- Title
- Using technology to monitor sleep and social activity in adults with bipolar disorder: an observational pilot study
- Creator
- Heaton, Gabriel L.
- Resource Type
- thesis
- Date
- 2019
- Description
- Masters Coursework - Master of Clinical Psychology (MClinPsych)
- Description
- Background: Signs of relapse in Bipolar Disorder (BD) are characterised by shifts in sleep and social activity. Contemporary technologies such as smartphones and lifestyle devices can automatically collect ecological data. This study investigated the feasibility including tolerability of technology to monitor sleep and social activity in the identification of signs of relapse in bipolar disorder. Methods: Sleep, social activity and mood were monitored over 12-months in twelve participants with BD. The Bipolar Depression Rating Scale, Young Mania Rating Scale, Pittsburgh Sleep Quality Index and Duke Social Support Inventory were used to assess mood, sleep and social activity at baseline, again at 1-week and then every 3-months. Daily phone calls and message logs were collected from participants’ smartphones using If This Then That (IFTTT) and Unforgettable Me (UM) applications. Hours of sleep were collected using a Fitbit Charge HR provided to participants. Tolerability was determined by the attrition rate in the sample. Results: Cumulative sum charts yielded change-points indicating probable ecological shifts in the pattern of telecommunication and/or sleep duration concomitated with self-reported changes in social-support and sleep duration. Limited fluctuations in mood were observed in participants throughout the 12-month period limiting the scope of the analysis. Limitations: The small sample size was restricted by an Android only operating system requirements of UM and also constrained analyses to an observation of change-points. Hardware and software reliability coupled with a high attrition rate reduced data integrity. Conclusions: Technology provides a novel opportunity to monitor symptoms in BD although more research into reliable and user-friendly methods is needed.
- Subject
- bipolar disorder; monitoring; device; social activity; sleep
- Identifier
- http://hdl.handle.net/1959.13/1412492
- Identifier
- uon:36490
- Rights
- Copyright 2019 Gabriel L. Heaton
- Language
- eng
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| Thumbnail | File | Description | Size | Format | |||
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| View Details Download | ATTACHMENT01 | Thesis | 6 MB | Adobe Acrobat PDF | View Details Download | ||
| View Details Download | ATTACHMENT02 | Abstract | 312 KB | Adobe Acrobat PDF | View Details Download |