Improving mobile health support for addiction and behavioral health decisions
Official title: Uncertainty-Informed Decision Making for Just-in-Time Adaptive Interventions (JITAIs)
Funded at Harvard University · NIH-11114787 · Data updated 2026-11-12
This study is working on a new mobile health app that gives personalized support to people struggling with addiction and mental health issues, helping them make better choices for quitting smoking and preventing suicide based on their real-time needs.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Harvard University NIH-funded |
| Lab location | 1 site (Cambridge, United States) |
| Project start | April 1, 2025 |
| Project end | March 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $112,482 |
| NIH project number | 1K99EB037411-01 |
| Project ID | NIH-11114787 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals seeking support for addiction, particularly those looking to quit smoking or manage suicidal thoughts.
✕Less likely to help
Patients who are not dealing with addiction or behavioral health issues may not receive any benefit from this research.
What this research studies
This research focuses on developing advanced methods to provide personalized mobile health (mHealth) support for individuals dealing with addiction and behavioral health issues. It aims to create systems that adaptively intervene based on real-time assessments of a patient's state, using machine learning techniques to quantify uncertainty in predictions. By integrating behavioral science with technology, the project seeks to enhance decision-making processes for interventions related to smoking cessation and suicide prevention. Patients will benefit from tailored support that adjusts to their needs throughout their daily lives.
Why it matters
Potential benefit: If successful, this research could lead to more effective and personalized interventions for individuals struggling with addiction and related behavioral health challenges.
How similar studies have gone: Previous research has shown promise in using adaptive interventions and machine learning for behavioral health, indicating potential success for this innovative approach.
Where this research is happening
-
Harvard University
Cambridge, United States Active
Researchers
- Principal investigator: Gazi, Asim Hossain — Harvard University
- Study coordinator: Gazi, Asim Hossain
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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.