A Pilot Study of Mood Ratings Captured by Mobile Phone Versus Paper-and-Pencil Mood Charts in Bipolar Disorder Using Smartphones to Monitor Bipolar Disorder Symptoms: A Pilot Study 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 Co-Variation of Depressive Mood and Locomotor Dynamics Evaluated by Ecological Momentary Assessment in Healthy Humans Voice analysis as an objective state marker in bipolar disorder Daily electronic self-monitoring in bipolar disorder using smartphones - the MONARCA I trial: a randomized, placebo-controlled, single-blind, parallel group trial. Harnessing Context Sensing to Develop a Mobile Intervention for Depression Effects of a Multifaceted Psychiatric Intervention Targeted for the Complex Medically Ill: A Randomized Controlled Trial Breaking Open the Black Box: Isolating the Most Potent Features of a Web and Mobile Phone-Based Intervention for Depression, Anxiety, and Stress Cognitive impairment in the euthymic phase of affective disorder. Diabetes Distress but Not Clinical Depression or Depressive Symptoms Is Associated With Glycemic Control in Both Cross-Sectional and Longitudinal Analyses Association between bipolar spectrum features and treatment outcomes in outpatients with major depressive disorder. Efficacy of a Web-Based Intervention With Mobile Phone Support in Treating Depressive Symptoms in Adults With Type 1 and Type 2 Diabetes: A Randomized Controlled Trial Depressive symptoms and measures of disability: a prospective study. Switching from 'unipolar' to bipolar II. An 11-year prospective study of clinical and temperamental predictors in 559 patients. Hamilton depression rating scale and montgomery–asberg depression rating scale in depressed and bipolar I patients: psychometric properties in a Brazilian sample Does psychomotor agitation in major depressive episodes indicate bipolarity?
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 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 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 Computerized ecological momentary assessment ( EMA ) is widely accepted as a “ gold st and ard ” method for capturing momentary symptoms repeatedly experienced in daily life . Although many studies have addressed the within-individual temporal variations in momentary symptoms compared with simultaneously measured external criteria , their concurrent associations , specifically with continuous physiological measures , have not been rigorously examined . Therefore , in the present study , we first examined the variations in momentary symptoms by validating the associations among self-reported symptoms measured simultaneously ( depressive mood , anxious mood , and fatigue ) and then investigated covariant properties between the symptoms ( especially , depressive mood ) and local statistics of locomotor activity as the external objective criteria obtained continuously . Healthy subjects ( N = 85 ) from three different population s ( adolescents , undergraduates , and office workers ) wore a watch-type computer device equipped with EMA software for recording the momentary symptoms experienced by the subjects .  Locomotor activity data were also continuously obtained by using an actigraph built into the device . Multilevel modeling analysis confirmed convergent associations by showing positive correlations among momentary symptoms . The increased intermittency of locomotor activity , characterized by a combination of reduced activity with occasional bursts , appeared concurrently with the worsening of depressive mood . Further , this association remained statistically unchanged across groups regardless of group differences in age , lifestyle , and occupation . These results indicate that the temporal variations in the momentary symptoms are not r and om but reflect the underlying changes in psychophysiological variables in daily life . In addition , our findings on the concurrent changes in depressive mood and locomotor activity may contribute to the continuous estimation of changes in depressive mood and early detection of depressive disorders 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 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 Background Mobile phone sensors can be used to develop context -aware systems that automatically detect when patients require assistance . Mobile phones can also provide ecological momentary interventions that deliver tailored assistance during problematic situations . However , such approaches have not yet been used to treat major depressive disorder . Objective The purpose of this study was to investigate the technical feasibility , functional reliability , and patient satisfaction with Mobilyze ! , a mobile phone- and Internet-based intervention including ecological momentary intervention and context sensing . Methods We developed a mobile phone application and supporting architecture , in which machine learning models ( ie , learners ) predicted patients ’ mood , emotions , cognitive/motivational states , activities , environmental context , and social context based on at least 38 concurrent phone sensor values ( eg , global positioning system , ambient light , recent calls ) . The website included feedback graphs illustrating correlations between patients ’ self-reported states , as well as didactics and tools teaching patients behavioral activation concepts . Brief telephone calls and emails with a clinician were used to promote adherence . We enrolled 8 adults with major depressive disorder in a single-arm pilot study to receive Mobilyze ! and complete clinical assessment s for 8 weeks . Results Promising accuracy rates ( 60 % to 91 % ) were achieved by learners predicting categorical context ual states ( eg , location ) . For states rated on scales ( eg , mood ) , predictive capability was poor . Participants were satisfied with the phone application and improved significantly on self-reported depressive symptoms ( betaweek = –.82 , P < .001 , per- protocol Cohen d = 3.43 ) and interview measures of depressive symptoms ( betaweek = –.81 , P < .001 , per- protocol Cohen d = 3.55 ) . Participants also became less likely to meet criteria for major depressive disorder diagnosis ( bweek = –.65 , P = .03 , per- protocol remission rate = 85.71 % ) . Comorbid anxiety symptoms also decreased ( betaweek = –.71 , P < .001 , per- protocol Cohen d = 2.58 ) . Conclusions Mobilyze ! is a scalable , feasible intervention with preliminary evidence of efficacy . To our knowledge , it is the first ecological momentary intervention for unipolar depression , as well as one of the first attempts to use context sensing to identify mental health-related states . Several lessons learned regarding technical functionality , data mining , and software development process are discussed . Trial Registration Clinical trials.gov NCT01107041 ; http:// clinical trials.gov/ct2/show/NCT01107041 ( Archived by WebCite at http://www.webcitation.org/60CVjPH0n Background : This study evaluated a multifaceted psychiatric intervention targeted at the complex medically ill identified by means of the INTERMED , an instrument to assess case complexity . Methods : Of 885 rheumatology in patients and diabetes out patients who were assessed for eligibility , 247 were identified as complex ( INTERMED score > 20 ) and r and omized to the intervention ( n = 125 , 84 rheumatology and 41 diabetes patients ) or care as usual ( n = 122 , 78 rheumatology and 44 diabetes patients ) . For the majority of the cases the multifaceted intervention consisted of an intervention conducted by a psychiatric liaison nurse and /or of referral to a liaison psychiatrist , followed by advice to the treating physician or organization of a multidisciplinary case conference . Baseline and follow-up at months 3 , 6 , 9 and 12 measured prevalence of major depression ( Mini-International Neuropsychiatric Interview ) , depressive symptoms ( Center for Epidemiological Studies Depression Rating Scale ) , physical and mental health ( SF-36 ) , quality of life ( EuroQol ) , health care utilization and HbA1c levels ( diabetic patients ) . Results : Prevalence of major depression was reduced from 61 % ( T0 ) to 28 % ( T4 ) in the intervention group and remained stable in care as usual ( 57 % at T0 to 50 % at T4 ) . Compared to care as usual , significant improvement over time was observed in the intervention group with regard to depressive symptoms ( F = 11.9 ; p = 0.001 ) , perception of physical ( F = 5.7 ; p = 0.018 ) and mental health ( F = 3.9 ; p = 0.047 ) and quality of life ( F = 21.8 ; p < 0.001 ) . Effects tended to be stronger in diabetes patients , in patients with baseline major depression and in patients with moderate INTERMED scores . Finally , hospital admissions occurred less often in the intervention group , reaching statistical significance for the period between 6 and 9 months of follow-up ( p = 0.02 ) . Conclusions : The results suggest that a psychiatric intervention targeted for complex medical patients can improve health outcomes Background Internet-delivered mental health ( eMental Health ) interventions produce treatment effects similar to those observed in face-to-face treatment . However , there is a large degree of variation in treatment effects observed from program to program , and eMental Health interventions remain somewhat of a black box in terms of the mechanisms by which they exert their therapeutic benefit . Trials of eMental Health interventions typically use large sample sizes and therefore provide an ideal context within which to systematic ally investigate the therapeutic benefit of specific program features . Furthermore , the growth and impact of mobile phone technology within eMental Health interventions provides an opportunity to examine associations between symptom improvement and the use of program features delivered across computer and mobile phone platforms . Objective The objective of this study was to identify the patterns of program usage associated with treatment outcome in a r and omized controlled trial ( RCT ) of a fully automated , mobile phone- and Web-based self-help program , “ myCompass ” , for individuals with mild-to-moderate symptoms of depression , anxiety , and /or stress . The core features of the program include interactive psychotherapy modules , a symptom tracking feature , short motivational messages , symptom tracking reminders , and a diary , with many of these features accessible via both computer and mobile phone . Methods Patterns of program usage were recorded for 231 participants with mild-to-moderate depression , anxiety , and /or stress , and who were r and omly allocated to receive access to myCompass for seven weeks during the RCT .  Depression , anxiety , stress , and functional impairment were examined at baseline and at eight weeks . Results Log data indicated that the most commonly used components were the short motivational messages ( used by 68.4 % , 158/231 of participants ) and the symptom tracking feature ( used by 61.5 % , 142/231 of participants ) . Further , after controlling for baseline symptom severity , increased use of these alert features was associated with significant improvements in anxiety and functional impairment . Associations between use of symptom tracking reminders and improved treatment outcome remained significant after controlling for frequency of symptom tracking . Although correlations were not statistically significant , reminders received via SMS ( ie , text message ) were more strongly associated with symptom reduction than were reminders received via email . Conclusions These findings indicate that alerts may be an especially potent component of eMental Health interventions , both via their association with enhanced program usage , as well as independently . Although there was evidence of a stronger association between symptom improvement and use of alerts via the mobile phone platform , the degree of overlap between use of email and SMS alerts may have precluded identification of alert delivery modalities that were most strongly associated with symptom reduction . Future research using r and om assignment to computer and mobile delivery is needed to fully determine the most ideal platform for delivery of this and other features of online interventions . Trial Registration Australian New Zeal and Clinical Trials Registry ( ACTRN ) : 12610000625077 ; http://www.anzctr.org.au/Trial Search .aspx ? ( Archived by WebCite http://www.webcitation.org/6WPqHK0mQ ) BACKGROUND A review of studies of cognition in the euthymic phase of unipolar and bipolar affective disorder reveals diverging results . METHODS The study was design ed as a controlled cohort study , with the Danish psychiatric case register of admissions used to identify patients and the Danish civil register to identify controls . Patients who were hospitalized between 19 and 25 years ago with an affective diagnosis and who at interviews fulfilled criteria for a primary affective unipolar or bipolar disorder , according to ICD-10 , were compared with age- and gender-matched controls . Interviews and assessment of the cognitive function  were made in the euthymic phase of the disorder . In all , 118 unipolar patients , 28 bipolar patients and 58 controls were included . Analyses were adjusted for differences in the level of education and for sub clinical depressive and anxiety symptoms . RESULTS Patients with recurrent episodes were significantly more impaired than patients with a single episode and more impaired than controls . Also , within patients the number of prior episodes seemed to be associated with cognitive outcome . There was no difference in the severity of the dysfunction between unipolar and bipolar patients . CONCLUSIONS Cognitive impairment in out- patients with unipolar and bipolar disorder appears to be associated with the number of affective episodes OBJECTIVE To determine the concurrent , prospect i ve , and time-concordant relationships among  major depressive disorder ( MDD ) , depressive symptoms , and diabetes distress with glycemic control . RESEARCH DESIGN AND METHODS In a noninterventional study , we assessed 506 type 2 diabetic patients for MDD ( Composite International Diagnostic Interview ) , for depressive symptoms ( Center for Epidemiological Studies -Depression ) , and for diabetes distress ( Diabetes Distress Scale ) , along with self-management , stress , demographics , and diabetes status , at baseline and 9 and 18 months later . Using multilevel modeling ( MLM ) , we explored the cross-sectional relationships of the three affective variables with A1C , the prospect i ve relationships of baseline variables with change in A1C over time , and the time-concordant relationships with A1C . RESULTS All three affective variables were moderately intercorrelated , although the relationship between depressive symptoms and diabetes distress was greater than the relationship of either with MDD . In the cross-sectional MLM , only diabetes distress but not MDD or depressive symptoms was significantly associated with A1C . None of the three affective variables were linked with A1C in prospect i ve analyses . Only diabetes distress displayed significant time-concordant relationships with A1C . CONCLUSIONS We found no concurrent or longitudinal association between MDD or depressive symptoms with A1C , whereas both concurrent and time-concordant relationships were found between diabetes distress and A1C . What has been called “ depression ” among type 2 diabetic patients may really be two conditions , MDD and diabetes distress , with only the latter displaying significant associations with A1C . Ongoing evaluation of both  diabetes distress and MDD may be helpful in clinical setting CONTEXT It has been suggested that patients with major depressive disorder ( MDD ) who display pretreatment features suggestive of bipolar disorder or bipolar spectrum features might have poorer treatment outcomes . OBJECTIVE To assess the association between bipolar spectrum features and antidepressant treatment outcome in MDD . DESIGN Open treatment followed by sequential r and omized controlled trials . SETTING Primary and specialty psychiatric outpatient centers in the United States . PARTICIPANTS Male and female out patients aged 18 to 75 years with a DSM-IV diagnosis of nonpsychotic MDD who participated in the Sequenced Treatment Alternatives to Relieve Depression ( STAR*D ) study . INTERVENTIONS Open treatment with citalopram followed by up to 3 sequential next-step treatments . MAIN OUTCOME MEASURES Number of treatment levels required to reach protocol -defined remission , as well as failure to return for the postbaseline visit , loss to follow-up , and psychiatric adverse events . For this secondary analysis , putative bipolar spectrum features , including items on the mania and psychosis subscales of the Psychiatric Diagnosis Screening Question naire , were examined for association with treatment outcomes . RESULTS Of the 4041 subjects who entered the study , 1198 ( 30.0 % ) endorsed at least 1 item on the psychosis scale and 1524 ( 38.1 % ) described at least 1 recent maniclike/hypomaniclike symptom . Irritability and psychoticlike symptoms at entry were significantly associated with poorer outcomes across up to 4 treatment levels , as were shorter episodes and some neurovegetative symptoms of depression . However , other indicators of bipolar diathesis including recent maniclike symptoms and family history of bipolar disorder as well as summary measures of bipolar spectrum features were not associated with treatment resistance . CONCLUSION Self-reported psychoticlike symptoms were common in a community sample of out patients with MDD and strongly associated with poorer outcomes . Overall , the data do not support the hypothesis that unrecognized bipolar spectrum illness contributes substantially to antidepressant treatment resistance OBJECTIVE Depression is common in diabetes and linked to adverse health outcomes . This study evaluated the efficacy of a guided web-based intervention in reducing  depression in adults with type 1 and type 2 diabetes . RESEARCH DESIGN AND METHODS A total of 260 participants with diabetes and elevated depressive symptoms ( Center for Epidemiologic Studies Depression Scale [ CES-D ≥23 ] ) were r and omly assigned to the GET.ON  Mood Enhancer Diabetes ( a guided self-help intervention , n = 130 ) or a brief online unguided psychoeducation program for depression ( n = 130 ) . The primary outcome was depressive symptoms severity ( CES-D ) . The secondary outcomes included diabetes-specific emotional distress ( Problem Areas in Diabetes [ PAID ] scale ) and participant satisfaction ( adaption CSQ-8 ) . Data were collected at baseline and 2 months after r and omization . To identify differences in outcome between the groups , we used analyses of covariance with the baseline CES-D score as covariate on both intent-to-treat ( ITT ) and per- protocol ( PP ) basis . RESULTS Compared with the control group , the intervention group showed significantly less depressive symptom severity at posttreatment based on ITT ( d = 0.89 ) and PP analyses ( d = 1.00 ) . The intervention participants displayed a significantly larger reduction in diabetes-specific emotional distress ( d = 0.58 , ITT ) . The intervention appeared to be acceptable to the participants ; 95 % ( n = 121 ) would recommend the training to a friend with diabetes in need of psychological help . CONCLUSIONS A guided , web-based intervention to reduce depression in adults with type 1 and type 2 diabetes  is effective in reducing both depressive symptoms and diabetes-specific emotional distress OBJECTIVE The purpose of this study was to test the hypothesis that decreases in severity of depressive symptoms in patients with chronic tinnitus would correlate with reductions in measures of functional disability . METHOD This study describes the correlations between several measures of functional disability and Hamilton depression scores in two groups of patients with major depression and depressive symptoms ( D-NOS ) who were patients enrolled in a 12-week placebo-controlled , double-blind trial of nortriptyline . These patients had chronic severe tinnitus which was associated in most patients with high frequency hearing loss . The effect of whether affective symptoms improved and the patient 's initial depression status ( major depression versus depressive symptoms ) are examined in order to increase underst and ing about the correlations between depressive symptoms and functional disability . RESULTS Most measures of functional disability decreased synchronously with Hamilton Depression Scale scores in both patients with major depression and those with sub clinical depressive symptoms . Patients whose depression improved had a significantly greater change in each disability measure than patients whose depression did not improve . This significant decrease in functional disability was seen in 11 of 13 scales in the improved D-NOS group , versus only 3 of the 13 scales in the unimproved D-NOS group ; 9 of 13 scales of functional disability significantly decreased in the improved major depression group , versus 3 of 13 scales in the unimproved major depression group . CONCLUSIONS The results suggest that there was a significant correlation between improvement in both major depression and depression-NOS symptoms , and decreases in measures of functional disability in an aging population with a chronic medical illness BACKGROUND Given the therapeutic and prognostic importance of the unipolar-bipolar dichotomy , predicting which patients will become bipolar subsequent to index diagnosis of major depressive disorder ( MDD ) is of paramount clinical significance . We sought to characterize the profile of patients with MDD who would convert to the more subtle bipolar subtype ( known as BPII ) on the basis of clinical and personality variables obtained during MDD episodes . METHODS A total of 559 patients , comprehensively evaluated with the Schedule of Affective Disorders and Schizophrenia and " unipolar " MDD at entry , were administered 17 self-report personality measures .  Hypomanic and manic episodes were systematic ally recorded over a prospect i ve observation period of up to 11 years . We compared 48 converters to BPII ( 8.6 % ) with 22 converters to bipolar I ( BPI ) ( 3.9 % ) and the remaining larger group of unipolar patients . RESULTS Except for greater acuteness , severity , and psychotic symptomatology , BPI converters were essentially similar to MDD nonconverters . By contrast , BPII converters were robustly distinguished from those with MDD who remained unipolar on the basis of self-report measures along the newly derived factors of Mood Lability , Energy-Activity , and Daydreaming . This profile was associated with early age at onset of MDD and pleomorphic psychopathology beyond the usual affective realm , high rates of substance abuse , as well as educational , marital , and occupational disruption and minor antisocial acts prior to discrete hypomanic episodes . Overall , BPII switchers had a more protracted and tempestuous course with shorter well intervals . " Habitual self " descriptions of temperamental instability during MDD episodes provided useful clinical information for predicting which depressed patients will switch to BPII , attaining a sensitivity of 91 % for all three factors combined ( 23 items ) ; Mood Lability alone ( nine items ) was the most specific predictor ( 86 % ) , though of lower sensitivity ( 42 % ) . CONCLUSIONS The BPII subtype is best understood by such lability intruding into , and possibly its accentuation during , depressive episodes , thereby creating an intimate interweaving of trait and state . Clinicians must note that the foregoing temperamental profile appears more fundamental in defining the affective dysregulation of the BPII subtype than hypomanic episodes emphasized in DSM-IV Background The Hamilton Depression Rating Scale ( HAM-D ) and the Montgomery – Asberg Depression Scale ( MADRS ) are used worldwide and considered st and ard scales for evaluating depressive symptoms . This paper aims to investigate the psychometric proprieties ( reliability and validity ) of these scales in a Brazilian sample , and to compare responses in bipolar and unipolar patients . Methods The sample comprised 91 patients with either bipolar I or major depressive disorder from a psychiatric institute at São Paulo , Brazil . Participants were recruited and treated by clinicians through the Structured Interview for DSM-IV criteria  , and had previously been interviewed by a trained , blind tester . Results Both scales indicated good reliability properties ; however , the MADRS reliability statistics were higher than those of the HAM-D for detecting initial symptoms of unipolar depression . Correlation between the tests was moderate . Despite demonstrating adequate validity , neither test achieved the levels of sensitivity and specificity required for identification of a cutoff score to differentiate bipolar I and unipolar patients . Conclusions Both scales demonstrate adequate reliability and validity for assessing depressive symptoms in the Brazilian sample , and are good options to complement psychiatric diagnosis , but are not appropriate for distinguishing between the two affective disorder types Abstract Background Kraepelin ’s partial interpretation of agitated depression  as a mixed state of “ manic-depressive insanity ” ( including the current concept of bipolar disorder ) has recently been the focus of much research . This paper tested whether , how , and to what extent both psychomotor symptoms , agitation and retardation in depression are related to bipolarity and anxiety . Method The prospect i ve Zurich Study assessed psychiatric and somatic syndromes in a community sample of young adults ( N = 591 ) ( aged 20 at first interview ) by six interviews over 20 years ( 1979–1999 ) .  Psychomotor symptoms of agitation and retardation were assessed by professional interviewers from age 22 to 40 ( five interviews ) on the basis of the observed and reported behaviour within the interview section on depression . Psychiatric diagnoses were strictly operationalised and , in the case of bipolar-II disorder , were broader than proposed by DSM-IV-TR and ICD-10 . As indicators of bipolarity , the association with bipolar disorder , a family history of mania/hypomania/cyclothymia , together with hypomanic and cyclothymic temperament as assessed by the general  behavior inventory  ( GBI ) [ 15 ] , and mood lability ( an element of cyclothymic temperament ) were used . Results Agitated and retarded depressive states were equally associated with the indicators of bipolarity and with anxiety . Longitudinally , agitation and retardation were significantly associated with each other ( OR = 1.8 , 95 % CI = 1.0–3.2 ) , and this combined group of major depressives showed stronger associations with bipolarity , with both hypomanic/cyclothymic and depressive temperamental traits , and with anxiety . Among agitated , non-retarded depressives , unipolar mood disorder was even twice as common as bipolar mood disorder . Conclusion Combined agitated and retarded major depressive states are more often bipolar than unipolar , but , in general , agitated depression ( with or without retardation ) is not more frequently bipolar than retarded depression ( with or without agitation ) , and pure agitated depression is even much less frequently bipolar than unipolar . The findings do not support the hypothesis that agitated depressive syndromes are mixed states . Limitations The results are limited to a population up to the age of 40 ; bipolar-I disorders could not be analysed ( small N )
Hence , continuous and everyday monitoring of behavioral aspects in affective disorders could be a promising supplementary objective measure for estimating depressive mood symptoms .
BACKGROUND Several studies have recently reported on the correlation between objective behavioral features collected via mobile and wearable devices and depressive mood symptoms in patients with affective disorders ( unipolar and bipolar disorders ) .
However , individual studies have reported on different and sometimes contradicting results , and no quantitative systematic review of the correlation between objective behavioral features and depressive mood symptoms has been published .
OBJECTIVE The objectives of this systematic review were to ( 1 ) provide an overview of the correlations between objective behavioral features and depressive mood symptoms reported in the literature and ( 2 ) investigate the strength and statistical significance of these correlations across studies .
The answers to these questions could potentially help identify which objective features have shown most promising results across studies .