- Title
- Bipolar disorder and sleep tracking using the Fitbit Charge HR
- Creator
- Drew, Madeleine
- Relation
- University of Newcastle Research Higher Degree Thesis
- Resource Type
- thesis
- Date
- 2017
- Description
- Masters Coursework - Masters of Clinical Psychology (MClinPsych)
- Description
- Background: Advances in actigraphy technology enables researchers to examine the link between sleep and Bipolar Disorder (BD), objectively and in real-time. The current study investigated the sleep-wake patterns in adults with BD prior to elevated and depressed moods. Method: Participants included ten individuals aged between 25 and 50 years (M = 35.3, SD = 7.83), with BD. Participants attended a baseline, 1-week and 3-month assessment, where they completed the PSQI (subjective measure of sleep) and their mood was objectively assessed. The participants completed a weekly self-report mood survey to determine mood state and the Fitbit objectively monitored their sleep patterns throughout the study. Results: Reduced sleep duration was not shown to predict elevated mood states. No relationship was found between sleep disruption and depressed mood states. A significant increase in sleep disturbances predicted depressed mood states. A trend for lower sleep efficiency prior to depressed mood states was found. There was a strong association between the Fitbit and PSQI measure of sleep duration. Limitations: This study was limited by a small sample size and a lack of mood variability within the hyo/mania spectrum. Conclusions: There is preliminary support for the Fibit Charge HR being an efficient measure of sleep disturbances in participants with BD. Sleep disturbances predicted depressed mood states. If the Fitbit was unavailable, clinicians could consider using the PSQI measure of sleep duration as an alternate method for tracking sleep. Further testing of the Fitbit Charge HR with more participants with BD for a longer duration is required.
- Subject
- bipolar disorder; sleep-wake patterns; Fitbit Charge HR; technology
- Identifier
- http://hdl.handle.net/1959.13/1349951
- Identifier
- uon:30465
- Rights
- Copyright 2017 Madeleine Drew
- Language
- eng
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| View Details Download | ATTACHMENT01 | Thesis | 5 MB | Adobe Acrobat PDF | View Details Download | ||
| View Details Download | ATTACHMENT02 | Abstract | 113 KB | Adobe Acrobat PDF | View Details Download |