Personalized cash rewards to help adults lose weight

Applying reinforcement learning to create a precision medicine weight loss intervention

['FUNDING_OTHER'] · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · NIH-11377457

This project uses smart computer algorithms to send personalized small cash rewards to adults to help them keep healthy habits and lose weight.

Quick facts

Phase['FUNDING_OTHER']
Study typeNih_funding
SexAll
SponsorUTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH (nih funded)
Locations1 site (SALT LAKE CITY, UNITED STATES)
Trial IDNIH-11377457 on ClinicalTrials.gov

What this research studies

You would use a smartphone app to log food and weight while the program tracks how you respond to small cash rewards. A machine-learning method called reinforcement learning would learn which timing and amount of incentives work best for you and adjust rewards over time. The team builds the approach from past incentive trials and digital logging data to predict when rewards will boost adherence. The goal is to help more people reach clinically meaningful weight loss (about 5%).

Who could benefit from this research

Good fit: Adults aged 21 and older with overweight or obesity who are willing to use a diet-logging app and accept small monetary incentives are ideal candidates.

Not a fit: People who cannot or will not use a smartphone app, refuse incentive payments, or who need medical or surgical weight-loss care may not get benefit from this approach.

Why it matters

Potential benefit: If successful, this could help more people reach meaningful weight loss by directing limited incentive funds to those who respond best.

How similar studies have performed: Previous behavioral weight-loss programs and small-incentive trials have helped some people lose weight, but applying reinforcement learning to personalize incentives is a relatively new approach.

Where this research is happening

SALT LAKE CITY, UNITED STATES

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.

View on NIH RePORTER →

Last reviewed 2026-05-15 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.