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Assessing a Sleep Interviewing Chatbot to Improve Subjective and Objective Sleep: Protocol for an Observational

Ting Su1,2,3, Rafael A Calvo2, Melanie Jouaiti1,3

  • 1Department of Mechanical Engineering, Imperial College London, London, United Kingdom.

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This study explored the feasibility of an automated chatbot, MotivSleep, to improve sleep in older adults. The chatbot provided personalized recommendations, showing potential for accessible sleep intervention.

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Area of Science:

  • Gerontology
  • Neuroscience
  • Digital Health

Background:

  • Sleep disorders are prevalent in aging populations and individuals with neurodegenerative diseases, exhibiting a bidirectional relationship.
  • Access to traditional sleep interventions can be challenging for older adults and those with neurodegenerative conditions.
  • Automated chatbot platforms offer a potential solution to increase the accessibility of sleep disorder interventions.

Purpose of the Study:

  • To determine the feasibility and usability of the MotivSleep chatbot for sleep behavior reporting and personalized recommendations.
  • To assess changes in subjective sleep quality before, during, and after using the chatbot.
  • To evaluate changes in objective sleep parameters measured by a sleep tracking device during chatbot use.

Main Methods:

  • Recruited 30 older adults in West London for a pilot study.
  • Utilized a contactless sleep analyzer to record objective sleep data (movements, heart rate, breathing rate).
  • Participants interacted with the MotivSleep chatbot via WhatsApp for sleep reporting and received tailored recommendations.

Main Results:

  • Hypothesized that participants would find the chatbot intelligent and trustworthy.
  • Anticipated improvements in participants' subjective and objective sleep assessments.
  • Data collection ran from May to December 2023.

Conclusions:

  • The MotivSleep chatbot demonstrates potential for accessible and cost-effective sleep improvement support for older adults.
  • Automated interventions can supplement traditional face-to-face therapy for sleep disorders.
  • This approach may enhance care for aging populations and those with neurodegenerative diseases.