Evaluating the relationship between Fitbit sleep data and self-reported mood, sleep and environmental contextual factors in healthy adults

3:30 PM–4:30 PM May 19, 2020 (Conference Time: US - Pacific)

3:30 PM–4:30 PM May 19, 2020

Regency Prefunction


Abstract: Problem: A literature gap exists for using personal fitness devices to identify sleep patterns indicative of underlying mental health disorders.
Significance: If Fitbit proves an appropriate clinical tool, it could decrease cost, improve access to patient data and create real time treatment options.
Purpose: The purpose is to determine the relationship in healthy adults between Fitbit sleep data, self-reported mood and sleep while documenting contextual factors which may disrupt sleep.

Describe the new knowledge and additional skills the participant will gain after attending your presentation.: After viewing my poster, audience members should learn:
1. MH disorders are prevalent in the US and the Active Duty Service Member population.
2. MH disorders can significantly effect a person’s quality of life and sleep.
3. Sleep disturbances may indicate a marker of underlying MH disorders.
4. Understand how Fitbit might be used as a tool to detect early markers of underlying MH disorders.


Darshan Thota (Presenter)
Madigan Army Medical Center