Tailored Advice Tool for Weight Loss

Overseen By Nisha O'Shea, PhD

Age: 18 - 65

Sex: Any

Trial Phase: Academic

Sponsor: UNC Lineberger Comprehensive Cancer Center

Must not be taking: Oral steroids, Weight loss medications

Disqualifiers: Diabetes, Heart condition, Pregnancy, others

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

Compensation: Varies

Number of Visits: Unknown

Duration: 12 weeks

20 Participants Needed

Trial Summary

What is the purpose of this trial?

The purpose of this pilot study is to conduct a 12-week pilot feasibility study testing usability of a reinforcement learning model (AdaptRL) in a weight loss intervention (ADAPT study). Building upon a previous just-in-time adaptive intervention (JITAI), a reinforcement learning model will generate decision rules unique to each individual that are intended to improve the tailoring of brief intervention messages (e.g., what behavior to message about, what behavior change techniques to include), improve achievement of daily behavioral goals, and improve weight loss in a sample of 20 adults.

Will I have to stop taking my current medications?

If you are currently using prescription medications that affect appetite or weight, you may not be eligible to participate, unless you have been on a stable dose of SSRIs (a type of antidepressant) for at least 3 months. The trial does not specify a need to stop other medications.

What data supports the effectiveness of the treatment ADAPT for weight loss?

Research shows that using patient-reported outcome measures (PROMs) can improve patient care and outcomes by helping clinicians better understand and address patient needs. This suggests that the tailored advice tool in ADAPT, which likely uses similar feedback mechanisms, could be effective in supporting weight loss. ^{1 2 3 4 5}

Is the Tailored Advice Tool for Weight Loss safe for humans?

The safety of anti-obesity medications has been studied, showing that some can cause serious side effects, especially related to heart and mental health. For example, rimonabant has been linked to psychiatric issues, and orlistat can cause stomach problems. It's important to consider these potential risks when evaluating any weight loss treatment. ^{6 7 8 9 10}

How does the ADAPT treatment for weight loss differ from other treatments?

The ADAPT treatment is unique because it uses a tailored advice tool that likely incorporates elements of personalization and real-time feedback, similar to mHealth interventions, which are designed to engage users and provide motivation and education through mobile technology. ^{11 12 13 14 15}

Research Team

Brooke Nezami, PhD, MA

Principal Investigator

University of North Carolina, Chapel Hill

Eligibility Criteria

This trial is for adults aged 18-55 with a BMI of 25-40 who are not meeting US physical activity guidelines, can speak and write English, have no major health issues that limit exercise, and own a smartphone. Excluded are those on weight loss meds, pregnant or planning pregnancy soon, with certain medical conditions like diabetes requiring insulin treatment or recent cancer treatment.

Inclusion Criteria

Has a smartphone with a data and text messaging plan

Not adhering to the US physical activity guidelines of at least 150 moderate-to-vigorous intensity activity minutes/week

Body Mass Index of 25-40 kg/m2

Exclusion Criteria

Another member of the household is a participant or staff member in this trial

I have heart or bone issues, or take medicine for blood pressure or heart conditions.

I have Type 1 diabetes or am being treated for Type 2 diabetes.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment

Participants receive a smart scale and a physical activity tracker, with daily goals and personalized messages for 12 weeks

12 weeks

0-3 virtual interactions per day

Follow-up

Participants are monitored for safety and effectiveness after treatment

4 weeks

Treatment Details

Interventions

• ADAPT

Trial Overview The ADAPT study is testing the AdaptRL tool over 12 weeks to see if it helps people lose weight by suggesting personalized behavior change techniques. It builds on an existing approach that adjusts support based on how individuals respond to different contexts in real-time.

Participant Groups

Group I: ADAPT intervention Experimental Treatment 1 Intervention

Participants will receive a smart scale and a physical activity tracker and will have three daily goals: weigh daily, a daily personalized active minutes goal, and a daily calorie goal. For 12 weeks, participants will receive 0-3 text messages per day about their behaviors and progress towards their goals, along with weekly personalized feedback, progress graphs, and lessons and resources available on the website.

Who Is Running the Clinical Trial?

UNC Lineberger Comprehensive Cancer Center

Lead Sponsor

Trials

377

Recruited

95,900+

RTI International

Collaborator

Trials

201

Recruited

942,000+

National Cancer Institute (NCI)

Collaborator

Trials

14,080

Recruited

41,180,000+

Duke University

Collaborator

Trials

2,495

Recruited

5,912,000+

Findings from Research

Patient-reported outcome measure (PROM) feedback interventions in oncology showed a positive impact on health-related quality of life (HRQL) and patient-healthcare provider communication, with a moderate effect size based on a meta-analysis of 29 studies involving 7071 cancer patients.

The intervention also demonstrated a significant improvement in 1-year overall survival rates, suggesting that providing feedback can enhance care processes and outcomes for cancer patients, although the findings are limited by a high risk of bias in the studies reviewed.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Effectiveness of routine provision of feedback from patient-reported outcome measurements for cancer care improvement: a systematic review and meta-analysis. Lu, SC., Porter, I., Valderas, JM., et al.[2023]

Integrating patient-reported outcomes data into the management of chronic, non-cancer pain can significantly guide improvements in patient care and outcomes.

Standardizing care processes and using valid outcome measurement tools can enhance the effectiveness of treatment while minimizing the burden on patients and healthcare providers.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Can assessing chronic pain outcomes data improve outcomes? Witkin, LR., Farrar, JT., Ashburn, MA.[2019]

Patient-reported outcome measures (PROMs) are crucial for accurately capturing patient symptoms and quality of life, which can enhance the robustness of clinical research and improve patient outcomes.

Incorporating PROMs in clinical trials helps reduce observer bias and actively engages patients in the research process, while also providing valuable insights for health service planning.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

How to Include Patient-Reported Outcome Measures in Clinical Trials. McGee, RG.[2021]

A study analyzing adverse drug events (ADEs) related to anti-obesity medications found that phentermine and liraglutide were the most commonly reported drugs, with serious ADEs linked to psychiatric, liver, cardiovascular, and respiratory disorders.

Men were found to be at a higher risk for serious adverse events, especially when using multiple anti-obesity medications or when taking fluoxetine alongside them, indicating the need for careful monitoring and further research on the safety of these treatments.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A nationwide pharmacovigilance investigation on trends and seriousness of adverse events induced by anti-obesity medication. Choi, YJ., Choi, CY., Kim, CU., et al.[2023]

In a review of 28 trials involving orlistat, sibutramine, and rimonabant, rimonabant and orlistat were associated with a significantly higher risk of discontinuation due to adverse events, with rimonabant having the highest risk ratio of 2.00.

The most common reasons for discontinuation were gastrointestinal issues for orlistat (40%) and psychiatric issues for rimonabant (47%), highlighting the importance of monitoring side effects in patients using these medications.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Discontinuation due to adverse events in randomized trials of orlistat, sibutramine and rimonabant: a meta-analysis. Johansson, K., Neovius, K., DeSantis, SM., et al.[2018]

Diet and exercise alone have not proven effective for sustained weight loss in most obese individuals, while surgical interventions can lead to prolonged weight loss but may result in rebound weight gain over time.

The authors propose a new framework for evaluating medical devices aimed at treating obesity, focusing on a benefit-risk assessment to guide the development and approval of these devices, which was discussed at an FDA workshop and advisory panel.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Benefit-risk paradigm for clinical trial design of obesity devices: FDA proposal. Lerner, H., Whang, J., Nipper, R.[2021]

A total of 4941 adverse event (AE) reports were identified for antiobesity medicines in Europe from 2007 to 2014, with over 90% classified as serious, including 159 deaths, highlighting significant safety concerns associated with these medications.

The most commonly reported serious AEs were cardiac (19%) and psychiatric disorders (18%), particularly linked to orlistat and rimonabant, indicating a need for ongoing safety monitoring despite the withdrawal of some products from the market.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Serious adverse events reported for antiobesity medicines: postmarketing experiences from the EU adverse event reporting system EudraVigilance. Aagaard, L., Hallgreen, CE., Hansen, EH.[2018]

In a 12-week study involving 112 overweight Japanese adults, those receiving professional dietary coaching via a smartphone app lost significantly more weight (average -1.4 kg) compared to the control group (-0.1 kg).

Participants who frequently uploaded meal photos to the group chat not only lost more weight but also showed significant improvements in cardiometabolic risk factors, indicating that active engagement in the program enhances health outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Professional dietary coaching within a group chat using a smartphone application for weight loss: a randomized controlled trial. Tanaka, K., Sasai, H., Wakaba, K., et al.[2022]

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]

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]

The OnTrack smartphone app, designed to predict and prevent dietary lapses using machine learning, was found to be feasible and acceptable among 43 participants in an 8-week weight loss program, with high user satisfaction reported.

Participants using OnTrack experienced an average weight loss of 3.13% and a reduction in unplanned dietary lapses, indicating the app's potential effectiveness in supporting weight management efforts.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

OnTrack: development and feasibility of a smartphone app designed to predict and prevent dietary lapses. Forman, EM., Goldstein, SP., Zhang, F., et al.[2023]

References

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Effectiveness of routine provision of feedback from patient-reported outcome measurements for cancer care improvement: a systematic review and meta-analysis. [2023]

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

Can assessing chronic pain outcomes data improve outcomes? [2019]

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Patient-reported outcome measures and supportive care need assessment in patients attending an Australian comprehensive care centre: a multi-method study. [2021]

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How to Include Patient-Reported Outcome Measures in Clinical Trials. [2021]

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A nationwide pharmacovigilance investigation on trends and seriousness of adverse events induced by anti-obesity medication. [2023]

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Discontinuation due to adverse events in randomized trials of orlistat, sibutramine and rimonabant: a meta-analysis. [2018]

9. Germany pubmed.ncbi.nlm.nih.gov

Benefit-risk paradigm for clinical trial design of obesity devices: FDA proposal. [2021]

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Serious adverse events reported for antiobesity medicines: postmarketing experiences from the EU adverse event reporting system EudraVigilance. [2018]

11. New Zealand pubmed.ncbi.nlm.nih.gov

Professional dietary coaching within a group chat using a smartphone application for weight loss: a randomized controlled trial. [2022]

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

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

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

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OnTrack: development and feasibility of a smartphone app designed to predict and prevent dietary lapses. [2023]