Reinforcement Learning in Diabetes Mellitus Trial (REINFORCE)

Optimizing Message Framing for Healthy Habits for Patients With Type 2 Diabetes - Phase II (Pragmatic Trial)

Reinforcement learning is an advanced analytic method that discovers each individual's pattern of responsiveness by observing their actions and then implements a personalized strategy to optimize individuals' behaviors using trial and error. The goal of this pilot study is to develop and test a novel reinforcement learning-enhanced text messaging program to support medication adherence in patients with type 2 diabetes. Type 2 diabetes is an optimal condition in which to test this program, as it is one of the most prevalent chronic conditions in the US adult population and requires most patients to be on daily or twice daily doses of medications. This pilot study will be a parallel randomized pragmatic trial comparing medication adherence and clinical outcomes for adults aged 18-84 with type 2 diabetes who are prescribed 1-3 daily oral medications for this disease. Participants will be randomized to one of two arms for the duration of the study period: (1) a reinforcement learning intervention arm with up to daily, tailored text messages based on time-varying treatment-response patterns; or (2) a control arm with up to daily, un-tailored text messages. Our outcomes of interest will be medication adherence, as measured by electronic pill bottles, and HbA1c levels.

Study Overview

• Status: Completed
• Conditions: Diabetes Mellitus, Type 2; Medication Adherence
• Intervention / Treatment: Behavioral: Reinforcement Learning

Detailed Description

The goal of this pilot study is to develop and test a novel reinforcement learning-enhanced text messaging program to support medication adherence in patients with type 2 diabetes. This pilot study will be a parallel randomized pragmatic trial comparing medication adherence and clinical outcomes for adults aged 18-84 with type 2 diabetes who are prescribed 1-3 daily oral medications for this disease. Participants will be randomized to one of two arms for the duration of the study period: 1) a reinforcement learning intervention arm with up to daily, tailored text messages based on time-varying treatment response patterns, or 2) a control arm with up to daily, untailored text messages. Our outcomes of interest will be medication adherence, as measured by electronic pill bottles, and HbA1c levels.

• Study Type: Interventional
• Enrollment (Actual): 60
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Massachusetts
    • Boston, Massachusetts, United States, 02120
      • Brigham and Women's Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 84 years (ADULT, OLDER_ADULT)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion criteria:

• Age between 18-84 years
• Diagnosed with type 2 diabetes mellitus (T2DM) and are prescribed between 1-3 daily oral medications for this disease
• Currently have a smartphone with a data plan or WiFi at home
• HbA1c level ≥7.5%
• Basic working knowledge of English
• Willing and able to set up the platform and adhere to study procedures
• Either not currently using a pillbox or willing to use electronic pill bottles (EDMs) for diabetes medications for the duration of the study

Exclusion criteria:

• Patients with active enrollment in another diabetes trial within Mass General Brigham
• Patients who receive daily assistance with taking their medications at home
• Patients who are unable to receive text messages for more than 3 days in a row during the study period

Study Plan

How is the study designed?

Design Details

• Primary Purpose: HEALTH_SERVICES_RESEARCH
• Allocation: RANDOMIZED
• Interventional Model: PARALLEL
• Masking: DOUBLE

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
EXPERIMENTAL: Reinforcement Learning Intervention Arm; Up to daily, tailored text messages.	Behavioral: Reinforcement Learning; Participants in the intervention arm will receive up to daily, tailored text messages based on their electronic pill bottle-measured adherence. Given the participants' baseline characteristics and time-varying responses to the messages, a reinforcement learning algorithm will deliver different text messages and adapt over time to determine which type of messaging works best for each individual participant.
NO_INTERVENTION: Control Arm; Up to daily, untailored text messages.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Medication Adherence	Medication adherence to type 2 diabetes oral medications (averaged) as measured by the number of dates and times of pillbottle openings in the electronic pill bottles	6 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Glycemic Control	Change in glycated hemoglobin A1c from baseline to end of the 6-month follow-up	6 months

Collaborators and Investigators

• Sponsor: Brigham and Women's Hospital
• Collaborators: National Institute on Aging (NIA)

Publications and helpful links

General Publications

• Lauffenburger JC, Yom-Tov E, Keller PA, McDonnell ME, Bessette LG, Fontanet CP, Sears ES, Kim E, Hanken K, Buckley JJ, Barlev RA, Haff N, Choudhry NK. REinforcement learning to improve non-adherence for diabetes treatments by Optimising Response and Customising Engagement (REINFORCE): study protocol of a pragmatic randomised trial. BMJ Open. 2021 Dec 3;11(12):e052091. doi: 10.1136/bmjopen-2021-052091.

Study record dates

Study Major Dates

• Study Start (ACTUAL): February 4, 2021
• Primary Completion (ACTUAL): January 4, 2022
• Study Completion (ACTUAL): January 28, 2022

Study Registration Dates

• First Submitted: July 13, 2020
• First Submitted That Met QC Criteria: July 13, 2020
• First Posted (ACTUAL): July 16, 2020

Study Record Updates

• Last Update Posted (ACTUAL): February 8, 2023
• Last Update Submitted That Met QC Criteria: February 6, 2023
• Last Verified: February 1, 2023

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Glucose Metabolism Disorders; Metabolic Diseases; Endocrine System Diseases; Diabetes Mellitus; Diabetes Mellitus, Type 2
• Other Study ID Numbers: 2020P000846; P30AG064199-01 (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