide Research Gaps: Aggregating Existing Data Sets for Secondary Analyses


Jane Pearson, Ph.D.
Division of Services and Intervention Research


The purpose of this initiative is to leverage prior basic, clinical and intervention research on suicide risk and behaviors by encouraging the integration of existing data sets for novel secondary analyses to identify potential biological, experiential and other predictors and moderators of suicide risk. The utilization of dimensional variables and inclusion of multiple levels of analysis would be encouraged. A secondary goal of this initiative is to generate pilot data for larger research studies on suicide-related behaviors that can begin to adopt, or minimally inform, a Research Domain Criteria (RDoC) approach. These efforts would also address gaps identified in the 2014 Prioritized Research Agenda for Suicide Prevention.


Suicide is the tenth leading cause of death in the United States, and second leading cause of death in 10-34 year olds. Understanding the mechanisms and trajectories of this behavior has the potential to influence novel prevention and intervention development. This work can be expedited by leveraging federal and private investments to maximize the use of existing data.

Suicide, while devastating, is a low base rate occurrence. Its frequent precursors, particularly suicidal ideation and self-injury, often occur in the context of mental and substance use disorders. The transdiagnostic phenotypes of suicide death, attempts, and ideation vary across the lifespan and by sex. Given this heterogeneity, there are likely several combinations of biological measures that confer risk for each type/level of suicidality (i.e., suicide ideation, attempt and death). Using a multifactorial and dimensional approach, it may be possible to parcel suicide behavior into component parts and identify sets of variables that interact with each other to confer elevated risk, or responsiveness to particular interventions. It is expected that the variability of biological factors involved in suicide risk might parallel the variability in individuals that suffer suicidal thoughts and behaviors, and identification of these measures would facilitate the identification of targets for novel intervention development.

This initiative will provide an opportunity for investigators to integrate and analyze datasets in a cost-efficient manner, to yield novel findings, identify key scientific gaps, and inform future research investments. Data from these projects will shed light on how the measures of suicidal behavior in current studies might link to, or inform NIMH’s Research Domain Criteria (RDoC) project.

Questions that could be answered using these combined datasets include 1) the identification of composite suicide risk and protective factors, 2) moderators and mediators of risk factors for suicide risk factor research, and/or 3) identification of special considerations for subgroups of populations (e.g., age, gender, cultural and sexual orientation differences).

This initiative will support research in the following areas:

  • Integration and analyses of datasets including, but not limited to
    • studies designed to specifically answer questions about suicide
    • studies designed to answer questions about mental health or substance use (i.e., not focusing on suicide measures specifically, but might have collected the relevant suicide measures)
    • studies of large epidemiological samples
    • studies sponsored by industry, government, and private foundations.
  • Aggregation of datasets that permit analysis of multiple levels of analysis for a common construct.
  • Sharing of the newly combined and analyzed dataset for broad research use would be encouraged when appropriate.

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