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Peer-reviewedCC BY-NC-ND 4.0npj Digital Medicine

Patient engagement, acceptability, and preference of artificial intelligence versus human coaching for diabetes prevention

  • Benjamin Lalani1
  • Cyd Eaton2
  • Daniel Zade1
  • Kristin Riekert3
  • Nisa Maruthur4
  • Adrian Dobs1
  • Nestoras Mathioudakis1
4 affiliations
  1. 1Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, Johns Hopkins University School of Medicine
  2. 2Division of Pediatrics, Johns Hopkins University School of Medicine
  3. 3Division of Pulmonary and Critical Care Medicine, Department of Medicine, Johns Hopkins University School of Medicine
  4. 4Division of Hospital and General Internal Medicine, Department of Medicine, University of Maryland School of Medicine
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Abstract

Artificial intelligence-powered lifestyle interventions may expand access to behavioral change support, but patient experience remains critical to real-world uptake and effectiveness. In a phase 3 randomized clinical trial of adults with prediabetes and overweight or obesity (N = 368), we compared a fully automated AI-driven diabetes prevention program (DPP) with a CDC-recognized human-coach-based DPP. Participants assigned to the AI-led DPP initiated the intervention sooner (median 11 vs 26 days; p < 0.001) and demonstrated higher and more evenly distributed engagement over 12 months. Acceptability ratings were consistently higher for the human-led DPP across all domains, with the largest differences in satisfaction (p < 0.001). Preference responses also favored human coaching, with 46.5% of AI-assigned participants indicating they would have preferred a human coach compared with 31.5% preferring a fully automated program in the human-led group (p = 0.012). These findings illustrate a trade-off between scalability and perceived quality of experience. Clinical trial registration: ClinicalTrials.gov NCT05056376 (registered September 24, 2021).

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Cite

BibTeXRIS
BibTeX
@article{lalani2026patient,
  title = {{Patient engagement, acceptability, and preference of artificial intelligence versus human coaching for diabetes prevention}},
  author = {Benjamin Lalani and Cyd Eaton and Daniel Zade and Kristin Riekert and Nisa Maruthur and Adrian Dobs and Nestoras Mathioudakis},
  journal = {npj Digital Medicine},
  year = {2026},
  month = aug,
  doi = {10.1038/s41746-026-03063-w},
  url = {https://doi.org/10.1038/s41746-026-03063-w},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Patient engagement, acceptability, and preference of artificial intelligence versus human coaching for diabetes prevention
AU  - Benjamin Lalani
AU  - Cyd Eaton
AU  - Daniel Zade
AU  - Kristin Riekert
AU  - Nisa Maruthur
AU  - Adrian Dobs
AU  - Nestoras Mathioudakis
PY  - 2026
DA  - 2026/08/01
JO  - npj Digital Medicine
DO  - 10.1038/s41746-026-03063-w
UR  - https://doi.org/10.1038/s41746-026-03063-w
AB  - Artificial intelligence-powered lifestyle interventions may expand access to behavioral change support, but patient experience remains critical to real-world uptake and effectiveness. In a phase 3 randomized clinical trial of adults with prediabetes and overweight or obesity (N = 368), we compared a fully automated AI-driven diabetes prevention program (DPP) with a CDC-recognized human-coach-based DPP. Participants assigned to the AI-led DPP initiated the intervention sooner (median 11 vs 26 days; p < 0.001) and demonstrated higher and more evenly distributed engagement over 12 months. Acceptability ratings were consistently higher for the human-led DPP across all domains, with the largest differences in satisfaction (p < 0.001). Preference responses also favored human coaching, with 46.5% of AI-assigned participants indicating they would have preferred a human coach compared with 31.5% preferring a fully automated program in the human-led group (p = 0.012). These findings illustrate a trade-off between scalability and perceived quality of experience. Clinical trial registration: ClinicalTrials.gov NCT05056376 (registered September 24, 2021).
SN  - 2398-6352
ER  -