<p>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.</p>

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The All of Us Research Program’s wearables dataset

  • Theresa Patten,
  • Edward A. Preble,
  • Hiral Master,
  • Jennifer Adjemian,
  • Andrea Ramirez,
  • James McClain,
  • Amy Rose Price

摘要

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.