# Low-burden Adaptive Mobile Interventions for Mood and Suicide Risk

> **NIH NIH K23** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2022 · $172,542

## Abstract

Project Summary/Abstract
Depression is the #1 cause of disease-related disability worldwide and prevalence rates for depression and
suicide have increased significantly in the United States over the past 25 years. Young adults, including
college students, have especially high rates of depression, yet a majority of individuals with clinically significant
symptoms do not seek formal treatment. Previous work by the Candidate (Dr. Adam Horwitz) suggests that
college students at elevated risk for suicide may decline formal treatment due to barriers such as lack of time,
low perceived need for treatment, or limited access to services. Mobile health technologies offer promising new
opportunities to overcome these barriers and improve outcomes. Further, the use of mobile technologies in
combination with wearable sensors allow for the gathering of real-time subjective and objective data, and an
ability to respond to mood changes directly with an intervention at the time it is needed. This K23 Mentored
Career Development Award application proposes a program of focused research and training to facilitate the
Candidate’s transition to an independent career in patient-oriented research with a specialization in low-burden
adaptive mobile preventative interventions for mood and suicide risk. The specific research aims are to: 1)
using a participatory action approach, identify the target population preferences, barriers to engagement, and
relevant domains for ecological momentary assessments and personalized feedback messages; and 2)
conduct a pilot feasibility micro-randomized trial of a mobile health personalized feedback intervention with
college students (N = 60) at risk for depressive episodes. The Candidate will pursue these research aims by
obtaining specific training to gain expertise in: 1) participatory action research methods for intervention
development; 2) mHealth, micro-randomized trials, and adaptive mobile intervention development and
evaluation; and 3) advanced statistical analysis for mobile, sensor, and ecological momentary assessment
data. These training objectives will be met through close mentorship from experts in these content areas,
specialized trainings and didactics, and applied research experiences. Findings from the outlined
investigations will provide invaluable pilot data regarding acceptability, feasibility, perceived helpfulness, and
hypothesized mechanisms of change, as well as potential features and thresholds that can be used as
intervention triggers in an adaptive design. Together, these findings will directly inform an NIH R01 application
at the conclusion of the study period seeking to evaluate a just-in-time adaptive intervention designed to
optimize the delivery of personalized feedback messages, and provide additional coping tips, tools, and/or
resources when indicated. In summary, the training and research opportunities outlined in this proposal will
provide the necessary skills for a promising Candidate to launch a car...

## Key facts

- **NIH application ID:** 10569278
- **Project number:** 1K23MH131761-01
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Adam Gabriel Horwitz
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $172,542
- **Award type:** 1
- **Project period:** 2022-09-07 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10569278

## Citation

> US National Institutes of Health, RePORTER application 10569278, Low-burden Adaptive Mobile Interventions for Mood and Suicide Risk (1K23MH131761-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10569278. Licensed CC0.

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