# Swift Outpatient Alternatives for Rapid Stabilization (SOARS)

> **NIH NIH P50** · UNIVERSITY OF WASHINGTON · 2024 · $775,993

## Abstract

Suicide is a leading cause of death for youth and prevention efforts embedded in healthcare systems have
promise for reducing this substantial public health problem. There is a significant gap between the expectations
of a suicide care pathway and existing capacity and could be improved with optimized intervention packages
that address key stakeholders- youth, patient, behavioral health providers, and outpatient medical providers-
needs. Building upon promising pilot results, this project seeks to evaluate components of the Swift Outpatient
Alternative for Rapid Stabilization (SOARS) intervention to build the strongest combination to reduce youth
suicidal thoughts and behaviors (STB; Aim 1). We will test the impact patient characteristics (Aim 2) and if
SOARS components function through their putative mechanisms. The optimized treatment package will be
refined through co-design with providers to augment its acceptability and usability (Aim 4). Results will be
used to create an optimized intervention package to accelerate the pace of adoption by healthcare systems
and reduction of youth STBs. This will result in a youth suicide care intervention package optimized for
ecological validity, effectiveness and efficiency, and ready for evaluation in a hybrid implementation trial.

## Key facts

- **NIH application ID:** 10791825
- **Project number:** 5P50MH129708-02
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Molly Adrian
- **Activity code:** P50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $775,993
- **Award type:** 5
- **Project period:** 2023-02-17 → 2028-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10791825

## Citation

> US National Institutes of Health, RePORTER application 10791825, Swift Outpatient Alternatives for Rapid Stabilization (SOARS) (5P50MH129708-02). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10791825. Licensed CC0.

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