App & Fitbit Monitoring for Type 2 Diabetes

Recruiting at 1 trial location

Overseen By Rachel Goode, PhD, MPH, LCSW

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: University of North Carolina, Chapel Hill

Disqualifiers: Major diabetes complications, Weight loss surgery, Pregnant, Substance use treatment, others

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

Compensation: Varies

Number of Visits: 2

Duration: 24 weeks

60 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

The purpose of this 6-month randomized clinical trial is to examine the feasibility of recruitment, attendance, retention, program adherence, and satisfaction of a digital application designed, Centering Appetite to improve glucose scores (HbA1c) and binge eating in African American adults with type 2 diabetes. Intervention participants will receive type 2 diabetes education and web-based lessons on appetite self-regulation. Participants will also receive a Fitbit to monitor daily physical activity. The investigators will follow up with participants at six months.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It is best to consult with the trial coordinators for specific guidance.

Is the App & Fitbit Monitoring for Type 2 Diabetes safe for humans?

The studies reviewed suggest that using digital tools like apps and Fitbits for self-monitoring diet and physical activity is generally safe for humans, as they have been used in various weight loss and diabetes prevention programs without significant safety concerns. ^{1 2 3 4 5}

How does the DSME + ASE intervention (Centering Appetite) treatment differ from other treatments for Type 2 Diabetes?

The DSME + ASE intervention (Centering Appetite) treatment is unique because it combines diabetes self-management education (DSME) with an app and Fitbit technology to monitor and adjust lifestyle behaviors, focusing on appetite control. This approach integrates digital tools to provide personalized feedback and support, which is different from traditional treatments that may not use technology to this extent. ^{2 4 6 7 8}

What data supports the effectiveness of the treatment DSME + ASE intervention (Centering Appetite) for Type 2 Diabetes?

Research shows that using digital tools like apps and wearable devices can help people with type 2 diabetes manage their condition better by promoting self-management and healthy lifestyle changes, which can improve blood sugar control and reduce complications. ^{2 6 9 10 11}

Who Is on the Research Team?

Rachel Goode, PhD, MPH, LCSW

Principal Investigator

University of North Carolina at Chapel Hil

Are You a Good Fit for This Trial?

This trial is for African American adults with type 2 diabetes who experience binge eating. They must be over 18, have an HbA1c level above 7.5, and own a working smartphone. It's not for those with major diabetes complications, substance use treatment, involvement in other weight programs, history of weight loss surgery or current pregnancy.

Inclusion Criteria

Your A1c value is higher than 7.5.

You have been screened for binge eating.

I am over 18 years old.

Exclusion Criteria

I have serious complications from type 2 diabetes.

I have had weight loss surgery in the past.

Are currently pregnant

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment

Participants receive a 6-month digital diabetes self-management education program plus an appetite self-regulation intervention

24 weeks

2 intervention sessions, monthly booster sessions, weekly messages

Follow-up

Participants are monitored for changes in weight, binge eating episodes, blood pressure, and HbA1C

4 weeks

What Are the Treatments Tested in This Trial?

Interventions

• DSME + ASE intervention (Centering Appetite)

Trial Overview The study tests a digital app called Centering Appetite combined with diabetes education to improve blood sugar control and reduce binge eating. Participants will also use a Fitbit to track physical activity and follow up after six months.

How Is the Trial Designed?

Group I: DSMES + ASE intervention Appetite Self-Regulation (Centering Appetite) Experimental Treatment 1 Intervention

The Diabetes Self-Management Education and Support (DSMES) + Appetite Self-Regulation (ASE) intervention includes two, 45-60-minute group sessions delivered via telehealth. These sessions will enable participants to relearn their stomach's hunger and fullness signals and monitor their appetite. Participants will also learn strategies for glucose monitoring and carbohydrate management. Monthly booster sessions will be devoted to problem-solving, addressing barriers to emotion management, and self-monitoring type 2 diabetes mellitus symptoms. Participants will also receive weekly lessons with interactive activities delivered via a digital app.

Group II: Control Active Control 1 Intervention

Control group participants will attend two remotely delivered DSMES sessions that will offer content commonly. They will also receive weekly emails providing content from the American Association of Diabetes Educators.

Who Is Running the Clinical Trial?

University of North Carolina, Chapel Hill

Lead Sponsor

Trials

1,588

Recruited

4,364,000+

American Diabetes Association

Collaborator

Trials

148

Recruited

102,000+

Published Research Related to This Trial

A 12-week study involving 90 participants with type 2 diabetes found that both supervised exercise and technology-based programs (mobile app and smartwatch) led to similar improvements in glycemic control, measured by HbA1c levels.

Approximately 46% of participants in the supervised group and 43% in the technology groups achieved a clinically meaningful reduction in HbA1c, indicating that technology can be an effective alternative for diabetes management when supervised programs are not available.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Technology-based and supervised exercise interventions for individuals with type 2 diabetes: Randomized controlled trial. Timurtas, E., Inceer, M., Mayo, N., et al.[2022]

In a study involving 27 participants with type 1 diabetes, an automated insulin delivery (AID) system that used real-time exercise data (exMPC) showed a significant reduction in mean glucose levels during exercise compared to a standard AID system (exAPD), indicating improved glucose management during physical activity.

Both AID systems effectively reduced the time spent in hypoglycemia and maintained glucose levels within the target range, demonstrating that integrating wearable fitness data into insulin dosing can enhance safety and efficacy for individuals with type 1 diabetes during exercise.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Integrating metabolic expenditure information from wearable fitness sensors into an AI-augmented automated insulin delivery system: a randomised clinical trial. Jacobs, PG., Resalat, N., Hilts, W., et al.[2023]

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]

In a 12-week pilot study with 39 participants, all groups using self-monitoring (SM) of food intake, whether with or without real-time feedback (FB) or in-person sessions, achieved significant weight loss, averaging around 3% of their body weight.

Adherence to dietary self-monitoring was similar across all groups, indicating that the addition of real-time feedback or in-person sessions did not significantly enhance adherence or weight loss outcomes, suggesting that self-monitoring alone can be effective.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The SMARTER pilot study: Testing feasibility of real-time feedback for dietary self-monitoring. Burke, LE., Zheng, Y., Ma, Q., et al.[2022]

Digital self-monitoring of diet and physical activity is effective in promoting weight loss, with a mean difference of -2.87 kg and a significant reduction in calorie intake of approximately 182 calories per day, based on a meta-analysis of 12 randomized controlled trials involving adults with obesity or overweight.

Tailored interventions that provide personalized advice were found to be significantly more effective than non-tailored approaches, highlighting the importance of customization in digital self-monitoring programs for better outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Does self-monitoring diet and physical activity behaviors using digital technology support adults with obesity or overweight to lose weight? A systematic literature review with meta-analysis. Berry, R., Kassavou, A., Sutton, S.[2021]

Citations

1. England pubmed.ncbi.nlm.nih.gov

Technology-based and supervised exercise interventions for individuals with type 2 diabetes: Randomized controlled trial. [2022]

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

DPPFit: Developing and Testing a Technology-Based Adaptation of the Diabetes Prevention Program (DPP) to Address Prediabetes in a Primary Care Setting. [2022]

3. England pubmed.ncbi.nlm.nih.gov

Integrating metabolic expenditure information from wearable fitness sensors into an AI-augmented automated insulin delivery system: a randomised clinical trial. [2023]

4. Switzerland pubmed.ncbi.nlm.nih.gov

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

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

Perceptions of Using Multiple Mobile Health Devices to Support Self-Management Among Adults With Type 2 Diabetes: A Qualitative Descriptive Study. [2022]

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

Comparing ecological momentary assessment to sensor-based approaches in predicting dietary lapse. [2022]

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

The SMARTER pilot study: Testing feasibility of real-time feedback for dietary self-monitoring. [2022]

8. England pubmed.ncbi.nlm.nih.gov

Does self-monitoring diet and physical activity behaviors using digital technology support adults with obesity or overweight to lose weight? A systematic literature review with meta-analysis. [2021]

9. Canada pubmed.ncbi.nlm.nih.gov

Consistency With and Disengagement From Self-monitoring of Weight, Dietary Intake, and Physical Activity in a Technology-Based Weight Loss Program: Exploratory Study. [2023]

10. Germany pubmed.ncbi.nlm.nih.gov

[App-based self-monitoring in type 2 diabetes]. [2018]

11. England pubmed.ncbi.nlm.nih.gov

Digital health application integrating wearable data and behavioral patterns improves metabolic health. [2023]