Viewing Study NCT05344859


Ignite Creation Date: 2025-12-24 @ 2:46 PM
Ignite Modification Date: 2025-12-26 @ 1:33 PM
Study NCT ID: NCT05344859
Status: COMPLETED
Last Update Posted: 2025-12-17
First Post: 2022-04-18
Is NOT Gene Therapy: True
Has Adverse Events: False

Brief Title: GODART Pilot and Feasibility
Sponsor: University of Alabama at Birmingham
Organization:

Study Overview

Official Title: A Feasibility and Pilot Trial of Gamification and AI-based Health Coaching Intervention Components for Diabetes Management Using the GODART Platform
Status: COMPLETED
Status Verified Date: 2025-12
Last Known Status: None
Delayed Posting: No
If Stopped, Why?: Not Stopped
Has Expanded Access: False
If Expanded Access, NCT#: N/A
Has Expanded Access, NCT# Status: N/A
Acronym: GODART-P&F
Brief Summary: The purpose of this study is to pilot and assess the feasibility of implementing an artificial intelligence-assisted individualized lifestyle modification intervention for glycemic control in rural populations, which can be delivered even with regular landline phone service. This study will provide us with the knowledge to plan a well-powered optimization trial in the future to develop an optimal (low-cost) intervention package that can be delivered in a sustainable manner to the rural portions of America.
Detailed Description: Evidence-based guidelines for type 2 diabetes mellitus (T2DM) management aimed at glycemic control (reduced hemoglobin A1c) include a combination of diet, physical activity (PA), glucose monitoring, and medication adherences. However, the majority of individuals with T2DM are unable to follow these guidelines due to a lack of consistent health behavior counseling offered in the primary care setting. This problem is amplified in remote rural communities within the U.S. In response, this project aims to create an optimized telehealth-based intervention - Gamified Optimized Diabetes management with Artificial Intelligence-powered Rural Telehealth (GODART). GODART is grounded in the social cognitive theory and will serve as an automated behavior-monitoring and telecoaching platform. At the core, GODART is an automated conversational-style behavior-monitoring system using natural language-understanding technologies. In this project, we propose to pilot and feasibility test the various components of GODART by leveraging a multiphase optimization strategy (MOST). MOST is an efficient and rigorous resource-management and continuous- improvement framework for developing optimized interventions. Our proposal focuses on the MOST preparatory phase and will use full factorial experimentation. We will pilot and assess the feasibility of and evaluate two different intervention components, with two levels in each of the groups, yielding four experimental conditions. These groups will test the effect of (i) a fixed vs. adaptive (gamified) rewards program and (ii) automated vs. human-delivered weekly health coaching. We will end the project with exit interviews conducted with a subset of participants. Study findings will help us learn the feasibility of delivering such an intervention and its preliminary effectiveness in reducing HbA1c, leading to adequately powered confirmatory effectiveness studies.

Participants will be enrolled in the study in 2 phases:

Phase 1-The Feasibility Phase: Up to 16 participants will be enrolled in this phase of the study. Participants will be in the study for a duration of 14 days. This phase of the study is conducted to access the feasibility, usability, and accessibility of the GODART platform, before the actual intervention phase.

Phase 2- Intervention Phase: 88 participants will be enrolled in this phase of the study for a duration of 6 months.

Study Oversight

Has Oversight DMC: False
Is a FDA Regulated Drug?: False
Is a FDA Regulated Device?: False
Is an Unapproved Device?: None
Is a PPSD?: None
Is a US Export?: None
Is an FDA AA801 Violation?:

Secondary ID Infos

Secondary ID Type Domain Link View
5R01DK129378-03 NIH None https://reporter.nih.gov/quic… View
5R01DK129378-02 NIH None https://reporter.nih.gov/quic… View