Addressing Suicide Research Gaps: Understanding Mortality Outcomes (R01 Clinical Trial Not Allowed ) | RFA MH 20 305

FAQs: Addressing Suicide Research Gaps: Understanding Mortality Outcomes (R01 Clinical Trial Not Allowed) (RFA-MH-20-305)

What is the main purpose of this NIH funding opportunity?

The purpose of this funding opportunity is to close key knowledge gaps about suicide mortality outcomes by making better use of data that already exist. The focus is on generating new insights into what predicts suicide death and what factors may change risk across individuals or contexts, using innovative analytic approaches applied to already-collected information.

What type of projects does this FOA support?

This FOA supports research projects that rely on secondary analyses and data integration. Proposed work is expected to leverage and combine existing sources such as prior basic science, clinical, and intervention studies on suicide risk and suicidal behaviors, along with real-world data streams like healthcare records and social media data.

Are clinical trials allowed under this announcement?

No. This opportunity is designated "Clinical Trial Not Allowed." Applications should not propose prospective interventional studies that assign participants to conditions to test health outcomes. The work should instead center on secondary data analysis, harmonization of variables across datasets, linkage of datasets (where permitted and feasible), and advanced modeling using existing data.

What research outcomes are emphasized?

The central emphasis is on suicide mortality outcomes, specifically improving understanding of factors associated with suicide death and how risk may vary across people or contexts.

What does the FOA mean by "making better use of data that already exist"?

It means the project should primarily reanalyze, integrate, or link existing datasets rather than collect new prospective interventional data. Examples of existing sources mentioned include prior research studies (basic science, clinical, and intervention studies) and real-world data streams such as healthcare records and social media data.

What kinds of data sources are encouraged?

The FOA encourages combining and leveraging existing sources such as prior basic science, clinical, and intervention studies related to suicide risk and suicidal behaviors, as well as real-world data streams like healthcare records and social media data. Projects that responsibly connect different data types (for example, clinical histories with digital traces or administrative outcomes) are particularly aligned with the intent.

What is meant by secondary analysis in this context?

Secondary analysis refers to analyzing data that have already been collected, potentially for other studies or operational purposes. Under this FOA, secondary analysis may include reexamining existing datasets, harmonizing variables across datasets, integrating multiple datasets, linking datasets (where feasible and permitted), and using advanced modeling to understand pathways to suicide mortality.

What is meant by data integration or data linkage?

Data integration involves combining information from multiple existing sources to answer questions that single datasets cannot address alone. Data linkage refers to connecting records across different datasets (where permitted and feasible) to relate different types of information, such as linking clinical histories with administrative health outcomes or other data streams.

What scientific themes are prioritized in the research questions?

The FOA prioritizes identifying predictors and moderators of suicide risk, particularly those tied to mortality outcomes. It is geared toward understanding what predicts suicide death and what factors may change risk relationships across individuals or contexts.

What is a "predictor" of suicide risk in this FOA?

Predictors are measurable variables that may signal heightened suicide risk or relate to suicide mortality outcomes. The FOA notes predictors can include biological variables (such as biomarkers or physiological indicators), experiential and environmental factors (such as trauma exposure, life stressors, or social determinants), and other measurable characteristics associated with risk.

What is a "moderator" and why does it matter here?

Moderators are factors that influence the strength or direction of relationships between predictors and outcomes. In this FOA, moderators help explain why certain predictors may matter more for some people than others, or under certain circumstances, improving understanding of how risk operates across individuals or contexts.

What are "dimensional variables" and why are they encouraged?

Dimensional variables generally refer to measuring traits, symptoms, or behaviors along continuous scales rather than simple yes/no categories. The FOA explicitly encourages dimensional variables to support more nuanced modeling of suicide risk and mortality outcomes.

What are "multi-level analyses" in this opportunity?

Multi-level analyses can involve integrating information across layers such as biology, behavior, clinical presentation, social context, and system-level factors like healthcare access and service use. The FOA encourages these approaches to better capture the complexity of suicide mortality risk.

What grant mechanism is used for this program?

This program uses the NIH R01 mechanism, intended to support substantial, well-scoped research projects with strong scientific rigor, clear hypotheses, and robust analytic plans.

What types of organizations are eligible to apply?

Eligibility is broad. Eligible applicants include state, county, city, township, and special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; federally recognized Native American tribal governments; tribal organizations that are not federally recognized tribal governments; public housing authorities and Indian housing authorities; nonprofits with or without 501(c)(3) status (outside higher education); for-profit organizations (other than small businesses); and small businesses, among others.

Are specific institution types explicitly highlighted as eligible?

Yes. The FOA highlights additional eligible categories including Alaska Native and Native Hawaiian Serving Institutions; Asian American Native American Pacific Islander Serving Institutions (AANAPISIs); Hispanic-serving Institutions; Historically Black Colleges and Universities (HBCUs); Tribally Controlled Colleges and Universities (TCCUs); faith-based or community-based organizations; eligible federal agencies; regional organizations; U.S. territories or possessions; and non-U.S. entities (foreign organizations).

Can non-U.S. (foreign) organizations apply?

Yes. The eligibility list includes non-U.S. entities (foreign organizations), indicating that foreign organizations may apply under this announcement.

What is the funding instrument and activity category?

The listing describes the opportunity as discretionary and using a grant funding instrument under the health activity category.

What is the CFDA number associated with this opportunity?

The CFDA number provided is 93.242.

What is the listed application closing date in the provided information?

The original closing date listed is February 10, 2020.

What is the award ceiling shown in the provided listing?

The award ceiling listed in the provided information is $500,000.

Does the provided information state how many awards are expected?

No. The provided text states that the number of expected awards is not specified in the excerpt.

What kinds of analytic approaches are consistent with the intent of this FOA?

Approaches consistent with the intent include secondary analyses, harmonization of variables across datasets, dataset linkage (where permitted and feasible), and advanced modeling aimed at clarifying predictors, moderators, and pathways to suicide mortality outcomes using already-collected data.

How does this FOA aim to accelerate progress in suicide mortality research?

It aims to accelerate progress by encouraging researchers to combine and reanalyze existing datasets in sophisticated ways to uncover actionable, multi-dimensional indicators of suicide mortality risk, with the goal of improving understanding that can inform prevention strategies and future research directions without conducting new clinical trials under this mechanism.