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 .
The evaluation of the results of clinical trials: surrogate end points and composite end points.
The evaluation of the clinical outcome of patients enrolled in r and omised controlled studies should always be accurate and objective . The methods used to assess and report patients ' results must consequently be indicated a priori in the design of the clinical experimentation . Major ( hard ) individual end points currently constitute the gold st and ard in the definition of outcome measures , yet surrogate and composite end points are spreading diffusely as alternative/complementary outcome measures . Surrogate end points are minor outcome measures that are easier to record and are being adopted instead of major end points . They may be considered acceptable substitutes of hard end points when capable of predicting major events reliably , and when it may be demonstrated that the intervention on such surrogate end points consistently modifies the incidence of the event . In other cases they can not represent predictive elements of major clinical outcomes . Composite ( combined ) primary end points may contribute to improve the statistical precision of a clinical trial ; moreover , since clinical trials are particularly expensive , their identification permits more limited sample s of patients to be enrolled . Their limits include the possibility that the direction in which the different outcome measures composing the combined end point are modified is not the same . Biomedical research ers are called upon to design studies adopting major ( hard ) end points , rather than solitary surrogate end points , in order to provide really useful information for the care of patients . The selection of composite end points requires notable method ological attention so as to retrieve the most reliable estimates on the efficacy and the effectiveness of treatments
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 .