Behavioral Economics mHealth for Obesity

(RISE Trial)

Overseen By Denise F Pierre, BS

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: University of Connecticut

Must not be taking: Insulin

Disqualifiers: Heart condition, Pregnancy, Diabetes, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

Duration: 12 months

192 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

The primary aim of this study is to test the efficacy of a behavioral economics intervention for weight loss in adults from economically disadvantaged backgrounds.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. However, if you have diabetes and are on insulin, you cannot participate in the trial.

Is the Behavioral Economics mHealth treatment for obesity safe for humans?

The studies reviewed did not report any safety concerns related to the use of mobile phone-based interventions for weight loss, suggesting that these methods are generally safe for human use. ^{1 2 3 4 5}

How is the BE mHealth treatment for obesity different from other treatments?

The BE mHealth treatment for obesity is unique because it uses principles from behavioral economics to influence healthier food and activity choices by adjusting the costs and rewards associated with these behaviors. This approach is different from traditional treatments as it focuses on changing the decision-making environment to promote weight loss. ^{6 7 8 9 10}

What data supports the effectiveness of the treatment BE mHealth, mHealth for obesity?

Research suggests that mobile health (mHealth) interventions can be effective in promoting weight loss and maintaining behavior changes. These interventions leverage mobile technology to deliver personalized health information and support, which has shown promise in improving weight management outcomes. ^{9 11 12 13 14}

Who Is on the Research Team?

Tricia Leahey, PhD

Principal Investigator

University of Connecticut

Are You a Good Fit for This Trial?

This trial is for adults aged 18-75 with a BMI of 25-55 who are from low-income backgrounds and willing to use their smartphone for the study. It's not for those currently in weight loss treatment, with recent significant weight loss, bariatric surgery history, pregnancy plans within a year, certain medical or heart conditions, insulin-treated diabetes, or inability to walk short distances.

Inclusion Criteria

BMI between 25-55kg/m2

I have a smartphone and am willing to use it for research.

All racial/ethnic groups

Exclusion Criteria

I have heart issues, chest pain during rest or activity, or have fainted.

Report unable to read and write English

I can't walk 2 blocks without stopping.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment

Participants receive a 12-month behavioral weight loss intervention delivered primarily via mobile phone (mHealth) with behavioral economics components

12 months

Follow-up

Participants are monitored for weight change and other outcomes after the treatment phase

6 months

What Are the Treatments Tested in This Trial?

Interventions

• BE mHealth
• mHealth

Trial Overview The study tests if a behavioral economics-based mobile health intervention (BE mHealth) is more effective at supporting healthy eating and exercise habits than a standard mobile health approach (mHealth) among economically disadvantaged adults aiming to lose weight.

How Is the Trial Designed?

Group I: Behavioral Economics intervention (BE mHealth) Experimental Treatment 1 Intervention

Participants will receive a 12-month behavioral weight loss intervention delivered primarily via mobile phone (mHealth) that includes behavioral economics components.

Group II: Standard mHealth intervention (mHealth) Active Control 1 Intervention

Participants will receive a 12-month behavioral weight loss intervention delivered primarily via mobile phone (mHealth).

Who Is Running the Clinical Trial?

University of Connecticut

Lead Sponsor

Trials

194

Recruited

162,000+

National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

Collaborator

Trials

2,513

Recruited

4,366,000+

Published Research Related to This Trial

Mobile eHealth behavioral interventions have the potential to effectively promote and sustain weight loss and maintenance, especially when they are well-designed and tailored to individual needs.

The review highlights that tailored informational interventions have been the most successful conventional methods for weight loss, and the advancements in mobile technology present new opportunities to enhance these interventions for broader public health impact.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Mobile eHealth interventions for obesity: a timely opportunity to leverage convergence trends. Tufano, JT., Karras, BT.[2018]

Inpatient rehabilitation for obesity should involve a multidisciplinary team, including various health professionals, to effectively improve weight loss and address related health issues.

Internet-based and mobile health (mHealth) technologies can enhance long-term obesity rehabilitation by improving treatment compliance and engagement, suggesting a promising direction for future research in this field.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Obesity and outpatient rehabilitation using mobile technologies: the potential mHealth approach. Castelnuovo, G., Manzoni, GM., Pietrabissa, G., et al.[2022]

In a 12-month study involving 70 adults with obesity, the group using mobile technology for self-monitoring and coaching lost an average of 3.9 kg more than the standard treatment group, indicating enhanced weight loss efficacy.

Participants in the mobile technology group had significantly higher odds (6.5 times greater) of losing at least 5% of their baseline weight compared to those receiving standard care alone, suggesting that mobile technology can effectively support weight loss efforts.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Integrating technology into standard weight loss treatment: a randomized controlled trial. Spring, B., Duncan, JM., Janke, EA., et al.[2021]

A pilot trial involving 34 rural women showed that a 6-month behavioral weight loss program delivered via group phone calls resulted in greater weight loss (mean 14.9 kg) compared to individual phone counseling (mean 9.5 kg), indicating that group support may enhance treatment efficacy.

The group phone-based treatment was not only more effective, with 62% of participants achieving a 10% weight loss goal compared to 50% in the individual condition, but it was also found to be more cost-effective, suggesting a promising strategy for obesity management in rural areas.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Group versus individual phone-based obesity treatment for rural women. Befort, CA., Donnelly, JE., Sullivan, DK., et al.[2021]

Financial incentives based on behavioral economics significantly increased the odds of health behavior change, with participants having nearly four times higher odds of changing their behavior compared to those in the control group (odds ratio of 3.96).

The effectiveness of these financial incentives did not vary significantly by demographic factors such as gender, age, or education, but showed that Black participants had higher odds of behavior change compared to White participants when using conditional payments, while higher-income individuals had lower odds of change with a specific incentive structure.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The role of behavioral economic incentive design and demographic characteristics in financial incentive-based approaches to changing health behaviors: a meta-analysis. Haff, N., Patel, MS., Lim, R., et al.[2022]

Citations

1. Canada pubmed.ncbi.nlm.nih.gov

Mobile eHealth interventions for obesity: a timely opportunity to leverage convergence trends. [2018]

2. England pubmed.ncbi.nlm.nih.gov

Improving the cost-effectiveness of obesity programs: three basic strategies for reducing the cost per pound. [2014]

3. Switzerland pubmed.ncbi.nlm.nih.gov

Obesity and outpatient rehabilitation using mobile technologies: the potential mHealth approach. [2022]

4. United States pubmed.ncbi.nlm.nih.gov

Integrating technology into standard weight loss treatment: a randomized controlled trial. [2021]

5. United States pubmed.ncbi.nlm.nih.gov

A low-cost reinforcement procedure improves short-term weight loss outcomes. [2021]

6. England pubmed.ncbi.nlm.nih.gov

Gaining pounds by losing pounds: preferences for lifestyle interventions to reduce obesity. [2022]

7. England pubmed.ncbi.nlm.nih.gov

Mobile phone short message service messaging for behaviour modification in a community-based weight control programme in Korea. [2019]

8. United States pubmed.ncbi.nlm.nih.gov

The Healthy Weigh study of lottery-based incentives and environmental strategies for weight loss: Design and baseline characteristics. [2020]

9. United States pubmed.ncbi.nlm.nih.gov

Group versus individual phone-based obesity treatment for rural women. [2021]

10. United States pubmed.ncbi.nlm.nih.gov

Lifetime health and economic benefits of weight loss among obese persons. [2022]

11. United States pubmed.ncbi.nlm.nih.gov

Behavioral Economic Factors Related to Pediatric Obesity. [2022]

12. Netherlands pubmed.ncbi.nlm.nih.gov

Behavioral economics: merging psychology and economics for lifestyle interventions. [2022]

13. United States pubmed.ncbi.nlm.nih.gov

The role of behavioral economic incentive design and demographic characteristics in financial incentive-based approaches to changing health behaviors: a meta-analysis. [2022]

14. United States pubmed.ncbi.nlm.nih.gov

Application of behavioral economics for understanding health behaviors among adolescents and young adults. [2023]