Smartphone-Based Dietary Support for Obesity

Overseen By Stephanie P Goldstein, PhD

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: The Miriam Hospital

Must not be taking: Weight loss medication

Disqualifiers: Pregnancy, Bariatric surgery, others

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

Compensation: Varies

Number of Visits: 4

Duration: 3 months

What You Need to Know Before You Apply

What is the purpose of this trial?

The trial aims to help people adhere to their dietary goals by using a smartphone app that provides timely support when they are likely to slip up. It will test different support methods, such as motivation boosts and self-control tips, to determine which best prevents dietary lapses. The trial seeks participants who have struggled with weight management, have a BMI between 25 and 50, and have conditions like prediabetes or high blood pressure. Participants will use the app alongside a 3-month online behavioral obesity treatment program. As an unphased trial, this study offers a unique opportunity to explore innovative support methods for improved dietary management.

Will I have to stop taking my current medications?

The trial does not specify whether you need to stop taking your current medications, but you cannot participate if you are currently taking weight loss medication.

What prior data suggests that this smartphone-based dietary support intervention is safe?

Research shows that using smartphones and online tools for obesity treatment is generally safe and effective. Studies have found that online programs for managing obesity work as well as in-person methods, without major safety concerns. These digital tools often help people lose weight successfully.

Programs that boost confidence in sticking to diet goals have also shown good results. They encourage physical activity and support weight loss, with few reported issues.

Motivation-focused programs help people stay committed to their weight goals. These have been linked to better weight loss results and are usually safe.

Self-regulation, which involves controlling one's own behavior, is another promising area. It helps people manage their eating habits and weight without significant safety concerns.

Finally, educational programs that provide information on healthy eating are considered safe and effective for promoting weight loss.

Overall, these programs support healthy weight management without major side effects. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about this trial because it's testing a new way of supporting people with obesity using their smartphones. Unlike traditional treatments that might rely on in-person counseling or medication, this approach offers digital interventions like self-efficacy, motivation, and self-regulation skills directly through an app. These interventions are designed to empower users to manage their dietary goals more effectively, providing a personalized and convenient alternative to standard options. By leveraging technology, this method could make weight management more accessible and adaptable to individual needs, which is a promising step forward in obesity care.

What evidence suggests that this trial's treatments could be effective for obesity?

Research has shown that smartphone apps can help people adhere to their diets when trying to lose weight. This trial will evaluate several approaches:

One study found that self-efficacy, or believing in one's ability to succeed, is linked to better weight loss results. This trial includes a self-efficacy intervention arm. Motivation is also crucial; studies have found that motivated individuals lose more weight and maintain it longer. This trial includes a motivation intervention arm. Programs that teach self-regulation, or behavior control, have been shown to help maintain weight loss, and this trial includes a self-regulation intervention arm.

Online treatments have proven effective, with some studies showing they work as well as in-person programs. This trial includes an online behavioral obesity treatment arm. Educational programs that enhance understanding of diet and nutrition have led to significant weight loss, and this trial includes an enhanced education intervention arm.

Overall, these methods show promise in reducing diet slip-ups and supporting weight loss. ^{1 3 6 7 8}

Are You a Good Fit for This Trial?

This trial is for adults aged 18-70 with a BMI of 25-50 and at least one cardiovascular risk factor like prediabetes, type 2 diabetes, high cholesterol, or hypertension. They must be able to walk two blocks without stopping and not be in another weight loss program or have conditions that affect study participation.

Inclusion Criteria

Your body mass index (BMI) falls between 25 and 50 kg/m².

I have been diagnosed with a condition that increases my risk for heart disease.

I can walk 2 city blocks without needing to stop.

Exclusion Criteria

Plans to become pregnant within 6 months of enrolling

Has any condition that would result in inability to follow the study protocol, including terminal illness, substance abuse, eating disorder (not including Binge Eating Disorder) and untreated major psychiatric illness.

I have had weight loss surgery in the past.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

1 visit (in-person or virtual)

Baseline Assessment

Participants complete baseline questionnaires and self-reported logs of dietary intake and ecological momentary assessments (EMA) for 1 week before the baseline assessment.

1 week

1 visit (in-person or virtual)

Treatment

Participants receive 3 months of online behavioral obesity treatment (BOT) and use the JITAI system to monitor and intervene on dietary lapses.

3 months

Daily interaction with JITAI, 1 assessment visit at 3 months

Follow-up

Participants continue using the JITAI system without the behavioral obesity treatment for an additional 3 months.

3 months

1 assessment visit at 6 months

What Are the Treatments Tested in This Trial?

Interventions

• Enhanced Education
• Generic Risk Alert (Active Comparator)
• Motivation
• Online Behavioral Obesity Treatment
• Self-Efficacy
• Self-Regulation

Trial Overview

The trial tests a smartphone-based intervention to prevent dietary lapses during obesity treatment. It uses daily surveys, machine learning for lapse risk assessment, and various interventions when there's a high risk of lapsing. The effectiveness of these interventions will be compared.

How Is the Trial Designed?

Group I: Self-regulation Experimental Treatment 2 Interventions

Theory-driven intervention focused on providing skills to increase self-regulation

Group II: Self-efficacy Experimental Treatment 2 Interventions

Theory-driven intervention focused on providing skills to increase self-efficacy for following dietary goals

Group III: Motivation Experimental Treatment 2 Interventions

Theory-driven intervention focused on providing skills to increase motivation for following dietary goals

Group IV: Enhanced Education Experimental Treatment 2 Interventions

Theory-driven intervention focused on providing information about dietary quality and goals

Group V: Generic Risk Alert Active Control 2 Interventions

A notification to alert participant of lapse risk, no additional intervention provided

Group VI: No Intervention Placebo Group 1 Intervention

No notification or intervention is delivered to the participant during lapse risk

Who Is Running the Clinical Trial?

The Miriam Hospital

Lead Sponsor

Trials

252

Recruited

39,200+

National Heart, Lung, and Blood Institute (NHLBI)

Collaborator

Trials

3,987

Recruited

47,860,000+

Published Research Related to This Trial

Recent advancements in internet and cell phone interventions have shown that technology-enabled self-management education can significantly improve outcomes for patients with diabetes, including better self-management, medication adherence, and weight loss.

Research indicates that these interventions are effective across various age groups, from teens to older adults, suggesting a broad applicability that could lead to increased recognition and reimbursement from payors for these valuable treatments.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Information technology in the service of diabetes prevention and treatment. Kaufman, N.[2022]

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]

A study involving 72 participants with overweight or obesity found that both simplified dietary self-monitoring and standard calorie tracking led to clinically meaningful weight loss after 6 months, with average weight losses of 5.7% and 4.0%, respectively.

There were no significant differences in adherence to dietary tracking or caloric intake between the two groups, suggesting that simplified monitoring of high-calorie foods could be an effective alternative to traditional calorie counting.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A pilot randomized trial of simplified versus standard calorie dietary self-monitoring in a mobile weight loss intervention. Nezami, BT., Hurley, L., Power, J., et al.[2023]

A digital weight loss intervention using either detailed or simplified dietary self-monitoring was found to be feasible and acceptable among racial and ethnic minority adults, with a high retention rate of 92% over 3 months.

Both intervention groups achieved similar weight loss results, with participants losing an average of approximately 3.4 kg, indicating that simplified self-monitoring may enhance engagement without sacrificing efficacy.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Detailed Versus Simplified Dietary Self-monitoring in a Digital Weight Loss Intervention Among Racial and Ethnic Minority Adults: Fully Remote, Randomized Pilot Study. Patel, ML., Cleare, AE., Smith, CM., et al.[2023]

The combination of motivational interviewing and nutrition psychoeducation (MINP) led to significant weight loss in adults with overweight/obesity over a 3-month period, with 21% of participants achieving at least 5% weight loss by the end of treatment.

Participants with binge-eating disorder (BED) showed greater improvements in disordered eating and depression compared to those without BED, indicating that MINP may be particularly beneficial for individuals struggling with these issues.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Examining motivational interviewing plus nutrition psychoeducation for weight loss in primary care. Barnes, RD., Ivezaj, V., Martino, S., et al.[2019]

In a study involving 55 overweight and obese adults, both a computer-assisted dieting intervention (CAD) and a combined intervention with self-management training (CAD+G) led to reductions in energy, fat, and carbohydrate intake.

The CAD+G group was more effective than the CAD-only group in reducing fat intake, increasing vegetable consumption, and maintaining fruit intake, suggesting that self-management training enhances the effectiveness of computer-assisted dieting.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Computer-assisted dieting: effects of a randomized nutrition intervention. Schroder, KE.[2019]

In a study of 60 obese patients over 24 months, those who received a therapy program focused on nutritional education and intensive follow-up showed a significant decrease in body mass index (%BMI), especially in females after 18 months.

The program had a higher success rate in females (40.5%) compared to males (5.5%), indicating that gender may influence the effectiveness of obesity management strategies.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

[Influence of nutritional education on management of infantile-juvenile obesity]. Durá Travé, T.[2013]

Between 2005 and 2009, about 75% of studies showed that e-health technologies effectively helped reduce fat intake and increase fruit and vegetable consumption in behavioral nutrition interventions.

By 2010, interventions began to focus more on body weight management and included personalized features like self-monitoring, but there has been limited progress in using objective dietary behavior measures instead of self-reports.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Behavioral Nutrition Interventions Using e- and m-Health Communication Technologies: A Narrative Review. Olson, CM.[2019]

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]

A review of 30 studies on web-based interventions for preventing overweight and obesity found that 93% reported positive changes in physical activity levels, dietary habits, and psychological factors.

While the meta-analysis indicated improvements in fruit and vegetable consumption and physical activity, these changes were not statistically significant, suggesting that web-based interventions can raise awareness and encourage healthy behaviors, but may need further optimization for greater impact.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The use of web-based interventions to prevent excessive weight gain. Maon, S., Edirippulige, S., Ware, R., et al.[2012]

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