Frontiers in Psychiatry (Mar 2021)

Monitoring Sleep Changes via a Smartphone App in Bipolar Disorder: Practical Issues and Validation of a Potential Diagnostic Tool

  • Frederike T. Fellendorf,
  • Carlo Hamm,
  • Nina Dalkner,
  • Martina Platzer,
  • Matteo C. Sattler,
  • Susanne A. Bengesser,
  • Melanie Lenger,
  • Rene Pilz,
  • Armin Birner,
  • Robert Queissner,
  • Adelina Tmava-Berisha,
  • Michaela Ratzenhofer,
  • Alexander Maget,
  • Mireille van Poppel,
  • Eva Z. Reininghaus

DOI
https://doi.org/10.3389/fpsyt.2021.641241
Journal volume & issue
Vol. 12

Abstract

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Background: Sleep disturbances are common early warning signs of an episode of bipolar disorder, and early recognition can favorably impact the illness course. Symptom monitoring via a smartphone app is an inexpensive and feasible method to detect an early indication of changes such as sleep. The study aims were (1) to assess the acceptance of apps and (2) to validate sleeping times measured by the smartphone app UP!.Methods:UP! was used by 22 individuals with bipolar disorder and 23 controls. Participants recorded their time of falling asleep and waking-up using UP! for 3 weeks. Results were compared to a validated accelerometer and the Pittsburgh Sleep Quality Index. Additionally, participants were interviewed regarding early warning signs and their feedback for apps as monitoring tools in bipolar disorder (NCT03275714).Results: With UP!, our study did not find strong reservations concerning data protection or continual smartphone usage. Correlation analysis demonstrates UP! to be a valid tool for measuring falling asleep and waking-up times.Discussion: Individuals with bipolar disorder assessed the measurement of sleep disturbances as an early warning sign with a smartphone as positive. The detection of early signs could change an individual's behavior and strengthen self-management. The study showed that UP! can be used to measure changes in sleep durations accurately. Further investigation of smartphone apps' impact to measure other early signs could significantly contribute to clinical treatment and research in the future through objective, continuous, and individual data collection.

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