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Exploring Variations in Sleep Perception: Comparative Study of Chatbot Sleep Logs and Fitbit Sleep Data.

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Wearable devices like Fitbits offer valuable sleep data, but individual time perception differences mean subjective patient input remains crucial for accurate sleep management. This highlights limitations of objective measures alone.

Keywords:
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Area of Science:

  • Digital Health
  • Sleep Science
  • Human-Computer Interaction

Background:

  • Patient-generated health data (PGHD) from wearable devices are increasingly vital for disease management.
  • Wearables like Fitbits can track sleep metrics (e.g., sleep onset, offset, total sleep time), but have limitations in accuracy and depth of sleep assessment.
  • Subjective patient reporting is essential and cannot be fully replaced by wearable device data.

Purpose of the Study:

  • To analyze the characteristics of individual time perception in sleep compared to wearable device data.
  • To understand how users perceive and report sleep times versus objective measurements.
  • To inform the effective use of time-related PGHD, specifically sleep data.

Main Methods:

  • Collected sleep data over two weeks using Fitbit devices.
  • Gathered daily sleep records from participants via chatbot conversations.
  • Statistically compared Fitbit-measured sleep data with self-reported data from chatbot interactions.

Main Results:

  • Analysis included 543 participants (aged 30-59) with over 7 days of data.
  • Participants often reported sleep times in hourly or 30-minute increments, generally within 60-90 minutes of Fitbit data.
  • Average differences between chatbot and Fitbit data were around 15 minutes; however, individual variations were significant, making prediction difficult.
  • Participants reporting good sleep tended to estimate longer sleep durations than measured by Fitbit.

Conclusions:

  • Chatbot-reported sleep times and Fitbit measurements show average similarity, but individual perception varies greatly.
  • Subjective reporting of good sleep quality correlates with longer perceived sleep duration.
  • Significant individual differences in sleep time perception underscore the limitations of relying solely on wearable devices for objective sleep assessment.