Weight loss in a digital app-based diabetes prevention program powered by artificial intelligence.
Open accessAbstract
Objective: The National Diabetes Prevention Program (DPP) reduces diabetes incidence and associated medical costs but is typically staffing-intensive, limiting scalability. We evaluated an alternative delivery method with 3933 members of a program powered by conversational Artificial Intelligence (AI) called Lark DPP that has full recognition from the Centers for Disease Control and Prevention (CDC). Methods: We compared weight loss maintenance at 12 months between two groups: 1) CDC qualifiers who completed ≥4 educational lessons over 9 months (n = 191) and 2) non-qualifiers who did not complete the required CDC lessons but provided weigh-ins at 12 months (n = 223). For a secondary aim, we removed the requirement for a 12-month weight and used logistic regression to investigate predictors of weight nadir in 3148 members. Results: CDC qualifiers maintained greater weight loss at 12 months than non-qualifiers (M = 5.3%, SE = .8 vs. M = 3.3%, SE = .8; p = .015), with 40% achieving ≥5%. The weight nadir of 3148 members was 4.2% (SE = .1), with 35% achieving ≥5%. Male sex ( β = .11; P = .009), weeks with ≥2 weigh-ins ( β = .68; P < .0001), and days with an AI-powered coaching exchange ( β = .43; P < .0001) were associated with a greater likelihood of achieving ≥5% weight loss. Conclusions: An AI-powered DPP facilitated weight loss and maintenance commensurate with outcomes of other digital and in-person programs not powered by AI. Beyond CDC lesson completion, engaging with AI coaching and frequent weighing increased the likelihood of achieving ≥5% weight loss. An AI-powered program is an effective method to deliver the DPP in a scalable, resource-efficient manner to keep pace with the prediabetes epidemic.
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AI-based DPP studies reported to date have been single-group or other nonrandomized designs.
“The AI-based DPP studies reported to date have been single-group or other nonrandomized designs.12,20,21”
From An AI-Powered Lifestyle Intervention vs Human Coaching in the Diabetes Prevention Program: A Randomized Clinical Trial (2025) · cites this paper as [20]
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Hadžidedić, S., Wang, J., Adeyemo, V. E., Sanders, G., & Westermann, G. (2026) · Smart innovation, systems and technologies · doi:10.1007/978-3-032-21376-1_19
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The Role of Artificial Intelligence in Diabetes Care
PATANGE, S. A., Wallace, A., & Gupta, S. (2026) · Springer eBooks · doi:10.1007/978-3-032-24854-1_19
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Digital Health in Obesity Care: Current Evidence, Challenges, and Future Directions
Pagoto, S., & Bannor, R. (2026) · Current Obesity Reports · doi:10.1007/s13679-026-00757-w
Applications of artificial intelligence in personalized nutrition interventions
Zhang, Y., Feng, M., Xue, Q., Ma, R., & Liu, F. (2026) · Frontiers in Nutrition · doi:10.3389/fnut.2026.1974199
KHOZHAMKUL, F., & SHARMAN, A. (2026) · Vestnik · doi:10.53065/kaznmu.2026.78.3.004
AI-Driven Lifestyle Interventions for Reducing Diabetes Risk: Systematic Review
Ekwunife, O. I., Nauta, T., Fraser, R. A., Campbell, J. A., Aidoo-Frimpong, G. A., Walker, R. J., & Egede, L. E. (2026) · Journal of Medical Internet Research · doi:10.2196/104940
- Authors
- Graham, S. A., Pitter, V., Hori, J. H., Stein, N., & Branch, O. H.
- Affiliations
- Lark Health, Mountain View, CA, USA
- Corresponding author
- Graham, Sarah A.
- Venue
- DIGITAL HEALTH
- Publisher
- SAGE Publications
- Published
- 2022-01
- Volume
- 8
- Pages
- 205520762211306
- ISSN
- 2055-2076 (ISSN-L)
- PMC
- PMC9551332
- OpenAlex
- W4306247928
- Cited by
- 43
- References
- 55
- Citations by year
- 2026: 13 · 2025: 13 · 2024: 10 · 2023: 7
- FWCI
- 8.61
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Digital Health (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- Diabetes Prevention Program, National Diabetes Prevention Program, artificial intelligence, weight loss maintenance, prediabetes, digital health interventions, predictors of weight loss, weigh-in
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