Piloting a Reinforcement Learning Tool for Individually Tailoring Just-in-time Adaptive Interventions

The purpose of this pilot study is to conduct a 12-week pilot feasibility study testing usability of the adapt learning tool (AdaptRL)in a weight loss intervention (ADAPT study). Building upon a previous just-in-time adaptive intervention (JITAI), a reinforcement learning tool will generate decision rules regarding which behavior change techniques, in which contexts, are most efficacious for promoting weight loss in a sample of 20 adults.

Study Overview

Status

Not yet recruiting

Intervention / Treatment

Detailed Description

Reinforcement Learning (RL), a type of machine learning, holds promise for addressing the limitations of previous approaches to implementing JITAIs. Adaptive RL applications work by updating information about expected "rewards" (i.e., proximal outcomes) based on the results of sequentially randomized trials. In the context of mHealth, random delivery of intervention messages is referred to as a micro-randomized trial. To realize the potential of adaptive interventions to reduce health disparities in cancer prevention and control, mHealth interventionists first need a user-friendly RL tool that enables use of digital health participant data to continually adapt decision rules guiding highly tailored intervention delivery. This research team has developed a user-friendly, web-based application (AdaptRL) that reads in and analyzes user data (e.g., from Fitbit) in real-time, uses RL to efficiently conduct micro-randomized trials, and creates a JITAI tailored to optimize weight loss for each participant. The objective of this study is to test the feasibility of using the AdaptRL tool in a pilot weight loss study.

Study Type

Interventional

Enrollment (Estimated)

20

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

  • Name: Brooke Nezami, PhD, MA
  • Phone Number: 919-966-5852
  • Email: bnezami@unc.edu

Study Contact Backup

Study Locations

    • North Carolina
      • Chapel Hill, North Carolina, United States, 27514
        • University of North Carolina at Chapel Hill
        • Contact:
        • Contact:
        • Principal Investigator:
          • Brooke Nezami, PhD, MA
        • Sub-Investigator:
          • Nisha Gottfredson, PhD

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 55 years (Adult)

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  1. Age 18-55 years
  2. Body Mass Index of 25-40 kg/m2
  3. Not adhering to the US physical activity guidelines of at least 150 moderate-to-vigorous intensity activity minutes/week
  4. English-speaking and writing
  5. No pre-existing medical condition(s) that preclude adherence to an unsupervised exercise program, diabetes treated with insulin, history of heart attack or stroke, current treatment for cancer, or inability to walk for exercise
  6. Has a smartphone with a data and text messaging plan

Exclusion Criteria:

  1. Current participation in another weight loss, physical activity, nutrition program, or research study
  2. Currently taking weight loss medications
  3. Currently pregnant or planning pregnancy in the next 3 months
  4. Lost 10 or more pounds and kept it off in the last 6 months
  5. History of weight loss surgery
  6. Report a heart condition, chest pain during periods of activity or rest, loss of consciousness, joint or bone problems, medical conditions that could limit exercise, or prescription medicine used for blood pressure or heart condition on the Physical Activity Readiness Questionnaire (PAR-Q)
  7. Type 1 diabetes or currently receiving medical treatment for Type 2 diabetes
  8. Cancer treatment within the past 5 years
  9. Tuberculosis
  10. Health or psychological diagnoses that preclude participation in a prescribed dietary and exercise program, including diagnosis of schizophrenia or bipolar disorder, hospitalization for a psychiatric diagnosis in the past year, a diagnosis of alcohol or substance abuse
  11. Report a past diagnosis of or receiving treatment for The Diagnostic and Statistical Manual of Mental Disorders, fourth edition, text revision (DSM-IV-TR) eating disorder (anorexia nervosa or bulimia nervosa).
  12. Moving out of the area in the next 4 months
  13. Out of town for a week or more during the study period
  14. Another member of the household is a participant or staff member in this trial
  15. Not willing to attend two study visits
  16. Not willing to wear a Fitbit every day

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Health Services Research
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: ADAPT 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 which they will be able to rate (like/dislike), along with weekly personalized feedback, progress graphs, and lessons and resources available on the website.
The intervention is testing the feasibility of a reinforcement learning tool to pull in participants' behavioral data (calories, activity, and weight) and use this data along with participants' past behavioral goal achievements to deliver the type of message that should be most effective for a given participant at a given time. At each decision point (early morning, morning, midday, and evening on a daily basis), the system evaluates which intervention options a participant is eligible to receive, and randomly chooses one intervention option from that list. Then the participant is randomly assigned to either receive or not receive that intervention message (with a 50-50 probability).

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Feasibility (success of using the AdaptRL Tool)
Time Frame: up to 12 weeks
Feasibility as the success of using the AdaptRL Tool will be defined as the mean number of messages delivered per participant per day.
up to 12 weeks
Study engagement
Time Frame: up to 12 weeks
Study engagement will be defined as the percent of person-days in which participants accessed the web app.
up to 12 weeks
Self-monitoring adherence
Time Frame: up to 12 weeks
Self-monitoring adherence will be defined as the percent of person-days in which participants tracked at least one weight loss behavior (tracked calories, wore tracker, or self-weighed).
up to 12 weeks

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Message satisfaction
Time Frame: up to 12 weeks
Message satisfaction will be defined as the percent of delivered messages that were rated as "liked" (compared to dislike or not rated).
up to 12 weeks
Percent weight loss
Time Frame: 12 weeks
Percent weight loss will be defined as weight change from baseline to 12 weeks calculated as a percent from baseline weight.
12 weeks
Moderate-to-vigorous physical activity
Time Frame: Baseline, 12 weeks
Moderate-to-vigorous physical activity will be defined as the change in self-reported weekly minutes of moderate-to-vigorous physical activity as measured by the Paffenbarger Activity Questionnaire from baseline to 12 weeks. The minimum is 0, no maximum. Higher numbers represent higher minutes of weekly moderate-to-vigorous physical activity.
Baseline, 12 weeks
Dietary intake
Time Frame: Baseline, 12 weeks
Dietary intake will be defined as the change in average daily calorie intake as measured by the Automated Self-Administered 24-hour (ASA 24-hour) dietary recalls from baseline to 12 weeks. Daily caloric intake is measured in kcals, with higher numbers indicating higher caloric intake.
Baseline, 12 weeks
Adherence to calorie goal
Time Frame: up to 12 weeks
Adherence to the calorie goal as the percent of person-days in which participants tracked their calories and stayed at or under their calorie goal will be measured by dietary self-monitoring data tracked in the Fitbit app and transmitted via Application Programming Interface (API) to study servers.
up to 12 weeks
Adherence to daily active minutes goal
Time Frame: up to 12 weeks
Adherence to daily active minutes goal, the percent of person-days in which participants met their daily active minute goal, will be measured by activity tracker data tracked in the Fitbit app and transmitted via Application Programming Interface (API) to study servers.
up to 12 weeks
Adherence to daily self-weighing
Time Frame: up to 12 weeks
Adherence to daily self-weighing, the percent of person-days in which participants self-weighed will be measured by Fitbit smart scales and transmitted via Application Programming Interface (API) to study servers.
up to 12 weeks
Adherence to daily self-weighing at the participant-day level
Time Frame: up to 12 weeks
Adherence to daily self-weighing at the participant-day level, the percent of person-days weighed after the message randomization time until the end of the day will be measured by Fitbit smart scales and transmitted via Application Programming Interface (API) to study servers.
up to 12 weeks
Adherence to the daily self-weighing percent of person-days weighed
Time Frame: up to 12 weeks
Adherence to the daily self-weighing percent of person-days weighed the day after the message randomization will be measured by Fitbit smart scales and transmitted via Application Programming Interface (API) to study servers.
up to 12 weeks
Achievement of active minutes goal
Time Frame: up to 12 weeks
Achievement of active minutes goal, percent of person-days met active minutes goal after the message randomization time until the end of the day will be measured by activity tracker data tracked in the Fitbit app and transmitted via Application Programming Interface (API) to study servers.
up to 12 weeks
Achievement of active minutes goal percent of person-days
Time Frame: up to 12 weeks
Achievement of active minutes goal percent of person-days met active minutes goal the day after the message randomization will be measured by activity tracker data tracked in the Fitbit app and transmitted via Application Programming Interface (API) to study servers.
up to 12 weeks
Achievement of calorie goal (at or under goal)
Time Frame: up to 12 weeks
Achievement of calorie goal (at or under goal) percent of person-days met calorie goal after the message randomization time until the end of the day will be measured by dietary self-monitoring data tracked in the Fitbit app and transmitted via Application Programming Interface (API) to study servers.
up to 12 weeks
Achievement of calorie goal (at or under goal) percent of person-days
Time Frame: up to 12 weeks
Achievement of calorie goal (at or under goal) percent of person-days met calorie goal the day after the message randomization will be measured by dietary self-monitoring data tracked in the Fitbit app and transmitted via Application Programming Interface (API) to study servers.
up to 12 weeks

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Brooke Nezami, PhD, MA, University of North Carolina, Chapel Hill

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

April 1, 2024

Primary Completion (Estimated)

December 1, 2024

Study Completion (Estimated)

December 1, 2024

Study Registration Dates

First Submitted

February 20, 2023

First Submitted That Met QC Criteria

February 20, 2023

First Posted (Actual)

March 2, 2023

Study Record Updates

Last Update Posted (Actual)

April 17, 2024

Last Update Submitted That Met QC Criteria

April 15, 2024

Last Verified

April 1, 2024

More Information

Terms related to this study

Other Study ID Numbers

  • 22-0149
  • R21CA260092 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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