# Methods for Optimizing the Integration of Adaptive Human-Delivered and Digital SUD/HIV Services

> **NIH NIH P50** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2024 · $408,663

## Abstract

PROJECT SUMMARY: PROJECT 2
Advances in digital technologies (e.g., electronic health records, telehealth, and mobile health technologies)
have created unprecedented opportunities to extend the reach and impact of adaptive services for individuals
with or at risk for substance use disorders (SUD) and HIV. While services delivered by automated software
tools, such as digital just-in-time adaptive interventions (JITAIs), are relatively inexpensive and can deliver
support in the moment, insufficient engagement remains a major barrier. Human delivery of services can be
more engaging but often more expensive and burdensome. Hence, the integration of digital and human-
delivered services requires a trade-off between benefits and drawbacks that necessitates balancing
effectiveness against scalability and sustainability. Understanding how to best leverage digital and human
modalities to deliver adaptive interventions is critical for building effective and scalable SUD/HIV services. A
major challenge is determining how best to use data to optimize the integration between intervention
components that are human-delivered with a low intensity of adaptation (e.g., weekly, monthly) and those that
are digitally delivered with a high intensity of adaptation (e.g., every minute or day). The long-term goal of the
proposed project is to enable scientists to optimize Multimodality Adaptive Interventions (MADIs), in which both
human-delivered and digital components are sequenced and adapted over time, at different time scales. To
achieve this long-term goal, we will: (Aim 1) Develop a new, flexible trial design in which individuals can be
randomized simultaneously to human-delivered and digital interventions at different time scales; (Aim 2)
Develop new statistical methods for use with data from the new experimental design to address novel
questions about synergies between human-delivered and digital services; (Aim 3) Develop sample size
calculators to enable SUD/HIV scientists to plan novel experimental studies to address these questions; and
(Aim 4) Place these methods directly into the hands of SUD/HIV scientists so that they can be readily applied
to advance SUD/HIV prevention, treatment, and recovery services. We will conduct workshops for SUD/HIV
scientists and publish both tutorials and applications in drug-use, HIV, and methodology outlets. We will work
with the Dissemination and Training Core to develop free, user-friendly software that will enable SUD/HIV
scientists to employ the new method in their own work. This project will provide the scaffolding to support
evidence-driven integration and adaptation of human-delivered and digital services, accelerating a new
generation of effective and scalable SUD/HIV interventions.

## Key facts

- **NIH application ID:** 10867507
- **Project number:** 5P50DA054039-04
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Inbal Billie Nahum-Shani
- **Activity code:** P50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $408,663
- **Award type:** 5
- **Project period:** 2021-09-01 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10867507

## Citation

> US National Institutes of Health, RePORTER application 10867507, Methods for Optimizing the Integration of Adaptive Human-Delivered and Digital SUD/HIV Services (5P50DA054039-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10867507. Licensed CC0.

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