Daily electronic self-monitoring in bipolar disorder using smartphones - the MONARCA I trial: a randomized, placebo-controlled, single-blind, parallel group trial. Daily electronic self-monitoring of subjective and objective symptoms in bipolar disorder—the MONARCA trial protocol (MONitoring, treAtment and pRediCtion of bipolAr disorder episodes): a randomised controlled single-blind trial Daily electronic monitoring of subjective and objective measures of illness activity in bipolar disorder using smartphones– the MONARCA II trial protocol: a randomized controlled single-blind parallel-group trial Using Smartphones to Monitor Bipolar Disorder Symptoms: A Pilot Study Saving time and money: a validation of the self ratings on the prospective NIMH life-chart method (NIMH-LCM) Voice analysis as an objective state marker in bipolar disorder A Pilot Study of Mood Ratings Captured by Mobile Phone Versus Paper-and-Pencil Mood Charts in Bipolar Disorder Self-monitoring and psychoeducation in bipolar patients with a smart-phone application (SIMPLe) project: design, development and studies protocols Self-monitoring Using Mobile Phones in the Early Stages of Adolescent Depression: Randomized Controlled Trial A randomized comparison of online and paper mood charts for people with bipolar disorder. Using Electronic Health Record–Based Tools To Screen for Bipolar Disorder in Primary Care Patients With Depression Computer-assisted self-assessment in persons with severe mental illness. Health-related quality of life assessment in euthymic and depressed patients with bipolar disorder. Psychometric performance of four self-report measures. An online randomised controlled trial to assess the feasibility, acceptability and potential effectiveness of 'Living with Bipolar': a web-based self-management intervention for bipolar disorder: trial design and protocol. A randomized controlled trial of cognitive therapy for bipolar disorder: focus on long-term change. Longitudinal monitoring of heartbeat dynamics predicts mood changes in bipolar patients: A pilot study. Validation of the prospective NIMH-Life-Chart Method (NIMH-LCM-p) for longitudinal assessment of bipolar illness.
BACKGROUND The number of studies on electronic self-monitoring in affective disorder and other psychiatric disorders is increasing and indicates high patient acceptance and adherence . Nevertheless , the effect of electronic self-monitoring in patients with bipolar disorder has never been investigated in a r and omized controlled trial ( RCT ) . The objective of this trial was to investigate in a RCT whether the use of daily electronic self-monitoring using smartphones reduces depressive and manic symptoms in patients with bipolar disorder . METHOD A total of 78 patients with bipolar disorder according to ICD-10 criteria , aged 18 - 60 years , and with 17-item Hamilton Depression Rating Scale ( HAMD-17 ) and Young Mania Rating Scale ( YMRS ) scores ≤17 were r and omized to the use of a smartphone for daily self-monitoring including a clinical feedback loop ( the intervention group ) or to the use of a smartphone for normal communicative purpose s ( the control group ) for 6 months . The primary outcomes were differences in depressive and manic symptoms measured using HAMD-17 and YMRS , respectively , between the intervention and control groups . RESULTS Intention-to-treat analyses using linear mixed models showed no significant effects of daily self-monitoring using smartphones  on depressive as well as manic symptoms . There was a tendency towards more sustained depressive symptoms in the intervention group ( B = 2.02 , 95 % confidence interval -0.13 to 4.17 , p = 0.066 ) . Sub-group analysis among patients without mixed symptoms and patients with presence of depressive and manic symptoms showed significantly more depressive symptoms and fewer manic symptoms during the trial period in the intervention group . CONCLUSIONS These results highlight that electronic self-monitoring , although intuitive and appealing , needs critical consideration and further clarification before it is implemented as a clinical tool Introduction Electronic self-monitoring of affective symptoms using cell phones is suggested as a practical and inexpensive way to monitor illness activity and identify early signs of affective symptoms . It has never been tested in a r and omised clinical trial whether electronic self-monitoring improves outcomes in bipolar disorder . We are conducting a trial testing the effect of using a Smartphone for self-monitoring in bipolar disorder . Methods We developed the MONARCA application for And roid-based Smartphones , allowing patients suffering from bipolar disorder to do daily self-monitoring — including an interactive feedback loop between patients and clinicians through a web-based interface . The effect of the application was tested in a parallel-group , single-blind r and omised controlled trial so far including 78 patients suffering from bipolar disorder in the age group 18–60 years who were given the use of a Smartphone with the MONARCA application ( intervention group ) or to the use of a cell phone without the application ( placebo group ) during a 6-month study period . The study was carried out from September 2011 . The outcomes were changes in affective symptoms ( primary ) , social functioning , perceived stress , self-rated depressive and manic symptoms , quality of life , adherence to medication , stress and cognitive functioning ( secondary and tertiary ) . Analysis Recruitment is ongoing . Ethics Ethical permission has been obtained . Dissemination Positive , neutral and negative findings of the study will be published . Registration details The trial is approved by the Regional Ethics Committee in The Capital Region of Denmark ( H-2 - 2011 - 056 ) and The Danish Data Protection Agency ( 2013 - 41 - 1710 ) . The trial is registered at Clinical Trials.gov as NCT01446406 Background Patients with bipolar disorder often show decreased adherence with mood stabilizers and frequently interventions on prodromal depressive and manic symptoms are delayed . Recently , the MONARCA I r and omized controlled trial investigated the effect of electronic self-monitoring using smartphones on depressive and manic symptoms . The findings suggested that patients using the MONARCA system had more sustained depressive symptoms than patients using a smartphone for normal communicative purpose s , but had fewer manic symptoms during the trial . It is likely that the ability of these self-monitored measures to detect prodromal symptoms of depression and mania may be insufficient compared to automatically generated objective data on measures of illness activity such as phone usage , social activity , physical activity , and mobility . The Monsenso system , for smartphones integrating subjective and objective measures of illness activity was developed and will be tested in the present trial . Methods The MONARCA II trial uses a r and omized controlled single-blind parallel-group design . Patients with bipolar disorder according to ICD-10 who previously have been treated at the Copenhagen Clinic for Affective Disorder , Denmark are included and r and omized to either daily use of the Monsenso system including an feedback loop between patients and clinicians ( the intervention group ) or to the use of a smartphone for normal communicative purpose s ( the control group ) for a 9-month trial period . The trial was started in September 2014 and recruitment is ongoing . The outcomes are : differences in depressive and manic symptoms ; rate of depressive and manic episodes ( primary ) ; automatically generated objective data on measures of illness activity ; number of days hospitalized ; psychosocial functioning ( secondary ) ; perceived stress ; quality of life ; self-rated depressive symptoms ; self-rated manic symptoms ; recovery ; empowerment and adherence to medication ( tertiary ) between the intervention group and the control group during the trial . Ethical permission has been obtained . Positive , neutral and negative findings will be published . Discussion If the system is effective in reducing depressive and /or manic symptoms ( and other symptoms of bipolar disorder ) and the rate of episodes , there will be basis for extending the use to the treatment of bipolar disorder in general and in larger scale . Trial registration Clinical Trials.gov NCT02221336 . Registered 26th of September 2014 Background Relapse prevention in bipolar disorder can be improved by monitoring symptoms in patients ' daily life .  Smartphone apps are easy-to-use , low-cost tools that can be used to assess this information . To date , few studies have examined the usefulness of smartphone data for monitoring symptoms in bipolar disorder . Objective We present results from a pilot test of a smartphone-based monitoring system , Social Information Monitoring for Patients with Bipolar Affective Disorder ( SIMBA ) , that tracked daily mood , physical activity , and social communication in 13 patients . The objective of this study was to investigate whether smartphone measurements predicted clinical symptoms levels and clinical symptom change . The hypotheses that smartphone measurements are ( 1 ) negatively related to clinical depressive symptoms and ( 2 ) positively related to clinical manic symptoms were tested . Methods Clinical rating scales were administered to assess clinical depressive and manic symptoms . Patients used a smartphone with the monitoring app for up to 12 months . R and om-coefficient multilevel models were computed to analyze the relationship between smartphone data and externally rated manic and depressive symptoms . Overall clinical symptom levels and clinical symptom changes were predicted by separating between-patient and within-patient effects . Using established clinical thresholds from the literature , marginal effect plots displayed clinical relevance of smartphone data . Results Overall symptom levels and change in clinical symptoms were related to smartphone measures . Higher overall levels of clinical depressive symptoms were predicted by lower self-reported mood measured by the smartphone ( beta=-.56 , P<.001 ) . An increase in clinical depressive symptoms was predicted by a decline in social communication ( ie , outgoing text messages : beta=-.28 , P<.001 ) and a decline in physical activity as measured by the smartphone ( ie , cell tower movements : beta=-.11 , P=.03 ) . Higher overall levels of clinical manic symptoms were predicted by lower physical activity on the smartphone ( ie , distance travelled : beta=-.37 , P<.001 ) , and higher social communication ( beta=.48 , P=.03 ) . An increase in clinical manic symptoms was predicted by a decrease in physical activity on the smartphone ( beta=-.17 , P<.001 ) . Conclusions Clinical symptoms were related to some objective and subjective smartphone measurements , but not all smartphone measures predicted the occurrence of bipolar symptoms above clinical thresholds . Thus , smartphones have the potential to monitor bipolar disorder symptoms in patients ’ daily life . Further validation of monitoring tools in a larger sample is needed . Conclusions are limited by the low prevalence of manic and depressive symptoms in the study sample . Trial Registration International St and ard R and omized Controlled Trial Number ( IS RCT N ) : 05663421 ; http://www.controlled-trials.com/IS RCT N05663421 ( Archived by WebCite at http://www.webcitation.org/6d9wsibJB Background Careful observation of the longitudinal course of bipolar disorders is pivotal to finding optimal treatments and improving outcome . A useful tool is the daily prospect i ve Life-Chart Method , developed by the National Institute of Mental Health . However , it remains unclear whether the patient version is as valid as the clinician version . Methods We compared the patient-rated version of the Lifechart ( LC-self ) with the Young-Mania-Rating Scale ( YMRS ) , Inventory of Depressive Symptoms – Clinician version ( IDS-C ) , and Clinical Global Impression – Bipolar version ( CGI-BP ) in 108 bipolar I and II patients who participated in the Naturalistic Follow-up Study ( NFS ) of the German centres of the Bipolar Collaborative Network ( BCN ; formerly Stanley Foundation Bipolar Network ) . For statistical evaluation , levels of severity of mood states on the Lifechart were transformed numerically and comparison with affective scales was performed using chi-square and t tests . For testing correlations Pearson´s coefficient was calculated . Results Ratings for depression of LC-self and total scores of IDS-C were found to be highly correlated ( Pearson coefficient r = −.718 ; p < .001 ) , whilst the correlation of ratings for mania with YMRS compared to LC-self were slightly less robust ( Pearson coefficient r = .491 ; p = .001 ) . These results were confirmed by good correlations between the CGI-BP IA ( mania ) , IB ( depression ) and IC ( overall mood state ) and the LC-self ratings ( Pearson coefficient r = .488 , r = .721 and r = .65 , respectively ; all p < .001 ) . Conclusions The LC-self shows a significant correlation and good concordance with st and ard cross sectional affective rating scales , suggesting that the LC-self is a valid and time and money saving alternative to the clinician-rated version which should be incorporated in future clinical research in bipolar disorder . Generalizability of the results is limited by the selection of highly motivated patients in specialized bipolar centres and by the open design of the study Changes in speech have been suggested as sensitive and valid measures of depression and mania in bipolar disorder . The present study aim ed at investigating ( 1 ) voice features collected during phone calls as objective markers of affective states in bipolar disorder and ( 2 ) if combining voice features with automatically generated objective smartphone data on behavioral activities ( for example , number of text messages and phone calls per day ) and  electronic self-monitored data ( mood ) on illness activity would increase the accuracy as a marker of affective states . Using smartphones , voice features , automatically generated objective smartphone data on behavioral activities  and  electronic self-monitored data  were collected from 28 out patients with bipolar disorder in naturalistic setting s on a daily basis during a period of 12 weeks . Depressive and manic symptoms were assessed using the Hamilton Depression Rating Scale 17-item and the Young Mania Rating Scale , respectively , by a research er blinded to smartphone data . Data were analyzed using r and om forest algorithms . Affective states were classified using voice features extracted during everyday life phone calls . Voice features were found to be more accurate , sensitive and specific in the classification of manic or mixed states with an area under the curve (AUC)=0.89 compared with an AUC=0.78 for the classification of depressive states . Combining voice features with automatically generated objective smartphone data on behavioral activities  and electronic self-monitored data  increased the accuracy , sensitivity and specificity of classification of affective states slightly . Voice features collected in naturalistic setting s using smartphones may be used as objective state markers in patients with bipolar disorder Objective : Patient-reported mood charts are frequently used in management of bipolar disorder . Although mood charts have recently been programmed in electronic devices such as mobile phones , little is known about the impact of the method of data capture on the psychometric properties and validity of these data . Methods : In an ongoing pilot study , a sample of out patients with bipolar disorder were r and omized to complete mood charts either on a mobile phone or with st and ard paper and pencil as part of a 12-week intervention ( primary outcomes for the trial await study completion ) . We compared these conditions across a single item rating of mood state , and we hypothesized that mobile phone-based data capture would produce greater compliance to mood ratings , variability between and within participants , and concurrent validity with blinded clinician-rated affective symptom severity . Results : A total of 56 participants were r and omized and 40 participants were included in the analyses . There were no significant differences between conditions on demographic or clinical variables . The rate of compliance was significantly higher in paper- and -pencil versus mobile phone ratings . Ratings demonstrated significantly more variability within individuals in the mobile phone condition . Mobile phone mood ratings were significantly correlated with clinician-rated depressive symptom severity across the study and with manic symptom severity at the week-6 assessment , whereas paper- and -pencil ratings were not significantly associated with clinician-rated depression or mania . Conclusions : Although preliminary , our results suggest a lower rate of compliance with mobile phones compared to paper- and -pencil daily mood rating in bipolar disorder , yet a greater ability to capture variability and concurrent validity in quantifying affective symptoms . This clinical trial is registered at www . clinical trials.gov as NCT01670123 Background New technologies have recently been used for monitoring signs and symptoms of mental health illnesses and particularly have been tested to improve the outcomes in bipolar disorders . Web-based psychoeducational programs for bipolar disorders have also been implemented , yet to our knowledge , none of them have integrated both approaches in one single intervention . The aim of this project is to develop and vali date a smartphone application to monitor symptoms and signs and empower the self-management of bipolar disorder , offering customized embedded psychoeducation contents , in order to identify early symptoms and prevent relapses and hospitalizations . Methods / design The project will be carried out in three complementary phases , which will include a feasibility study ( first phase ) , a qualitative study ( second phase ) and a r and omized controlled trial ( third phase ) comparing the smartphone application ( SIMPLe ) on top of treatment as usual with treatment as usual alone . During the first phase , feasibility and satisfaction will be assessed with the application usage log data and with an electronic survey . Focus groups will be conducted and technical improvements will be incorporated at the second phase . Finally , at the third phase , survival analysis with multivariate data analysis will be performed and relationships between socio-demographic , clinical variables and assessment s scores with relapses in each group will be explored . Discussion This project could result in a highly available , user-friendly and not costly monitoring and psychoeducational intervention that could improve the outcome of people suffering from bipolar disorders in a practical and secure way . Trial registration Clinical Trials.gov : NCT02258711 ( October 2014 ) Background The stepped-care approach , where people with early symptoms of depression are stepped up from low-intensity interventions to higher-level interventions as needed , has the potential to assist many people with mild depressive symptoms .  Self-monitoring techniques assist people to underst and their mental health symptoms by increasing their emotional self-awareness ( ESA ) and can be easily distributed on mobile phones at low cost . Increasing ESA is an important first step in psychotherapy and has the potential to intervene before mild depressive symptoms progress to major depressive disorder . In this secondary analysis we examined a mobile phone self-monitoring tool used by young people experiencing mild or more depressive symptoms to investigate the relationships between  self-monitoring  , ESA , and depression . Objectives We tested two main hypotheses : ( 1 ) people who monitored their mood , stress , and coping strategies would have increased ESA from pretest to 6-week follow-up compared with an attention comparison group , and ( 2 ) an increase in ESA would predict a decrease in depressive symptoms . Methods We recruited patients aged 14 to 24 years from rural and metropolitan general practice s. Eligible participants were identified as having mild or more mental health concerns by their general practitioner . Participants were r and omly assigned to either the intervention group ( where mood , stress , and daily activities were monitored ) or the attention comparison group ( where only daily activities were monitored ) , and both groups self-monitored for 2 to 4 weeks . R and omization was carried out electronically via r and om seed generation , by an in-house computer programmer ; therefore , general practitioners , participants , and research ers were blinded to group allocation at r and omization . Participants completed pretest , posttest , and 6-week follow-up measures of the Depression Anxiety Stress Scale and the ESA Scale . We estimated a parallel process latent growth curve model ( LGCM ) using Mplus to test the indirect effect of the intervention on depressive symptoms via the mediator ESA , and calculated 95 % bias-corrected bootstrapping confidence intervals ( CIs ) . Results Of the 163 participants assessed for eligibility , 118 were r and omly assigned and 114 were included in analyses ( 68 in the intervention group and 46 in the comparison group ) . A parallel process LGCM estimated the indirect effect of the intervention on depressive symptoms via ESA and was shown to be statistically significant based on the 95 % bias-corrected bootstrapping CIs not containing zero ( –6.366 to –0.029 ) . The proportion of the maximum possible indirect effect estimated was κ2 = .54 ( 95 % CI .426–.640 ) . Conclusions This study supported the hypothesis that self-monitoring increases ESA , which in turn decreases depressive symptoms for young people with mild or more depressive symptoms . Mobile phone self-monitoring programs are ideally suited to first-step intervention programs for depression in the stepped-care approach , particularly when ESA is targeted as a mediating factor . Trial Registration Clinical Trials.gov NCT00794222 ; http:// clinical trials.gov/ct2/show/NCT00794222 ( Archived by WebCite at http://www.webcitation.org/65lldW34k BACKGROUND Longitudinal mood instability is the essential feature of bipolar disorder , however most rating scales are cross sectional in nature , and focus on acute symptoms . By contrast , the NIMH Life Chart Methodology ( LCM ) characterizes in detail the severity , duration , and frequency of mood episodes . Adherence to daily rating , however , tends to be low . In this study an online version of the LCM , design ed to enhance adherence , was compared to the st and ard paper version . METHODS Patients from a mood disorders specialty clinic were r and omized to the st and ard LCM or an online , open- source adaptation . The online version used hypertext links embedded in a daily email as the primary rating interface . Participants rated for 90 days . The total number of days rated and the number of days with complete data were compared for the two groups . RESULTS Forty-eight patients participated in the study . The online group rated approximately twice as many days compared to the st and ard group ( 44.3 versus 20.4 , p=.029 ) . The online group also entered complete data for a larger portion of days ( 55.2 % versus 27.7 % , p=.039 ) . LIMITATIONS This was a small , short-term study . The implication s for longer-term rating are unclear . CONCLUSIONS Despite the advantages of documenting mood fluctuation on a daily basis , the LCM is not commonly used , in part because ensuring adequate adherence can be re source intensive . An easily accessible online adaptation that utilizes email checking behavior can make this tool available to a wider range of patients Purpose : National guidelines recommend screening all persons with depression for bipolar disorder ( BPD ) ; one way to facilitate screening is through the use of electronic health records ( EHRs ) . This study examined the impact of an EHR-based screening and decision support tool on diagnosis and treatment of BPD among patients diagnosed with depression in primary care offices . Methods : This nonr and omized , controlled trial was conducted in a national network of offices using EHRs . The intervention included a screening instrument and other tools for diagnosis and management of BPD , which were embedded into the EHR . This instrument automatically activated when a patient with a diagnosis of depression but no diagnosis of BPD was seen in the office . The primary outcomes were the rates of new diagnoses of BPD and prescription of new BPD medications during the 6-month study period ( April to October 2009 ) . Results : Twenty-one offices with 75 clinicians and 8355 adult patients with depression composed the intervention group , whereas 17 offices with 81 clinicians and 8799 adult patients with depression served as the comparison group . The screening tool was used with 47.5 % of intervention patients , of whom 2.5 % scored at high or very high risk for BPD . Intervention patients were more likely than comparison patients to be newly diagnosed with BPD ( 1.11 % vs. 0.36 % ; P < .01 ) and be prescribed new BPD medications ( 1.85 % vs. 1.19 % ; P < .01 ) . Conclusions : The study suggests that EHR-based tools can be useful for screening and management of BPD for patients with depression in primary care offices BACKGROUND It has been difficult to improve care for severe mental illness ( SMI ) in usual care setting s because clinical information is not reliably and efficiently managed . Methods are needed for efficiently collecting this information to evaluate and improve health care quality . Audio computer-assisted self-interviewing ( ACASI ) can facilitate this data collection and has improved outcomes for a number of disorders , suggesting the need to test its accuracy and reliability in people with SMI . METHOD Ninety patients with DSM-IV schizophrenia or schizoaffective disorder ( N = 45 ) or bipolar disorder ( N = 45 ) recruited between Oct. 15 , 2002 , and July 1 , 2003 , were r and omly assigned to 1 of 2 study groups and completed 2 st and ardized symptom surveys ( Revised Behavior and Symptom Identification Scale and the symptom severity scale of the Schizophrenia Outcomes Module 2 ) 20 minutes apart in a crossover study design . Half of the patients first completed the scales via an in-person interview , and the other half first completed the scales via an  ACASI survey self-administered through an Internet browser using a touchscreen developed to meet the cognitive needs of people with SMI . We evaluated attitudes toward ACASI  , underst and ing of the ACASI survey , internal consistency , correlations between the ACASI and interview modes , concurrent validity , and a possible administration mode bias . RESULTS All ACASI and in-person interview scales had similar internal reliability , high correlations ( r = 0.78 - 1.00 ) , and mean scores similar enough as not to be different at p < .05 . A large majority rated the ACASI survey as easier , more enjoyable , more preferable if monthly completion of a survey were required , and more private , and 97 % to 99 % perfectly answered questions about how to use it . CONCLUSION ACASI data collection is reliable among people with bipolar disorder and schizophrenia and could be a valuable tool to improve their care The purpose of this study was to evaluate the psychometric properties of selected health-related quality of life ( HRQL )  self-report measures in 62 euthymic and depressed patients diagnosed with bipolar disorder . Patients completed the Quality of Life in Depression Scale ( QLDS ) , Mental Health Index-17 ( MHI-17 ) , Cognitive Function Scale , and Medical Outcomes Study Short Form-36 ( SF-36 ) at baseline and 8 weeks following treatment . Hamilton and Young Rating Scales were used to assess clinical status and vali date the HRQL measures . The MHI-17 , Cognitive Function Scale , QLDS , and SF-36 social function , vitality , role limitations -emotional , and mental health scales have good reliability and validity , and are responsive to changes in clinical status in patients with bipolar disorder . Although the small sample size limits generalizablity , euthymic and depressed out patients with bipolar disorder appear to contribute reliable self reports on selected aspects of their quality of life BACKGROUND Bipolar Disorder ( BD ) is a common and severe form of mental illness . Pharmacotherapy is the main treatment offered , but has limited effectiveness , and there is increasing evidence that people with BD respond well to psychological interventions . Inequalities in access to face-to-face psychological interventions mean many people seek support outside of routine health services . AIM To assess a recovery informed web-based self-management intervention for BD to increase access to psychological support . METHOD A small online r and omised controlled trial ( RCT ) will evaluate the feasibility , acceptability and potential effectiveness of the intervention compared to treatment as usual ( TAU ) .  Feasibility and acceptability will be assessed by recruitment , adherence and dropout rates , website usage statistics , user satisfaction scales and a series of qualitative interviews . Effectiveness will be assessed on a range of outcome measures including quality of life , mood symptoms , coping , recovery , and illness beliefs . ANALYSIS Rates of adherence and dropout will be analysed using logistic regression models with health , socioeconomic and treatment factors as explanatory variables . Changes in quality of life mean scores , contrasting between arms , will be assessed using r and om effects models . An exploratory analysis will be performed on the secondary outcomes . Thematic analysis ( Braun & Clarke , 2006 ) will be used to analyse the qualitative interviews . DISCUSSION The benefits , challenges and method ological challenges of developing a web-based intervention and conducting an RCT online are discussed . CONCLUSION The results of this trial will inform a definitive trial ; and the implementation phase will aim to assess the potential for use within the NHS BACKGROUND This study reports the outcome of a r and omized controlled trial of cognitive therapy ( CT ) for bipolar disorder . The treatment protocol differed from other published forms of CT for bipolar disorder through the addition of emotive techniques . METHOD Fifty-two patients with DSM-IV bipolar I or II disorder were r and omly allocated to a 6-month trial of either CT or treatment as usual , with both treatment groups also receiving mood stabilizers . Outcome measures included relapse rates , dysfunctional attitudes , psychosocial functioning , hopelessness , self-control , and medication adherence . Patients were assessed during treatment by independent raters blind to the patients ' group status . RESULTS At posttreatment , patients allocated to CT had experienced less severe depression scores ( Beck Depression Inventory and Montgomery-Asberg Depression Rating Scale ) and less dysfunctional attitudes . After controlling for the presence of major depressive episode at baseline , there was a statistical trend toward a greater time to depressive relapse ( p=.06 ) for the CT group . At 12-month follow-up , the CT group showed a trend toward lower Young Mania Rating Scale scores and improved behavioral self-control . The Clinical Global Impressions-Improvement scale , comparing the 18 months prior to treatment to the severity of illness status at follow-up , showed a substantial difference between groups in favor of CT . CONCLUSION Our findings corroborate previous bipolar disorder research in demonstrating the value of CT , particularly immediately post-treatment , and indicate some continuation ( albeit diminishing ) of benefits in the succeeding 12 months . These findings suggest that psychological booster sessions may be crucial for maintaining the beneficial effects of cognitive therapy OBJECTIVES Recent research indicates that Heart Rate Variability ( HRV ) is affected in Bipolar Disorders ( BD ) patients . To determine whether such alterations are a mere expression of the current mood state or rather contain longitudinal information on BD course , we examined the potential influence of states adjacent in time upon HRV features measured in a target mood state . METHODS Longitudinal evaluation of HRV was obtained in eight BD patients by using a wearable monitoring system developed within the PSYCHE project . We extracted time-domain , frequency-domain and non-linear HRV-features and trained a Support Vector Machine ( SVM ) to classify HRV-features according to mood state . To evaluate the influence of adjacent mood states , we trained SVM with different HRV-feature sets : 1 ) belonging to each mood state considered alone ; 2 ) belonging to each mood state and normalized using information from the preceding mood state ; 3 ) belonging to each mood state and normalized using information from the preceding and subsequent mood states ; 4 ) belonging to each mood state and normalized using information from two r and omly chosen states . RESULTS SVM classification accuracy within a target state was significantly greater when HRV-features from the previous and subsequent mood states were considered . CONCLUSIONS Although preliminary and in need of replications our results suggest for the first time that psychophysiological states in BD contain information related to the subsequent ones . Such characteristic may be used to improve clinical management and to develop algorithms to predict clinical course and mood switches in individual patients BACKGROUND Systematic and accurate depiction of a patient 's course of illness is crucial for assessing the efficacy of maintenance treatments for bipolar disorder . This need to rate the long-term prospect i ve course of illness led to the development of the National Institute of Mental Health prospect i ve Life Chart Methodology ( NIMH-LCM-p or LCM ) . The NIMH-LCM-p allows for the daily assessment of mood and episode severity based on the degree of mood associated functional impairment . We have previously presented preliminary evidence of the reliability and validity of the LCM , and its utility in clinical trials . This study is a further and more extensive validation of the clinician rated NIMH-LCM-p . METHODS Subjects included 270 bipolar patients from the five sites participating in the Stanley Foundation Bipolar Network . Daily prospect i ve LCM ratings on the clinician form were initiated upon entry , in addition to at least monthly ratings with the Inventory of Depressive Symptomatology-clinician rated ( IDS-C ) , the Young Mania Rating Scale ( YMRS ) and the Global Assessment of Functioning ( GAF ) . We correlated appropriate measures and time domains of the LCM with the IDS-C , YMRS and GAF . RESULTS Severity of depression on the LCM and on the IDS-C were highly correlated in 270 patients ( r = -0.785 , P < 0.001 ) . Similarly , a strong correlation was found between LCM mania and the YMRS ( r = 0.656 , P < 0.001 ) and between the LCM average severity of illness and the GAF ( r = -0.732 , P < 0.001 ) . CONCLUSIONS These data further demonstrate the validity and potential utility of the NIMH-LCM-p for the detailed daily longitudinal assessment of manic and depressive severity and course , and response to treatment
Conclusions  Electronic self-monitoring of mood in depression appears to be a valid measure of mood in contrast to self-monitoring of mood in mania .
Background Various paper-based mood charting instruments are used in the monitoring of symptoms in bipolar disorder .
During recent years an increasing number of electronic self-monitoring tools have been developed .
The objectives of this systematic review were 1 ) to evaluate the validity of electronic self-monitoring tools as a method of evaluating mood compared to clinical rating scales for depression and mania and 2 ) to investigate the effect of electronic self-monitoring tools on clinical ly relevant outcomes in bipolar disorder .
There are yet few studies on the effect of  electronic self-monitoring of mood  in bipolar disorder .