Improving smartphone apps to help people with alcohol use disorder stay engaged in their treatment
Official title: Optimizing Smart Digital Therapeutic Message Components for Engagement and Clinical Outcomes for Alcohol Use Disorder
Funded at University of Wisconsin-Madison · NIH-10940692 · Data updated 2026-11-12
This study is working on improving an app for people dealing with alcohol use issues by using smart technology to predict when someone might be at risk of relapsing, so the app can give personalized support and help them stay on track with their recovery.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Wisconsin-Madison NIH-funded |
| Lab location | 1 site (Madison, United States) |
| Project start | August 20, 2024 |
| Project end | July 31, 2029 |
| Funding year | 2024 |
| Award (this year) | $683,611 |
| NIH project number | 1R01AA031762-01 |
| Project ID | NIH-10940692 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are adults aged 21 and older who are currently experiencing alcohol use disorder.
✕Less likely to help
Patients who are not struggling with alcohol use disorder or those under 21 years old may not benefit from this research.
What this research studies
This research focuses on enhancing digital therapeutic apps designed for individuals struggling with alcohol use disorder (AUD). By integrating machine learning models that predict potential relapses, the project aims to personalize feedback and support for users, helping them stay engaged with their treatment. The approach leverages personal sensing technology to tailor interventions based on individual risk factors, making the app more effective in preventing relapse. The goal is to create a smarter version of an existing digital therapeutic that can better meet the needs of users.
Why it matters
Potential benefit: If successful, this research could lead to more effective digital tools that help individuals manage their alcohol use disorder and reduce the risk of relapse.
How similar studies have gone: Previous research has shown promise in using digital therapeutics for alcohol use disorder, but this approach of integrating machine learning for personalized feedback is relatively novel.
Where this research is happening
-
University of Wisconsin-Madison
Madison, United States Active
Researchers
- Principal investigator: Curtin, John J. — University of Wisconsin-Madison
- Study coordinator: Curtin, John J.
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.