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 .
Augmenting psychoeducation with a mobile intervention for bipolar disorder: a randomized controlled trial.
BACKGROUND Psychosocial interventions for bipolar disorder are frequently unavailable and re source intensive . Mobile technology may improve access to evidence -based interventions and may increase their efficacy . We evaluated the feasibility , acceptability and efficacy of an augmentative mobile ecological momentary intervention targeting self-management of mood symptoms . METHODS This was a r and omized single-blind controlled trial with 82 consumers diagnosed with bipolar disorder who completed a four-session psychoeducational intervention and were assigned to 10 weeks of either : 1 ) mobile device delivered interactive intervention linking patient-reported mood states with personalized self-management strategies , or 2 ) paper- and -pencil mood monitoring . Participants were assessed at baseline , 6 weeks ( mid-point ) , 12 weeks ( post-treatment ) , and 24 weeks ( follow up ) with clinician-rated depression and mania scales and self-reported functioning . RESULTS Retention at 12 weeks was 93 % and both conditions were associated with high satisfaction . Compared to the paper- and -pencil condition , participants in the augmented mobile intervention condition showed significantly greater reductions in depressive symptoms at 6 and 12 weeks ( Cohen׳s d for both were d=0.48 ) . However , these effects were not maintained at 24-weeks follow up . Conditions did not differ significantly in the impact on manic symptoms or functional impairment . LIMITATIONS This was not a definitive trial and was not powered to detect moderators and mediators . CONCLUSIONS Automated mobile-phone intervention is feasible , acceptable , and may enhance the impact of brief psychoeducation on depressive symptoms in bipolar disorder . However , sustainment of gains from symptom self-management  mobile interventions , once stopped , may be limited
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 .