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

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This study explored using smartphones for large-scale biomedical research, focusing on sleep habits and daily function. The digital health approach proved practical for collecting real-world data from many participants.

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Area of Science:

  • Digital Health
  • Mobile Health Research
  • Biomedical Data Collection

Background:

  • Smartphone-based research offers a novel, practical method for large-scale data acquisition in health and disease.
  • This approach allows for the collection of real-world, real-time data, including contextual and environmental information through device sensors and wearables.
  • Previous research has not fully tapped into the potential of mobile technology for tracking disease manifestation and long-term health trajectories.

Purpose of the Study:

  • To investigate the relationship between sleep habits and daytime functioning using a novel digital health approach.
  • To assess the feasibility of a fully remote clinical data collection strategy.
  • To evaluate data validity, user retention, and data-sharing preferences in a large cohort study.

Main Methods:

  • Utilized a mobile application to collect data from a large cohort of 7,250 participants across the United States.
  • Employed surveys and sensor-based activities integrated into participants' daily routines.
  • Collected contextual and environmental data via device sensors, data aggregators, and connected wearable devices.

Main Results:

  • Successfully gathered extensive data from 7,250 participants, demonstrating the feasibility of a large-scale, remote digital health study.
  • The SleepHealth Mobile App Study (SHMAS) provided a rich dataset for understanding sleep-health relationships.
  • Participant data sharing was broad, including with qualified researchers globally.

Conclusions:

  • Smartphone-based research is a viable and practical method for large-scale biomedical data collection.
  • Digital health approaches, like SHMAS, can effectively study complex relationships such as sleep and daytime functioning.
  • The study highlights the potential for remote data collection to advance health research and understanding of disease.