Applications of time-series analysis to mood fluctuations in bipolar disorder to promote treatment innovation: a case series.

ABSTRACT: Treatment innovation for bipolar disorder has been hampered by a lack of techniques to capture a hallmark symptom: ongoing mood instability. Mood swings persist during remission from acute mood episodes and impair daily functioning. The last significant treatment advance remains Lithium (in the 1970s), which aids only the minority of patients. There is no accepted way to establish proof of concept for a new mood-stabilizing treatment. We suggest that combining insights from mood measurement with applied mathematics may provide a step change: repeated daily mood measurement (depression) over a short time frame (1 month) can create individual bipolar mood instability profiles. A time-series approach allows comparison of mood instability pre- and post-treatment. We test a new imagery-focused

SUBMITTER: Holmes EA 

PROVIDER: S-EPMC5068881 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature