# Continual Optimization and Personalization of Just-in-Time Adaptive Interventions for SUD  Prevention, Treatment, and Recovery

> **NIH NIH P50** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2021 · $510,036

## Abstract

PROJECT SUMMARY: PROJECT 3
In the modern, post-pandemic world, digital technology is becoming an increasingly important vehicle for the
delivery of substance use disorder (SUD) and HIV prevention, treatment, and recovery services. The long-term
goal of the proposed project is to enable digital health technology to deliver intervention services with
unprecedented effectiveness and sustainability. We propose to integrate ideas from behavioral science and
artificial intelligence to develop methodology for (1) continual optimization of just-in-time adaptive digital health
interventions in response to societal changes and evolving population treatment needs and (2) personalized
just-in-time adaptive digital health interventions to each individual's evolving treatment needs. This will enable
a second generation of just-in-time adaptive digital health interventions with enhanced and highly sustainable
effectiveness. To achieve this long-term goal, we will: (Aim 1) Promote sustainable intervention effectiveness
and engagement by integrating approaches from artificial intelligence — namely reinforcement learning — to
develop algorithms that continually optimize mobile health interventions over time; (Aim 2) Meet differential
individual needs by generalizing Aim 1 algorithms to construct and continually optimize person-specific mobile
health interventions; (Aim 3) Test, evaluate, and refine the algorithms developed in Aims 1 and 2 in extensive
simulations; and (Aim 4) Disseminate the developed algorithms so that they can be readily applied in SUD/HIV
prevention, treatment, and recovery. We will conduct workshops for SUD/HIV scientists and publish both
tutorials and new research in SUD, HIV, and methodology venues. We will work with the Dissemination and
Training Core to develop free, user-friendly software that will enable SUD/HIV scientists to develop, optimize,
and evaluate their own just-in-time adaptive digital health interventions.

## Key facts

- **NIH application ID:** 10267871
- **Project number:** 1P50DA054039-01
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** SUSAN A MURPHY
- **Activity code:** P50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $510,036
- **Award type:** 1
- **Project period:** 2021-09-01 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10267871

## Citation

> US National Institutes of Health, RePORTER application 10267871, Continual Optimization and Personalization of Just-in-Time Adaptive Interventions for SUD  Prevention, Treatment, and Recovery (1P50DA054039-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10267871. Licensed CC0.

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