# ADAPT: Enabling robust adaptation in mHealth interventions for supporting maintenance of heart-healthy behaviors

> **NIH NIH R01** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2024 · $728,661

## Abstract

Abstract
Cardiac rehabilitation (CR) programs are effective at improving cardiovascular outcomes by helping patients
make heart-healthy lifestyle changes. However, these gains often do not last since as many as 50% of CR
patients stop exercising or eating a heart-healthy diet within a few months of completing a CR program. Mobile
health (mHealth) has the potential to provide effective ongoing support after CR programs end, and to help
patients sustain and augment health gains obtained during CR. However, to realize this promise, new
approaches are needed to increase the engagement in mHealth interventions. Patients abandon these
interventions for many reasons, including because they get discouraged when they don't meet their goals,
frustrated when they feel the mHealth system is sending them messages at wrong times or too often, or when
other demands in their lives take priority over trying to be active or eat healthily. Once abandoned mHealth
interventions stop being able to provide any further support. In this project, we will address this important
problem by developing novel algorithms and user interfaces (elements of an mHealth app individuals use to
interact with the app) that will help mHealth interventions to effectively adapt to the changes in individuals'
needs and priorities, so the intervention can remain useful—and thus have an opportunity to support patients—
over the long-term. The methods will (1) help mHealth systems more effectively provide interventions by
monitoring and optimizing how these interventions impact both intermediate-term behavioral outcomes like
commitment to physical activity—which mediate long-term change—as well as engagement with the
intervention itself; and (2) enable users to directly make changes to how an intervention behaves by examining
and correcting the information that the system uses to make decisions about intervention provision and
specifying the level of support that better matches their current circumstances and priorities. Once developed
and optimized in a micro-randomized trial with 60 CR patients, we will evaluate the ability of these innovations
to improve engagement with an mHealth intervention for physical activity and to improve physical activity itself
in a 9-month randomized controlled trial with 150 CR patients. The trial will compare an intervention that
contains the newly developed algorithms and interfaces with one that includes the same components for
supporting behavior change but which does not include the new algorithms and interfaces for increasing
engagement. If found to be successful, the innovations developed in this project will enable the development of
a new generation of mHealth interventions that can effectively support behavior change and maintenance both
for cardiovascular risk reduction and in other domains of health.

## Key facts

- **NIH application ID:** 10799274
- **Project number:** 2R01HL125440-06A1
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Predrag Klasnja
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $728,661
- **Award type:** 2
- **Project period:** 2014-12-01 → 2028-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10799274

## Citation

> US National Institutes of Health, RePORTER application 10799274, ADAPT: Enabling robust adaptation in mHealth interventions for supporting maintenance of heart-healthy behaviors (2R01HL125440-06A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10799274. Licensed CC0.

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