# Effectiveness of Digital Versus In-Person Diabetes Prevention Programs

> **NIH NIH R01** · JOHNS HOPKINS UNIVERSITY · 2020 · $733,116

## Abstract

1 PROJECT SUMMARY
 Millions of U.S. adults living with prediabetes, a high risk state for future type 2 diabetes, do not receive
appropriate lifestyle counseling to lower their risk of type 2 diabetes. Mobile health (mHealth) technologies
represent a potential scalable solution to address this far-reaching problem. The objective of this project is to
compare the real-world effectiveness of a digital diabetes prevention program (dDPP) to standard of care in-
person diabetes prevention programs (ipDPPs). This study will test a novel, fully-automated digital health
platform (Sweetch Health, Ltd.) that uses artificial intelligence technology to provide just-in-time and adaptive
lifestyle change coaching for prediabetic adults. Preliminary evidence from feasibility or observational studies
suggests that JITAIs, which are often delivered via smartphone apps by virtue of their ability to provide
continuous self-monitoring and feedback, can be effective. However, it is currently not known whether dDPPs
that deliver a JITAI are as effective as ipDPPs in improving health outcomes in patients with prediabetes, a
susceptible patient population that is positioned to benefit from such an intervention.
 The overarching goal of this project, therefore, is to compare the effectiveness of the Sweetch digital
diabetes prevention program (dDPP) to real-world in-person diabetes prevention programs (ipDPPs) for
promoting weight loss, increasing physical activity, and reducing hemoglobin A1C in prediabetic adults. The
proposed study addresses an evidence gap in the science of chronic disease prevention and health behavior
change and is supported by promising short-term results from a previous pilot trial conducted by our team.
Building on our previous study and leveraging the collective expertise of our multidisciplinary study team, we
will conduct a randomized controlled trial of 382 overweight/obese, prediabetic adults ages 18-75 with 6 and 12
month follow-up visits: Arm 1 (N=191) will receive the fully automated Sweetch digital health kit (“dDPP” arm)
and Arm 2 (N=191) will be referred to a local CDC-recognized ipDPP. Both arms will have physical activity
measured serially during the trial using actimetry at baseline and 2 month intervals. We hypothesize that the
dDPP will be more effective than the ipDPP for the outcomes of weight loss, physical activity, and lowering of
hemoglobin A1C at 6 months, with sustained effects at 12 months. We further hypothesize that the overall
engagement and acceptability will be greater in the dDPP, and that the superiority of the dDPP on clinical
outcomes will be mediated by higher engagement in this arm.
 This project will advance chronic disease prevention and behavioral science research by elucidating the
extent to which fully-automated digital interventions using artificial intelligence technology can deliver effective,
scalable, sustainable, and cost-effective health-promoting behavioral change interventions in high-risk
popula...

## Key facts

- **NIH application ID:** 10034797
- **Project number:** 1R01DK125780-01
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** NESTORAS N MATHIOUDAKIS
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $733,116
- **Award type:** 1
- **Project period:** 2020-09-15 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10034797

## Citation

> US National Institutes of Health, RePORTER application 10034797, Effectiveness of Digital Versus In-Person Diabetes Prevention Programs (1R01DK125780-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10034797. Licensed CC0.

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