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

NCT05742685 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 28

Last updated 2026-03-20

No results posted yet for this study

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.

Conditions

  • Diabetes Mellitus, Type 2
  • Medication Adherence

Interventions

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.

Sponsors & Collaborators

  • Boston Medical Center

    collaborator OTHER

  • National Institute on Aging (NIA)

    collaborator NIH

  • Brigham and Women's Hospital

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
DOUBLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Max Age
84 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-08-23
Primary Completion
2025-12-17
Completion
2025-12-17

Countries

  • United States

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05742685 on ClinicalTrials.gov