Digital Weight Loss Intervention for Obesity and Type 2 Diabetes Risk

(mLIFE Trial)

Overseen By Brie Turner-McGrievy, PhD, MS, RD

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: University of South Carolina

Must not be taking: Blood glucose medications

Disqualifiers: Over 65, Type 2 diabetes, others

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

Compensation: Varies

Number of Visits: 3

240 Participants Needed

Trial Summary

Will I have to stop taking my current medications?

The trial requires that you do not use medications that may impact blood glucose. If you are taking such medications, you may need to stop them to participate.

What data supports the effectiveness of the treatment mLIFE app for weight loss and diabetes risk reduction?

Research shows that mobile health apps, like the Social POD app, which focus on social support and self-monitoring, can help with weight loss by encouraging healthy behaviors. Additionally, digital tools for diabetes management have been found to improve patient engagement and outcomes by promoting self-management and motivation. ^{1 2 3 4 5}

Is the digital weight loss intervention generally safe for humans?

The research does not provide specific safety data for the digital weight loss intervention, but it highlights the importance of designing apps that are user-friendly and personalized, which can help in managing weight and diabetes effectively. ^{2 4 5 6 7}

How is the mLIFE app treatment for obesity and Type 2 diabetes risk different from other treatments?

The mLIFE app treatment is unique because it incorporates self-regulation and social support features to help users manage their weight and reduce the risk of Type 2 diabetes. Unlike traditional methods, this digital intervention leverages mobile health technology to enhance user engagement and support through social networks, making it a novel approach in weight management. ^{1 2 8 9 10}

What is the purpose of this trial?

The goal of the study is to examine long term sustained weight loss digital intervention in a diverse cohort of adults with overweight/obesity. The intervention includes social gaming (using game-like elements in nongame contexts to promote supportive social interactions and openness to positive behavioral influences) to reward behaviors, such as self-monitoring and social support. Investigators will accomplish objectives and test hypotheses by following two specific primary aims: 1. Determine if the intervention plus gaming produces significantly more weight loss at 12 months than the same intervention without gaming among 240 adults with overweight or obesity and ≥3 T2DM risk factors. 2. Examine the differences in social support provision and receipt between groups at 12 months.

Research Team

Brie Turner-McGrievy, PhD, MS, RD

Principal Investigator

University of South Carolina

Eligibility Criteria

This trial is for adults aged 18-65 with obesity or overweight, having a BMI of 25-49.9 kg/m2 and at least three risk factors for Type 2 diabetes but not diagnosed with it. Participants must own a smartphone, be willing to change their diet and exercise habits, and not be on medications affecting blood glucose or involved in other weight loss programs.

Inclusion Criteria

I am not taking any medications that affect my blood sugar levels.

≥3 T2DM risk factors (as defined by the American Diabetes Association)

Must not be currently participating in a weight loss study or program

Exclusion Criteria

I have lost more than 10 pounds in the last 6 months.

I have been diagnosed with type 2 diabetes.

I am over 65 years old.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Orientation and Baseline Assessment

Participants attend a study orientation, complete all baseline measures, and are randomized into groups

1 week

1 visit (in-person)

Intervention

Participants engage in a 1-year behavioral intervention using the mLIFE app, with or without gamification, including twice-weekly podcasts and daily tracking

52 weeks

Ongoing virtual engagement

Assessment

Participants complete assessments at 6 and 12 months to evaluate changes in weight, diet, and physical activity

1 week

2 visits (in-person or virtual)

Follow-up

Participants are monitored for sustained weight loss and behavioral changes after the intervention

4 weeks

Treatment Details

Interventions

• mLIFE app (self-regulation features)
• mLIFE app (social support features)
• Podcasts and tips of the day (within app)
• standard mLIFE app (social support features)

Trial Overview The study tests whether an app called mLIFE that includes social gaming features can help people lose more weight over a year compared to the same app without these features. The app provides podcasts, tips, self-regulation tools, and rewards supportive interactions aimed at reducing calorie intake and increasing physical activity.

Participant Groups

Group I: Gamified mLIFE app group Experimental Treatment 3 Interventions

Participants allocated to this group will be provided with elements of social gaming and healthy competition within the mLIFE app.

Group II: standard mLIFE app Active Control 3 Interventions

Participants in this group will receive the same intervention as the experimental group, but some features of the App will not facilitate gaming or competition.

Who Is Running the Clinical Trial?

University of South Carolina

Lead Sponsor

Trials

233

Recruited

122,000+

Findings from Research

The use of digital self-management solutions for Type 2 diabetes, such as DM4All and DiaWatch, led to significant improvements in metabolic outcomes, including reductions in HbA1c, body weight, blood pressure, and cholesterol levels over an average follow-up of 8 months in 100 patients.

Compared to a control group, the ProEmpower participants showed significantly better improvements in cardiovascular risk factors, highlighting the efficacy of digital technologies in enhancing diabetes management and promoting healthier lifestyles.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Clinical outcomes of a digitally supported approach for self-management of type 2 diabetes mellitus. De Luca, V., Bozzetto, L., Giglio, C., et al.[2023]

A study involving 22 participants from a weight management clinic in Singapore identified key features that weight loss apps should include for a multi-ethnic population with overweight and obesity, such as comprehensive calorie counters and individualized behavior change recommendations.

Participants emphasized the importance of flexibility in food logging and the need for apps to provide just-in-time reminders about the consequences of their choices, suggesting that future apps could benefit from artificial intelligence to offer personalized support for weight management.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Essential elements of weight loss apps for a multi-ethnic population with high BMI: a qualitative study with practical recommendations. Chew, HSJ., Lim, SL., Kim, G., et al.[2023]

Users prefer mHealth weight loss apps that are simple, attractive, and allow for self-monitoring with feedback, emphasizing the importance of personalization and engaging content.

Key barriers to using these apps include technological issues and message overload, highlighting the need for careful consideration of message tone, structure, and delivery frequency to enhance user experience.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Consumer perspectives on mHealth for weight loss: a review of qualitative studies. Lyzwinski, LN., Caffery, LJ., Bambling, M., et al.[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]

Mobile health (m-Health) applications can effectively support self-management programs for weight management by helping users monitor their behaviors and engage in lifestyle changes.

These applications are essential tools in addressing obesity, which is primarily caused by overeating and lack of exercise, by providing consumers with resources to manage their weight effectively.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

mHealth Applications: A Tool for Behaviour Change in Weight Management. Vlahu-Gjorgievska, E., Mulakaparambil Unnikrishnan, S., Win, KT.[2018]

References

1. Ireland pubmed.ncbi.nlm.nih.gov

Social networks for improving healthy weight loss behaviors for overweight and obese adults: A randomized clinical trial of the social pounds off digitally (Social POD) mobile app. [2022]

2. Canada pubmed.ncbi.nlm.nih.gov

A Mixed-Methods Approach to the Development, Refinement, and Pilot Testing of Social Networks for Improving Healthy Behaviors. [2022]

3. Canada pubmed.ncbi.nlm.nih.gov

A Patient-Facing Diabetes Dashboard Embedded in a Patient Web Portal: Design Sprint and Usability Testing. [2020]

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

Rapid Evidence Review of Mobile Applications for Self-management of Diabetes. [2019]

5. Switzerland pubmed.ncbi.nlm.nih.gov

Clinical outcomes of a digitally supported approach for self-management of type 2 diabetes mellitus. [2023]

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

Essential elements of weight loss apps for a multi-ethnic population with high BMI: a qualitative study with practical recommendations. [2023]

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

Consumer perspectives on mHealth for weight loss: a review of qualitative studies. [2018]

8. Korea (South) pubmed.ncbi.nlm.nih.gov

The effects of dietary self-monitoring intervention on anthropometric and metabolic changes via a mobile application or paper-based diary: a randomized trial. [2023]

9. Switzerland pubmed.ncbi.nlm.nih.gov

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

10. Netherlands pubmed.ncbi.nlm.nih.gov

mHealth Applications: A Tool for Behaviour Change in Weight Management. [2018]