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Deering S, Pratap A, Suver C, et al. Real-world longitudinal data collected from the SleepHealth mobile app study. Sci Data. 2020;7(1):418doi: 10.1038/s41597-020-00753-2.
Deering, S., Pratap, A., Suver, C., Borelli, A. J., Amdur, A., Headapohl, W., & Stepnowsky, C. J. (2020). Real-world longitudinal data collected from the SleepHealth mobile app study. Scientific data, 7(1), 418. https://doi.org/10.1038/s41597-020-00753-2
Deering, Sean, et al. "Real-world longitudinal data collected from the SleepHealth mobile app study." Scientific data vol. 7,1 (2020): 418. doi: https://doi.org/10.1038/s41597-020-00753-2
Deering S, Pratap A, Suver C, Borelli AJ, Amdur A, Headapohl W, Stepnowsky CJ. Real-world longitudinal data collected from the SleepHealth mobile app study. Sci Data. 2020 Nov 27;7(1):418. doi: 10.1038/s41597-020-00753-2. PMID: 33247114; PMCID: PMC7695828.
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Sci Data. 2020 Nov 27;7(1):418. doi: 10.1038/s41597-020-00753-2.

Real-world longitudinal data collected from the SleepHealth mobile app study.

Scientific data

Sean Deering, Abhishek Pratap, Christine Suver, A Joseph Borelli, Adam Amdur, Will Headapohl, Carl J Stepnowsky

Affiliations

  1. Health Services Research & Development, VA San Diego Healthcare System, San Diego, CA, 92161, USA.
  2. Sage Bionetworks, Seattle, WA, 98109, USA.
  3. American Sleep Apnea Association, Washington, DC, 20001, USA.
  4. Health Services Research & Development, VA San Diego Healthcare System, San Diego, CA, 92161, USA. [email protected].
  5. Department of Medicine, University of California at San Diego, La Jolla, CA, 92037, USA. [email protected].

PMID: 33247114 PMCID: PMC7695828 DOI: 10.1038/s41597-020-00753-2

Abstract

Conducting biomedical research using smartphones is a novel approach to studying health and disease that is only beginning to be meaningfully explored. Gathering large-scale, real-world data to track disease manifestation and long-term trajectory in this manner is quite practical and largely untapped. Researchers can assess large study cohorts using surveys and sensor-based activities that can be interspersed with participants' daily routines. In addition, this approach offers a medium for researchers to collect contextual and environmental data via device-based sensors, data aggregator frameworks, and connected wearable devices. The main aim of the SleepHealth Mobile App Study (SHMAS) was to gain a better understanding of the relationship between sleep habits and daytime functioning utilizing a novel digital health approach. Secondary goals included assessing the feasibility of a fully-remote approach to obtaining clinical characteristics of participants, evaluating data validity, and examining user retention patterns and data-sharing preferences. Here, we provide a description of data collected from 7,250 participants living in the United States who chose to share their data broadly with the study team and qualified researchers worldwide.

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