Methods
In the present study, we search for evidence of nonlinearity using linear surrogates, then compare the expected prediction error of linear and nonlinear forecasting methods on eight selected patients. Time series data was collected as part of the OXTEXT (http://oxtext.psych.ox.ac.uk/) programme which investigates the potential benefits of mood self-monitoring for people with bipolar disorder. OXTEXT uses the True Colours (https://truecolours.nhs.uk/www/) self-management system for mood monitoring which was initially developed to monitor outpatients with bipolar disorder. Each week, patients complete a questionnaire and return the results as a digit sequence by text message or email. The resulting time series of mood ratings are visualised as color-coded graphs for use at an outpatient appointment. This information is used both by clinicians to select appropriate interventions and by the patients themselves for management of their condition. The Oxford mood monitoring system has generated a large database of mood time series which has been used for studying the longitudinal course of bipolar disorder ([Bopp et al. 2010]) and for nonlinear approaches to characterising mood by Bonsall et al. ([2012]). The data in the current study used the same telemonitoring techniques and the same rating scales as ([Bonsall et al. 2012]), but the studies are otherwise independent.
The work reported here has been performed in accordance with Declaration of Helsinki of 1975, as revised in 2004, and was approved by the local Research Ethics Committee ref: 10/H0604/13.