{
  "abstract": "The use of wearable technology for digital phenotyping has been limited in gerotherapeutic trials. Thus, it is important to identify insights into the operational feasibility of adopting accelerometers for digital phenotyping in gerotherapeutic trials, participant adherence to device and intervention, and study dropout risk, particularly in middle-aged adults. This exploratory analysis utilized data from 120 generally healthy, middle-aged adults participating in the Alpha-ketoglutarate (AKG) supplementation and BiologicaL agE in middle-aged adults (ABLE) double-blind, randomized, placebo-controlled trial (ClinicalTrials.gov identifier: NCT05706389). Participants were instructed to wear an ActiGraph wGT3X-BT accelerometer for seven days at four study visits, adhering to a six-month 1 g/day oral AKG supplement regimen with a three-month follow up. Device operational concerns, accelerometer wear behaviour, device wear and supplement use adherence, and study dropouts were evaluated. Associations between device wear (time or adherence) and dropout were analysed using Cox proportional hazards models using study visit as the time scale to account for when participants dropped out from the study. Participants (mean age 50.6 ± 6.0 years, 50% female, n = 59 AKG, n = 61 placebo) showed high adherence: median accelerometer wear was 24 hours per day, > 80% achieved ≥ 4 valid days per visit, and supplement use adherence >90%, with minimal device-related operational concerns across all four visits. Overall study dropout was 17%. In Cox models across study visits, one minute higher in wearing time (hazard ratio (HR): 0.998; 95% confidence interval (CI): 0.997–0.999) and being male (HR: 0.208; CI: 0.065–0.663) were significantly associated with lower dropout risk. Accelerometer deployment proved highly feasible in this gerotherapeutic trial with middle-aged adults. Higher device wearing time and being male were significantly associated with lower study dropout, informing strategies to enhance future trial success. Author summary: In our research, we set out to understand how practical it is to use wearable motion sensors to track health patterns in studies focused on healthy aging. While these digital tools offer a wealth of information, we haven’t yet seen them widely used in trials testing treatments that target the aging process. We followed 120 healthy middle-aged adults who were taking a daily supplement called alpha-ketoglutarate, which is being studied for its potential to lower biological age. Over nine months, we asked participants to wear a small activity tracker for one week each at four timepoints. We found that using these devices was highly successful: participants wore them nearly 24 hours a day and remained very consistent with their supplement routine. Our analysis also revealed that people who wore their trackers for longer periods, as well as male participants, were less likely to drop out of the study. This is a vital insight because keeping participants engaged is one of the biggest hurdles in medical research. By proving that this technology is both reliable and well-accepted, our work shows that digital tracking can provide a more continuous, “real-world” look at how new treatments affect us, helping us design more effective longevity interventional trials in the future.",
  "abstract_shown": true,
  "affiliations": [
    "Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore",
    "NUS Academy for Healthy Longevity, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore",
    "Centre for Healthy Longevity, National University Health System (NUHS), Singapore, Singapore",
    "Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore",
    "Department of Human Movement Sciences, @AgeAmsterdam, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, the Netherlands"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Jessica K. Lu"
    },
    {
      "affs": [
        1
      ],
      "name": "Weilan Wang"
    },
    {
      "affs": [
        2
      ],
      "name": "Yi Ern Chew"
    },
    {
      "affs": [
        3
      ],
      "name": "Lihuan Guan"
    },
    {
      "affs": [
        4
      ],
      "name": "Brian K. Kennedy"
    },
    {
      "name": "Andrea B. Maier"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/emvnmhpz36nkr.bib",
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  "doi": "10.1371/journal.pdig.0001691",
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  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
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  "metadata_licence": null,
  "native_subjects": [
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  "pmcid": null,
  "pmid": null,
  "published": "2026-09-25",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/emvnmhpz36nkr.ris",
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  "title": "Optimizing accelerometer implementation in a gerotherapeutic trial: Feasibility, adherence, and operational insights of ABLE",
  "title_text": "Optimizing accelerometer implementation in a gerotherapeutic trial: Feasibility, adherence, and operational insights of ABLE",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:43Z",
  "url": "https://research.draconitic.com/paper/emvnmhpz36nkr",
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