Reinforcement Learning in Diabetes Mellitus Trial

NCT ID: NCT04473326

Last Updated: 2023-02-08

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 60 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2021-02-04
• Study Completion Date: 2022-01-28

Brief Summary

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.

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.

Conditions

Diabetes Mellitus, Type 2; Medication Adherence

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: HEALTH_SERVICES_RESEARCH
• Blinding Strategy: DOUBLE

Study Groups

Reinforcement Learning Intervention Arm

Up to daily, tailored text messages.

Group Type: EXPERIMENTAL

Reinforcement Learning

Intervention Type: BEHAVIORAL

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.

Control Arm

Up to daily, untailored text messages.

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

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.

Intervention Type: BEHAVIORAL

Eligibility Criteria

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

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 84 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

National Institute on Aging (NIA)

NIH

Sponsor Role: collaborator

Brigham and Women's Hospital

OTHER

Sponsor Role: lead

Responsible Party

Julie Lauffenburger

Assistant Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

Brigham and Women's Hospital

Boston, Massachusetts, United States

Countries

United States

References

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.

Reference Type: DERIVED

PMID: 34862289 (View on PubMed)

Provided Documents

Document Type: Study Protocol and Statistical Analysis Plan

View Document

Document Type: Informed Consent Form

View Document

Other Identifiers

P30AG064199-01

Identifier Type: NIH

Identifier Source: secondary_id

View Link

2020P000846

Identifier Type: -

Identifier Source: org_study_id