REINFORCE: Reinforcement Learning in Diabetes Mellitus Trial
Study Details
Study Description
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.
Condition or Disease | Intervention/Treatment | Phase |
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N/A |
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 Design
Arms and Interventions
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. |
Outcome Measures
Primary Outcome Measures
- Medication adherence [6 months]
Medication adherence to one to three type 2 diabetes treatments as measured by electronic pill bottles
Secondary Outcome Measures
- Glycemic control [6 months]
Change in glycosylated hemoglobin A1c from baseline to follow-up
Eligibility Criteria
Criteria
Inclusion criteria:
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Age between 18-84 years
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Diagnosed with type 2 diabetes mellitus (T2DM) and are prescribed between 1-3 daily oral medications for this disease
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Currently have a smartphone with a data plan or WiFi at home
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HbA1c level ≥7.5%
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Basic working knowledge of English
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Willing and able to set up the platform and adhere to study procedures
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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:
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Patients with active enrollment in another diabetes trial within Mass General Brigham
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Patients who receive daily assistance with taking their medications at home
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Patients who are unable to receive text messages for more than 3 days in a row during the study period
Contacts and Locations
Locations
Site | City | State | Country | Postal Code | |
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1 | Brigham and Women's Hospital | Boston | Massachusetts | United States | 02120 |
Sponsors and Collaborators
- Brigham and Women's Hospital
- National Institute on Aging (NIA)
Investigators
None specified.Study Documents (Full-Text)
More Information
Publications
None provided.- 2020P000846
- P30AG064199-01