This grant aims to study and improve family navigation models in emergency departments for non-urgent mental health issues.
Funder: National Institutes of Health
Due Dates: June 16, 2025 (New) | July 16, 2025 (Renewal/Resubmission/Revision) | October 16, 2025 (New) | November 16, 2025 (Renewal/Resubmission/Revision) | February 16, 2026 (New) | March 16, 2026 (Renewal/Resubmission/Revision) | June 16, 2026 (New) | July 16, 2026 (Renewal/Resubmission/Revision) | October 16, 2026 (New) | November 16, 2026 (Renewal/Resubmission/Revision) | February 16, 2027 (New) | March 16, 2027 (Renewal/Resubmission/Revision) | June 16, 2027 (New) | July 16, 2027 (Renewal/Resubmission/Revision) | October 16, 2027 (New) | November 16, 2027 (Renewal/Resubmission/Revision)
Funding Amounts: Up to $225,000 direct costs/year; max $450,000 direct costs over 3 years (R34 mechanism).
Summary: Supports pilot research on family navigation models to divert non-urgent mental health cases from emergency departments and improve engagement with mental health services.
Key Information: Clinical trial required; only U.S.-based organizations and components are eligible; companion R01 available for larger-scale studies.
This opportunity, offered by the National Institute of Mental Health (NIMH) at NIH, funds pilot studies to test and optimize family navigation models that divert non-urgent mental health cases from emergency departments (EDs) to more appropriate care. The goal is to generate evidence on the effectiveness, implementation, and scalability of these models, which are designed to:
Projects should focus on models delivered by mental health professionals, allied health providers, or trained lay providers (e.g., peers, community health workers). The emphasis is on pilot testing established or newly developed navigation models, with the intent to inform future, fully powered studies (for which a companion R01 is available).
Research should address not only clinical outcomes but also service utilization, family engagement, and reduction of disparities in access and outcomes. Innovative designs (e.g., adaptive, factorial, or optimization trials) are encouraged, and collaborations with practice partners are expected to enhance real-world relevance and scalability.