Personalized financial rewards to support weight loss

Log2LoseAI: Reinforcement Learning to Create a Framework for Personalizing Financial Incentives

Not applicable Interventional University of Utah · NCT07225426

This program will try giving customized cash incentives, guided by an AI algorithm, to adults with obesity who are taking part in a virtual group weight-loss program to encourage diet tracking and interim weight loss.

Quick facts

PhaseNot applicable
Study typeInterventional
Enrollment80 (estimated)
Ages18 Years and up
SexAll
SponsorUniversity of Utah Academic / other
Locations1 site (Salt Lake City, Utah)
Trial IDNCT07225426 on ClinicalTrials.gov

What this trial studies

Over 24 weeks, participants attend clinician-facilitated biweekly group classes and use a mobile app to log dietary intake and a cellular scale to report weight. A software platform collects the data and a reinforcement learning algorithm uses those data to predict which participants are likely to respond to financial incentives. The system sends incentives and notifications by text message to participants the algorithm predicts will respond. The main goal is to test whether this personalized incentive approach is feasible within a community outpatient weight-loss program.

Who should consider this trial

Good fit: Adults aged 18 or older with a BMI of 30 kg/m2 or higher who want to lose weight, can attend virtual group classes, have an unshared smartphone and reliable internet access, and can use a cellular scale and Fitbit app are ideal candidates.

Not a fit: People without reliable smartphone or internet access, those with recent large weight loss, those weighing over the study limit (>380 lbs), or those currently in other weight-loss programs are unlikely to benefit or be eligible.

Why it matters

Potential benefit: If successful, this approach could improve diet self-monitoring and short-term weight loss by directing limited financial incentives to the people most likely to benefit.

How similar studies have performed: Previous work has shown that financial incentives can boost short-term weight-loss behaviors, but using reinforcement learning to personalize who receives incentives is relatively new and experimental.

Eligibility criteria

Show full inclusion / exclusion criteria
Inclusion Criteria:

1. Willing to attend virtual baseline and follow-up data collection visits
2. At least 18 years of age
3. Verified obesity as defined as a BMI ≥30 kg/m2
4. Agree to attend 13 biweekly group classes (virtual) delivered by a registered dietitian
5. Agree to review study materials between classes
6. Regular access to an unshared smart phone
7. Reliable access to internet
8. Able to speak and read English
9. Desire to lose weight
10. Able to connect to a video conference call using a smartphone, tablet or computer with a webcam and microphone
11. Ability to download and use Fitbit app daily
12. Have or be willing to create a Gmail address
13. Physical ability to stand on a scale without support

Exclusion Criteria:

1. Weight loss of at least 10lbs in the month prior to screening
2. Weight \> 380lbs
3. Currently enrolled or enrolled in the previous month in a clinical, research, or community program focusing on lifestyle change that could affect weight
4. New user of weight loss medication
5. Pregnant, lactating or planning on becoming pregnant during the study
6. History of bariatric procedure or planning to have bariatric procedure in the study timeframe
7. Residing in a nursing home, skilled nursing facility or assisted living facility
8. Impaired hearing
9. Significant dementia, drug or alcohol abuse, or unstable psychiatric illness (e.g., schizophrenia, psychosis)
10. Current treatment for cancer or being treated for cancer (besides basal cell carcinoma or squamous cell) in the last 6 months
11. Use of insulin, sulfonylureas, or meglitinides due to increased risk for hypoglycemia
12. Diuretic medication doses higher than hydrochlorothiazide or chlorthalidone 25 mg daily, furosemide 40 mg daily, torsemide 20 mg daily, bumetanide 1 mg daily, or any use of metolazone; use of potassium-sparing diuretics is acceptable
13. Unstable heart disease in the 6 months prior to screening
14. Chronic kidney disease at stage 4 or higher
15. Exertional chest pain
16. Pain, fainting, or other conditions that prohibit mild/moderate exercise
17. History of ascites requiring paracentesis
18. Inducing vomiting to prevent weight gain or counteract the effects of eating an average of 1 time per week or more in the past 3 months\*
19. Not suitable for study participation due to other reasons at the discretion of the investigators

Where this trial is running

Salt Lake City, Utah

Study contacts

How to participate

  1. Review the eligibility criteria above with your treating physician.
  2. Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
  3. Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions Obesity & Overweightbehavioral interventionobesityfinancial incentivesreinforcement learningartificial intelligence
Last reviewed 2026-06-15 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.