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REVIEW article

Front. Clin. Diabetes Healthc.

Sec. Diabetes Therapies

Volume 6 - 2025 | doi: 10.3389/fcdhc.2025.1562108

This article is part of the Research Topic Digital Technology in the Management and Prevention of Diabetes: Volume II View all 13 articles

Consumer-Oriented Review of Digital Diabetes Prevention Programs: Insights from the CDC's Diabetes Prevention Recognition Program

Provisionally accepted
  • Johns Hopkins Medicine, Johns Hopkins University, Baltimore, Maryland, United States

The final, formatted version of the article will be published soon.

    Prediabetes is highly prevalent and significantly increases the risk of type 2 diabetes. While access to proven interventions like the Diabetes Prevention Program (DPP) has historically been limited, digital DPPs (dDPPs) present a promising and scalable option. With the recent growth of dDPP offerings and potential variability across platforms, access to accurate and clear information is crucial for individuals seeking diabetes prevention options. This review provides an overview of the dDPP landscape and characterizes the "direct-to-consumer" information available--or lacking--for patients choosing a dDPP.We identified dDPPs through the CDC Diabetes Prevention Recognition Program (DPRP) Registry. Data were extracted from three sources available to consumers: the CDC DPRP Registry, the CDC "Find a Lifestyle Program" Website, and program-specific websites. Extracted data included CDC recognition status, intended audience, available languages, program features (e.g., artificial intelligence, integration with smart devices), website availability and functionality, demonstrations of credibility (e.g., ADA endorsement), clinical performance metrics (e.g., average weight loss), and user experience factors (e.g., satisfaction). Descriptive statistics were used to summarize extracted data.A total of 97 dDPPs were included in the review, with most in the early stages of CDC recognition. Only 35% of dDPPs listed in the CDC registry had functional websites, though additional websites were identified through manual searches. Program-specific features included AI-driven health recommendations, device integration (e.g., digital scales and activity trackers), nutrition tracking tools, and telehealth platforms. Nearly half of the dDPPs reported clinical performance metrics such as weight loss and A1C outcomes. User experience details were often presented through patient testimonials and satisfaction scores. Notably, many programs required users to provide personal information to access additional information.We found that available dDPPs vary significantly in their features, designs, and structures, reflecting a diverse and evolving landscape of diabetes prevention options. Concurrently, many dDPPs lack accessible information due to missing or incomplete websites. Centralized sources of information provided by the CDC are also insufficient, with discrepancies and gaps that hinder transparency and consumer decision-making. Addressing these issues through enhanced program visibility and improved centralized databases will be critical to optimizing the reach and impact of dDPPs.

    Keywords: prediabetes, diabetes, lifestyle intervention, Digital Health, Diabetes Prevention, cdc, mHealth, artificial intelligence

    Received: 06 Feb 2025; Accepted: 25 Mar 2025.

    Copyright: © 2025 Lalani, Shim, Vadini, Valdez, Zade and Mathioudakis. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Nestoras Mathioudakis, Johns Hopkins Medicine, Johns Hopkins University, Baltimore, 21218, Maryland, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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