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 web-based preventive intervention program for bipolar disorder: outcome of a 12-months randomized controlled trial.
BACKGROUND The Internet is used to deliver information on many psychiatric disorders such as bipolar disorder . This paper reports on the results of a 12-months r and omised controlled trial , which examined the efficacy of an Internet-based preventive program for bipolar disorder , adjunctive to usual pharmacological management . METHODS Participants were recruited by completing an online screening question naire accessed through the Black Dog Institute and Sentiens websites based in Australia . The treatment was predominantly psycho-educational with cognitive behavioral therapy optional elements . The attention control treatment comprised directing subjects to a variety of websites focused on ' healthy living ' . Time to recurrence was determined using Kaplan-Meier survival analysis . The main outcome measures were recurrence as defined by : ( i ) depressive and /or hypomanic symptomatology and functional capacity ( using Beck Depression Inventory , Internal State Scale and Sheehan Disability Scale ) and ( ii ) hospitalization . RESULTS Two-hundred- and -thirty-three subjects were r and omized to the active or control treatment groups . There were no significant differences between the active and control treatment groups on any of the definitions of recurrence . LIMITATIONS Reliance on an online self-report tool to confirm diagnosis and hospitalization rates may have potentially allowed for inclusion of individuals with other diagnoses such as borderline personality disorder . The ' attention control ' treatment may have included more ' active ' components than intended . CONCLUSIONS This is the first report examining the efficacy of a r and omized controlled web-based psychological intervention in a large sample of subjects with bipolar disorder . The potential reasons for failing to demonstrate a significant difference compared to the active control are discussed
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 .