This paper is in the following e-collection/theme issue:

Wearables and MHealth Viewpoints (82) Fitness Trackers and Smart Pedometers/Accelerometers (578) Evaluation and Research Methodology for mHealth (211) Fitness Trackers and Smart Pedometers/Accelerometers (578) Wearable Devices and Sensors (919) mHealth for Data Collection and Research (995) Mobile Health (mhealth) (3013) mHealth for Data Collection and Research (995) Evaluation and Research Methodology for mHealth (211) Mobile Health (mhealth) (3013) Wearable Devices and Sensors (919)

Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45103, first published .
The Importance of Data Quality Control in Using Fitbit Device Data From the All of Us Research Program

The Importance of Data Quality Control in Using Fitbit Device Data From the All of Us Research Program

The Importance of Data Quality Control in Using Fitbit Device Data From the All of Us Research Program

Authors of this article:

Lauren Lederer1 Author Orcid Image ;   Amanda Breton2 Author Orcid Image ;   Hayoung Jeong1 Author Orcid Image ;   Hiral Master3 Author Orcid Image ;   Ali R Roghanizad1 Author Orcid Image ;   Jessilyn Dunn1 Author Orcid Image
Article Authors Cited by (7) Tweetations (4) Metrics

Journals

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  6. Jeong H, Roghanizad A, Master H, Kim J, Kouame A, Harris P, Basford M, Marginean K, Dunn J. Data from the All of Us research program reinforces existence of activity inequality. npj Digital Medicine 2025;8(1) View
  7. Doherty I, Wells M. Sleep disparities in the United States: Comparison of logistic and linear regression with stratification by race. Sleep Epidemiology 2025;5:100106 View