Refinement and Adaption of Reinforcement Learning to Pers... | NCT05742685

Studies
Refinement and Adaption of Reinforcement Learning to Personalize Behavioral Messaging for Healthy Habits

NCT05742685

Sponsor

Brigham and Women's Hospital

Status

Completed

Last Update Posted

Mar 20, 2026Actual

Enrollment

28Actual

Phase

Not Applicable

Conditions

Diabetes Mellitus, Type 2
Medication Adherence

Interventions

Reinforcement Learning

Countries

United States

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

ID	Type	Description	Link
P30AG064199-04	U.S. NIH Grant/Contract		View source

Status Module

Record Verification Date

Dec 2025

Overall Recruitment Status or Expanded Access Status

Completed

Last Known Status

Not provided

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Aug 23, 2023Actual

Primary Completion Date

Dec 17, 2025Actual

Completion Date

Dec 17, 2025Actual

First Submitted Date

Feb 15, 2023

First Submission Date that Met QC Criteria

Feb 23, 2023

First Posted Date

Feb 24, 2023Actual

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

Mar 18, 2026

Last Update Posted Date

Mar 20, 2026Actual

Sponsor/Collaborators Module

Responsible Party, by Official Title

Julie Lauffenburger, Assistant Professor, Brigham and Women's HospitalPrincipal Investigator

Lead Sponsor

Brigham and Women's HospitalOTHER

Collaborators

Name	Class
Boston Medical Center	OTHER
National Institute on Aging (NIA)	NIH

Oversight Module

Has Data Monitoring Committee (DMC)

Is FDA Regulated Drug

Is FDA Regulated Device

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

Not provided

FDAAA801 Violation

Not provided

Description Module

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 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.

Design Module

Study Type

Interventional

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Not provided

Target Follow-Up Duration

Not provided

Phases

Not Applicable

Interventional Study Design

Allocation

Biospecimen

No data available

No data is available for this block.

Enrollment

28Actual

Arms/Interventions Module

Arm Groups

Label	Type	Description	Intervention Names
Reinforcement Learning Intervention Arm	Experimental	Up to daily, tailored text messages.	Behavioral: Reinforcement Learning
Control Arm	No Intervention	Up to daily, untailored text messages.

Interventions

Name	Type	Description	Arm Group Labels	Other Names
Reinforcement Learning	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.

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
Diabetes medication adherence	Proportion of correct doses recorded by electronic pill bottles in the 6-month follow-up period, averaged across study medications	6 months

Secondary Outcomes

Measure	Description	Time Frame
Glycemic control	Change between baseline HbA1c used for identification and the 6-month intervention period, using laboratory values in the EHR	6 months

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

Inclusion Criteria:

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

Exclusion Criteria:

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

Accepts Healthy Volunteers

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

18 Years

Maximum Age

84 Years

Standard Ages

AdultOlder Adult

Study Population

Not provided

Sampling Method

Not provided

Contacts/Locations Module

Central Contacts

Not provided

Overall Officials

Not provided

Locations

Facility	Status	City	State	ZIP	Country	Contacts
Boston Medical Center		Boston	Massachusetts	02118	United States

IPD Sharing Statement Module

Plan to Share IPD

Description

Not provided

Types

Not provided

Time Frame

Not provided

Access Criteria

Not provided

URL

Not provided

Condition Browse Module

MeSH Terms

ID	Term
D003924	Diabetes Mellitus, Type 2
D055118	Medication Adherence

Ancestor Terms

ID	Term
D003920	Diabetes Mellitus
D044882	Glucose Metabolism Disorders
D008659	Metabolic Diseases
D009750	Nutritional and Metabolic Diseases

Browse Leaves

Not provided

Browse Branches

Not provided

Intervention Browse Module

MeSH Terms

ID	Term
D000098408	Reinforcement Machine Learning

Ancestor Terms

ID	Term
D000069550	Machine Learning
D001185	Artificial Intelligence
D000465	Algorithms
D055641	Mathematical Concepts

Browse Leaves

Not provided

Browse Branches

Not provided