ArticleNature medicine2026
The All of Us Research Program's wearables dataset.
Article in Nature medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Interrelations of work with health and wellbeing on a 50+ year old workforce assessed using longitudinal self-reports and actigraphy.Scientific reports · 2026Article
- A Reproducible Pipeline for Processing Commercial Wearable Step-Count Data in Aging Cohorts: Application and Evaluation in the STRRIDE-PD Reunion Study.medRxiv : the preprint server for health sciences · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital health technologies (DHTs) are revolutionizing medical research, offering unprecedented insights into health monitoring and disease detection through continuous, real-world data collection. Here we characterize the data in one of the largest and most demographically rich DHT datasets as part of the All of Us Research Program. Through a historic device distribution effort, the program reached a broad range of participants nationwide, yielding a DHT dataset with an expanded a large demographic scope. This dataset contains Fitbit data from more than 59,000 participants spanning 14 years with more than 39 million step observations and 31 million sleep observations. Nearly half (46%) of participants with Fitbit data also contributed electronic health records, physical measurements, genomics and survey data. This resource enables researchers to study relationships between digital health metrics and clinical outcomes, advancing DHT methodologies through its large size, broad representation and multi-modal data linkage.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.