{
  "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).",
  "abstract_shown": true,
  "affiliations": [
    "Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, Johns Hopkins University School of Medicine",
    "Division of Pediatrics, Johns Hopkins University School of Medicine",
    "Division of Pulmonary and Critical Care Medicine, Department of Medicine, Johns Hopkins University School of Medicine",
    "Division of Hospital and General Internal Medicine, Department of Medicine, University of Maryland School of Medicine"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Benjamin Lalani"
    },
    {
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        1
      ],
      "name": "Cyd Eaton"
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    {
      "affs": [
        0
      ],
      "name": "Daniel Zade"
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    {
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        2
      ],
      "name": "Kristin Riekert"
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    {
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        3
      ],
      "name": "Nisa Maruthur"
    },
    {
      "affs": [
        0
      ],
      "name": "Adrian Dobs"
    },
    {
      "affs": [
        0
      ],
      "name": "Nestoras Mathioudakis"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/fbs1qvfn6kez6.bib",
  "cited_by": 0,
  "doi": "10.1038/s41746-026-03063-w",
  "fulltext_url": "https://doi.org/10.1038/s41746-026-03063-w",
  "id": "fbs1qvfn6kez6",
  "issns": [
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  "landing_url": "https://doi.org/10.1038/s41746-026-03063-w",
  "language": "en",
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
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  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
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  "pdf_url": "https://www.nature.com/articles/s41746-026-03063-w_reference.pdf",
  "pmcid": "PMC13737000",
  "pmid": "42982853",
  "published": "2026-08-01",
  "publisher": "Nature Portfolio",
  "ris": "https://research.draconitic.com/paper/fbs1qvfn6kez6.ris",
  "sources": [
    {
      "first_seen": "2026-11-08T14:21:02Z",
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      "url": "https://doi.org/10.1038/s41746-026-03063-w"
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  "subjects": [
    {
      "field": "medicine",
      "origin": "lcc:R858-859.7",
      "subfield": "general"
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  ],
  "title": "Patient engagement, acceptability, and preference of artificial intelligence versus human coaching for diabetes prevention",
  "title_text": "Patient engagement, acceptability, and preference of artificial intelligence versus human coaching for diabetes prevention",
  "type": "peer-reviewed",
  "updated_at": "2026-11-09T14:21:21Z",
  "url": "https://research.draconitic.com/paper/fbs1qvfn6kez6",
  "venue": "npj Digital Medicine",
  "versions": []
}