Taken together , the literature presented in this dissertation illustrates that 1 ) smartphone-based electronic self-monitoring of mood  seems to reflect clinical ly assessed depressive and manic symptoms and enables the long-term characterization of mood instability in bipolar disorder ; 2 ) preliminary results suggest that smartphone-based automatically generated data ( e.g. the number of text messages sent/day ; the number of incoming and outgoing calls/day ; the number of changes in cell tower IDs/day ; and voice features ) seem to reflect clinical ly assessed depressive and manic symptoms in bipolar disorder ; 3 ) smartphone-based electronic self-monitoring had no effects on the severity of depressive and manic symptoms in bipolar disorder , according to a r and omized controlled trial ; and 4 ) electronic  monitoring of psychomotor activity and heart rate variability seems to reflect illness activity in bipolar disorder and differentiate between patients with bipolar disorder and healthy control individuals .
These findings point toward the usefulness of  electronic monitoring  as a marker of illness in bipolar disorder .
Major reasons for the insufficient effects of current treatment options in bipolar disorder include delayed intervention for prodromal depressive and manic symptoms and decreased adherence to psychopharmacological treatment .
The reliance on subjective information and clinical evaluations when diagnosing and assessing the severity of depressive and manic symptoms calls for less biased and more objective markers .
By using electronic devices , fine-grained data on complex psychopathological aspects of bipolar disorder can be evaluated unobtrusively over the long term .
Using electronic monitoring as a treatment intervention could provide innovative and novel interventions on-dem and with a potential global reach , filling the gap between availability and the need for treatment .
A randomized head to head trial of MoodSwings.net.au: an Internet based self-help program for bipolar disorder.
BACKGROUND Adjunctive psychosocial interventions are efficacious in bipolar disorder , but their incorporation into routine management plans are often confounded by cost and access constraints . We report here a comparative evaluation of two online programs hosted on a single website ( www.moodswings.net.au ) . A basic version , called MoodSwings ( MS ) , contains psychoeducation material and asynchronous discussion boards ; and a more interactive program , MoodSwings Plus ( MS-Plus ) , combined the basic psychoeducation material and discussion boards with elements of Cognitive Behavioral Therapy . These programs were evaluated in a head-to-head study design . METHOD Participants with Bipolar I or II disorder ( n=156 ) were r and omized to receive either MoodSwings or MoodSwings-Plus .  Outcomes included mood symptoms , the occurrence of relapse , functionality , Locus of Control , social support , quality of life and medication adherence . RESULTS Participants in both groups showed baseline to endpoint reductions in mood symptoms and improvements in functionality , quality of life and medication adherence . The MoodSwings-Plus group showed a greater number of within-group changes on symptoms and functioning in depression and mania , quality of life and social support , across both poles of the illness . MoodSwings-Plus was superior to MoodSwings in improvement on symptoms of mania scores at 12 months ( p=0.02 ) but not on the incidence of recurrence . LIMITATIONS The study did not have an attention control group and therefore could not demonstrate efficacy of the two active arms . There was notable ( 81 % ) attrition by 12 months from baseline . CONCLUSION This study suggests that both CBT and psychoeducation delivered online may have utility in the management of bipolar disorder . They are feasible , readily accepted , and associated with improvement
Taken together , the literature presented in this dissertation illustrates that 1 ) smartphone-based electronic self-monitoring of mood  seems to reflect clinical ly assessed depressive and manic symptoms and enables the long-term characterization of mood instability in bipolar disorder ; 2 ) preliminary results suggest that smartphone-based automatically generated data ( e.g. the number of text messages sent/day ; the number of incoming and outgoing calls/day ; the number of changes in cell tower IDs/day ; and voice features ) seem to reflect clinical ly assessed depressive and manic symptoms in bipolar disorder ; 3 ) smartphone-based electronic self-monitoring had no effects on the severity of depressive and manic symptoms in bipolar disorder , according to a r and omized controlled trial ; and 4 ) electronic  monitoring of psychomotor activity and heart rate variability seems to reflect illness activity in bipolar disorder and differentiate between patients with bipolar disorder and healthy control individuals .
These findings point toward the usefulness of  electronic monitoring  as a marker of illness in bipolar disorder .
Major reasons for the insufficient effects of current treatment options in bipolar disorder include delayed intervention for prodromal depressive and manic symptoms and decreased adherence to psychopharmacological treatment .
The reliance on subjective information and clinical evaluations when diagnosing and assessing the severity of depressive and manic symptoms calls for less biased and more objective markers .
By using electronic devices , fine-grained data on complex psychopathological aspects of bipolar disorder can be evaluated unobtrusively over the long term .
Using electronic monitoring as a treatment intervention could provide innovative and novel interventions on-dem and with a potential global reach , filling the gap between availability and the need for treatment .