Diabetes Mellitus, Type 2REINFORCE2NCT05742685
Refinement and Adaption of Reinforcement Learning to Personalize Behavioral Messaging for Healthy Habits
A study testing Reinforcement Learning in people with Diabetes Mellitus, Type 2 and Medication Adherence, run by Brigham and Women's Hospital at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 84 years
- Conditions the study is for
- Diabetes Mellitus, Type 2, Medication Adherence
- What is being tested?
- Reinforcement Learning
- Type of treatment
- Pill or oral medicine, Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 28 participants
- Where
- 1 siteUnited States
- Study dates
- 23 Aug 2023to 17 Dec 2025
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 84 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Diagnosis of Type 2 Diabetes Mellitus (T2DM)
- Prescribed between 1-3 daily oral medications for diabetes
- Most recent HbA1c level of 7% or greater
- Suboptimal adherence, defined by proportion of days covered (PDC) < 0.90 based on chart review
- Must have a smartphone for which they are the sole user
- Must have a basic working knowledge of English or Spanish
Who cannot join
- Currently using a pillbox and/or not willing to use electronic pill bottles for 6 months
- Receive help at home on a daily basis with taking medications
Trial locations and contacts
1 site in 1 country.
About this study
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 the proposed research is to refine, adapt and perform efficacy testing of a novel reinforcement learning-based text messaging intervention to support medication adherence for patients with type 2 diabetes within a community health center setting. This study will be a parallel randomized pragmatic trial comparing medication adherence and clinical outcomes for adults in a community setting 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. Outcomes of interest will be medication adherence, as measured by electronic pill bottles, and HbA1c levels over 6 months.
Read the detailed description
The goal of the proposed research is to refine, adapt and perform efficacy testing of a novel reinforcement learning-based text messaging intervention to support medication adherence for patients with type 2 diabetes within a community setting. Type 2 diabetes is an optimal condition in which to refine 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 study will be a parallel randomized pragmatic trial comparing medication adherence and clinical outcomes for adults in a community setting 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. Outcomes of interest will be medication adherence, as measured by electronic pill bottles, and HbA1c levels over 6 months.
- Conditions
- Diabetes Mellitus, Type 2, Medication Adherence
- Being tested
- Reinforcement Learning
- Medical subject headings
- Diabetes Mellitus, Type 2, Medication Adherence
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Reinforcement LearningBehavioural
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.
| Study group | Role | What they receive |
|---|---|---|
| Reinforcement Learning Intervention Arm | Experimental | Up to daily, tailored text messages. Receives: Behavioral: Reinforcement Learning |
| Control Arm | No intervention | Up to daily, untailored text messages. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Diabetes medication adherence
Proportion of correct doses recorded by electronic pill bottles in the 6-month follow-up period, averaged across study medications
Measured: 6 months
Secondary outcomes (1)
Glycemic control
Change between baseline HbA1c used for identification and the 6-month intervention period, using laboratory values in the EHR
Measured: 6 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Feb 2023
- Study start23 Aug 2023
- Primary completion17 Dec 2025
- Study completion17 Dec 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Diabetes Mellitus, Type 2Studies of the same condition, open and under way.
- More trials run by Brigham and Women's HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind
- Who is masked
- Investigator, Outcomes assessor
- Enrolment
- 28 participants (actual)
Sponsor and investigators
- Lead sponsor
- Brigham and Women's Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- Boston Medical Center, National Institute on Aging (NIA)
- Responsible party
- Principal investigator, Julie Lauffenburger, Brigham and Women's Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05742685
- Sponsor's protocol ID
- 2023P000293
- Other IDs
- P30AG064199-04
- Acronym
- REINFORCE2
- Status last verified
- Dec 2025
- First submitted
- 15 Feb 2023
- Last updated
- 20 Mar 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 20 Mar 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Refinement and Adaption of Reinforcement Learning to Personalize Behavioral Messaging for Healthy Habits
- ClinicalTrials.gov ID
- NCT05742685
- Acronym / sponsor ID
- REINFORCE2 / 2023P000293
- Conditions
- Diabetes Mellitus, Type 2, Medication Adherence
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 28 participants (actual)
- Lead sponsor
- Brigham and Women's HospitalUniversity, hospital or other
- Collaborators
- Boston Medical Center, National Institute on Aging (NIA)
- Study start
- 23 Aug 2023 (actual)
- Primary completion
- 17 Dec 2025 (actual)
- Study completion
- 17 Dec 2025 (actual)
- First posted
- 24 Feb 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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 the proposed research is to refine, adapt and perform efficacy testing of a novel reinforcement learning-based text messaging intervention to support medication adherence for patients with type 2 diabetes within a community health center setting. This study will be a parallel randomized pragmatic trial comparing medication adherence and clinical outcomes for adults in a community setting 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. Outcomes of interest will be medication adherence, as measured by electronic pill bottles, and HbA1c levels over 6 months.
Detailed description
The goal of the proposed research is to refine, adapt and perform efficacy testing of a novel reinforcement learning-based text messaging intervention to support medication adherence for patients with type 2 diabetes within a community setting. Type 2 diabetes is an optimal condition in which to refine 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 study will be a parallel randomized pragmatic trial comparing medication adherence and clinical outcomes for adults in a community setting 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. Outcomes of interest will be medication adherence, as measured by electronic pill bottles, and HbA1c levels over 6 months.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (investigator, outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Reinforcement Learning Intervention Arm | Experimental | Behavioral: Reinforcement LearningUp to daily, tailored text messages. |
| Control Arm | No intervention | –Up to daily, untailored text messages. |
Who may qualify
- Ages
- 18 to 84 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (6 listed)
- Diagnosis of Type 2 Diabetes Mellitus (T2DM)
- Prescribed between 1-3 daily oral medications for diabetes
- Most recent HbA1c level of 7% or greater
- Suboptimal adherence, defined by proportion of days covered (PDC) < 0.90 based on chart review
- Must have a smartphone for which they are the sole user
Key exclusion criteria (2 listed)
- Currently using a pillbox and/or not willing to use electronic pill bottles for 6 months
- Receive help at home on a daily basis with taking medications
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Reinforcement LearningParticipants 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. | Behavioural | Reinforcement Learning Intervention Arm |
Primary outcome
Diabetes medication adherence
Time frame: 6 months
Proportion of correct doses recorded by electronic pill bottles in the 6-month follow-up period, averaged across study medications
1 secondary outcome
Glycemic control
Time frame: 6 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 20 Mar 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Reinforcement Learning in people with Diabetes Mellitus, Type 2 and Medication Adherence, run by Brigham and Women's Hospital at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 20 Mar 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diabetes medication adherence (time frame: 6 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 20 Mar 2026.