Abstract Background The temporal relationship between sleep and mood changes in bipolar disorder (BD) has been investigated before, and this paper aims to replicate results from previous analyses while adding new details to the understanding of the relationship between fluctuations of sleep and mood. Furthermore, we comment on the use of sleep changes as a prodrome to mood changes in BD, which could improve clinical outcomes. Methods BD outpatients in remission (N = 29) recorded daily their sleep of the past 24 h and rated their mood on a visual analogue scale for 1 year (total of 9,433 days). Cross-correlation functioning was employed to identify potential relationships between self-reported sleep values and mood scores, for both the days before and after a change in mood. Results 41% of participants reported a negative relationship between changes in total time spent in bed and mood the following day, e.g. spending more time in bed before a shift towards depressive symptoms. Additionally, 21%-28% of all participants experienced an increase (or decrease) in their 7-day sleep average (sleep duration and awake in bed duration) in the week before a change in mood towards a lower (or higher) score. Only a few participants showed any relationship between changes in the 7-day variability of sleep and mood change. Conclusion Our findings align with and support those of earlier studies with similar designs. The duration of sleep and time in bed may serve as early indicators of mood changes in BD for about two-fifths of patients, and integrating these symptoms into clinical practice may help anticipate critical clinical shifts.

Background:Bipolar disorders (BDs) represent a significant global health challenge, with frequent and severe affective episodes that impair quality of life. Accurate, early prediction of these episodes remains difficult. Recent advances in mobile sensing offer new possibilities to detect prodromal changes via smart digital phenotypes, such as geolocation data. Objective:This study aimed to examine whether spatial exploratory behavior, assessed via passive GPS data, can predict depressive and manic episodes in individuals with BD. Specifically, we evaluated the predictive value of unique places visited and related mobility metrics using statistical process control (SPC) techniques to identify both early deviations indicative of prodromal states and changes occurring during ongoing affective episodes. Methods:Using high-resolution GPS data from the BipoSense dataset, we applied Density-Based Spatial Clustering of Applications with Noise to extract behavioral mobility indicators: number of unique places visited, frequency of location changes, and time spent per location. We implemented exponentially weighted moving average (EWMA)-based SPC to identify "out-of-bounds" deviations from individual baselines. We then tested the alignment of these deviations with affective episodes and the prodromal periods. Optimization of SPC parameters (λ and control limit L) was performed to enhance predictive accuracy. Results:The analysis included 28 participants with BD and a total of 10,213 observation days, covering 26 depressive and 20 (hypo)manic episodes. Examining whether control limits distinguish affective episodes from euthymic days via multilevel models revealed that median time spent at clusters indicated both depressive and (hypo)manic episodes the best, whereas the number of unique clusters showed no significant association with phase transitions. While EWMA-SPC detected behavioral deviations during affective episodes, no single variable consistently met predefined thresholds for both sensitivity and specificity. Optimized SPC settings improved performance, but the number of unique places alone did not robustly predict prodromal or acute episodes. No statistically significant predictive accuracy (eg, sensitivity >70% and specificity >70%) was achieved for any individual indicator (P>.05). However, some SPC charts suggested within-person temporal deviations preceding episodes, indicating limited yet potentially informative patterns. Conclusions:Although unique places visited alone may not suffice as a predictive marker, the application of EWMA-based SPC to GPS data holds promise for the development of smart digital phenotypes. Although our analysis to predict upcoming episodes did not yield robust predictive accuracy in its current form, it provides a promising conceptual framework for individualized, low-burden behavioral monitoring. Further research is needed to refine existing digital biomarkers, develop new ones, and validate their clinical utility in reducing the frequency and severity of illness phases.

Background Bipolar disorder (BD) is a recurrent disorder, characterised by episodes of (hypo)mania, depression and euthymia with variation in mood, cognition and sleep. Many patients identify changes in sleep before an episode; using daily sleep logs could help identify these changes. Such early warning signs can be a valuable tool for patients and clinicians alike in predicting and preparing for changes in mood.Methods In the BipoSense study, we followed patients with BD, who were in remission at the start of the study, daily for 1 year. Patients reported for each hour if they were awake or asleep through an app and received fortnightly clinical assessments of bipolar symptoms. We used statistical analyses applying person-centred data in multilevel logit models to investigate if sleep patterns could differentiate between the period before an episode (prodromal stage) and euthymia, looking at both mean changes and variability of sleep. Bonferroni-Holm corrections were applied to avoid inflation of type I errors from multiple testing.Results Twenty-nine participants were included (mean age 44.0 years [SD = 11.9], female 55% and BD-I 59%). Waking up later was associated with prodromal depression and was the only significant finding for prodromal mood episodes. Greater variability of sleep duration, total time spent in bed and time waking up were associated with prodromal depression; less variability of time falling asleep and time waking up were linked with prodromal (hypo)mania.Conclusion Using self-assessed sleep changes and especially variability can be potential tools in helping patients identify early warning signs of mood recurrence; however, these analyses were explorative and further investigations are warranted.

Die Manie ist ein facettenreiches psychopathologisches Phänomen. Ziel jeder Behandlung sind das Aufrechterhalten bzw. Wiedererlangen eines hohen psychosozialen Funktionsniveaus und das Abwenden von Schäden, die durch krankheitsbedingte Verhaltensstörungen entstehen können. Moderne Therapiekonzepte sind trialogisch ausgerichtet und vereinen psychotherapeutische, sozialmedizinische sowie chronotherapeutische Ansätze mit einer gezielten Pharmakotherapie.

INTRODUCTION:Most people with bipolar disorder (BD) experience sleep disturbances across mood states and many identify sleep changes before both depressive and manic episodes. Nearly half of all patients have multiple relapses of BD and identifying early warning signs of relapse, such as sleep changes, could benefit both patients and clinicians as a preventive strategy. METHODS:A systematic search of the databases Embase, APA PsychINFO, and MEDLINE was performed to identify studies that investigated the relationship between sleep changes and mood in BD. The review was registered with PROSPERO (CRD42023405950) and followed the PRISMA guidelines. Results were categorised based on the identified relationship between sleep changes and mood, e.g. sleep and depression correlation, and these are synthesised narratively. The Newcastle-Ottawa scale was used to assess the risk of bias (RoB). RESULTS:The systematic literature search yielded 7159 records. 17 publications were included, describing 13 studies. Nine categories were identified describing the relationship between sleep and mood (e.g. sleep-mood correlations and comparing BD and HC on sleep duration). Regardless of sleep assessment (e.g. actigraphy), study duration or mood outcome, changes towards longer sleep, earlier onset and later wake-up were mostly followed by depressive mood, and vice versa for mania. 14 papers had a "fair" RoB rating. DISCUSSION:Changes in sleep patterns appear to precede predictable mood changes in BD and could be used as early warning signs for patients and clinicians. The main limitation of the study is the high heterogeneity between study results, preventing the conduction of a meta-analysis.

Abstract Objectives Lithium (Li) remains one of the most valuable treatment options for mood disorders. However, current knowledge about prescription practices in Germany is limited. The objective of this study is to estimate the prevalence of current Li use over time and in selected diagnoses, highlighting clinically relevant aspects such as prescription rates in elderly patients, concomitant medications, important drug–drug interactions, and serious adverse events. Methods We conducted a descriptive analysis of Li prescriptions, analyzing data from the ongoing Bavarian multicenter drug safety project Pharmaco-Epidemiology and Vigilance (Pharmako-EpiVig) from the years 2014–2021. Our study included 97,422 inpatients, 4543 of whom were prescribed Li. Results The Li prescription rate in unipolar depression (UD) remained constant at 4.6% over the observational period. In bipolar disorder (BD), the prescription rate increased significantly from 28.8% in 2014 to 34.4% in 2019. Furthermore, 30.3% of patients with Li prescriptions did not have a diagnosis of BD or UD, and 15.3% of patients with schizoaffective disorder were prescribed Li. The majority (64%) of patients with Li prescriptions were prescribed five or more drugs. Most of the 178 high-priority drug–drug interactions were due to hydrochlorothiazide (N = 157) followed by olmesartan (N = 16). Conclusion Our study does not substantiate concerns about a decline in Li prescription. The decline in prescription rates observed in some diagnostic groups in 2020 and 2021 may be associated with the COVID-19 pandemic. The symptom-oriented use of Li beyond BD and UD is common. Polypharmacy and drug–drug interactions present a challenge in Li therapy. Old age and comorbid substance use disorder do not appear to be major deterrents for clinicians to initiate Li therapy.

Background Lithium has long been considered the gold-standard pharmacological treatment for the maintenance treatment of bipolar disorders (BD) which is supported by a wide body of evidence. Prior research has shown a steady decline in lithium prescriptions during the last two decades. We aim to identify potential factors explaining this decline across the world with an anonymous worldwide survey developed by the International Society for Bipolar Disorders (ISBD) Task Force “Role of Lithium in Bipolar Disorders” and distributed by diverse academic and professional international channels. Results A total of 886 responses were received of which 606 completed the entire questionnaire while 206 completed it partially. Respondents were from 43 different countries comprising all continents. Lithium was the most preferred treatment option for the maintenance of BD patients (59%). The most relevant clinical circumstances in which lithium was the preferred option were in patients with BD I (53%), a family history of response (18%), and a prior response during acute treatment (17%). In contrast, Lithium was not the preferred option in case of patients´ negative beliefs and/or attitudes towards lithium (13%), acute side-effects or tolerability problems (10%) and intoxication risk (8%). Clinicians were less likely to prefer lithium as a first option in BD maintenance phase when practising in developing economy countries [X2 (1, N = 430) = 9465, p = 0.002) ] and private sectors [X2 (1, N = 434) = 8191, p = 0.004)]. Conclusions Clinicians’ preferences and attitudes towards the use of lithium in the maintenance treatment of bipolar disorders appear to be affected by both the patients’ beliefs and the professional contexts where clinicians provide their services. More research involving patients is needed for identifying their attitudes toward lithium and factors affecting its use, particularly in developing economies.

Abstract Background Research suggests that a low omega-3 index may contribute to the low heart rate variability and the increased risk of cardiovascular morbidity and mortality in bipolar disorders. However, so far, no intervention trial with EPA and DHA has been conducted in bipolar patients attempting to increase their heart rate variability. Methods 119 patients with bipolar disorder according to DSM-IV were screened, with 55 euthymic bipolar patients—owing to inclusion criteria (e.g. low omega-3 index (< 6%), SDNN < 60 ms.)—being enrolled in a randomized, double-blind, 12-week parallel study design with omega-3 fatty acids (4 capsules of 530 mg EPA, 150 mg DHA) or corn oil as a placebo, in addition to usual treatment. Heart rate variability as well as the omega-3 index were measured at baseline and at the endpoint of the study. Results A total of 42 patients (omega-3: n = 23, corn oil: n = 19) successfully completed the study after 12 weeks. There was a significant increase in the omega-3 index (value at endpoint minus value at baseline) in the omega-3 group compared to the corn oil group (p < 0.0001). However, there was no significant difference in the change of the SDNN (value at endpoint minus value at baseline) between the treatment groups (p = 0.22). In addition, no correlation between changes in SDNN and change in the omega-3 index could be detected in the omega-3 group (correlation coefficient = 0.02, p = 0.94) or the corn oil group (correlation coefficient = − 0.11, p = 0.91). Similarly, no significant differences between corn oil and omega-3 group regarding the change of LF (p = 0.19), HF (p = 0.34) and LF/HF ratio (p = 0.84) could be demonstrated. Conclusions In our randomized, controlled intervention trial in euthymic bipolar patients with a low omega-3 index and reduced heart rate variability no significant effect of omega-3 fatty acids on SDNN or frequency-domain measures HF, LF and LF/HF ratio could be detected. Possible reasons include, among others, the effect of psychotropic medication present in our trial and/or the genetics of bipolar disorder itself. Further research is needed to test these hypotheses. Trial registration ClinicalTrials.gov, NCT00891826. Registered 01 May 2009–Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT00891826

This narrative review summarizes and discusses the implications of the Diagnostic and Statistical Manual of Mental Disorders (DSM)-5 and the upcoming International Classification of Diseases (ICD)-11 classification systems on the prevalence of bipolar disorder and on the validity of the DSM-5 diagnosis of bipolar disorder according to the Robin and Guze criteria of diagnostic validity. Here we review and discuss current data on the prevalence of bipolar disorder diagnosed according to DSM-5 versus DSM-IV, and data on characteristics of bipolar disorder in the two diagnostic systems in relation to extended Robin and Guze criteria: 1) clinical presentation, 2) associations with para-clinical data such as brain imaging and blood-based biomarkers, 3) delimitation from other disorders, 4) associations with family history / genetics, 5) prognosis and long-term follow-up, and 6) treatment effects. The review highlights that few studies have investigated consequences for the prevalence of the diagnosis of bipolar disorder and for the validity of the diagnosis. Findings from these studies suggest a substantial decrease in the point prevalence of a diagnosis of bipolar with DSM-5 compared with DSM-IV, ranging from 30-50%, but a smaller decrease in the prevalence during lifetime, corresponding to a 6% reduction. It is concluded that it is likely that the use of DSM-5 and ICD-11 will result in diagnostic delay and delayed early intervention in bipolar disorder. Finally, we recommend areas for future research.

Background Internet of Things (IoT) devices for remote monitoring, diagnosis, and treatment are widely viewed as an important future direction for medicine, including for bipolar disorder and other mental illness. The number of smart, connected devices is expanding rapidly. IoT devices are being introduced in all aspects of everyday life, including devices in the home and wearables on the body. IoT devices are increasingly used in psychiatric research, and in the future may help to detect emotional reactions, mood states, stress, and cognitive abilities. This narrative review discusses some of the important fundamental issues related to the rapid growth of IoT devices. Main body Articles were searched between December 2019 and February 2020. Topics discussed include background on the growth of IoT, the security, safety and privacy issues related to IoT devices, and the new roles in the IoT economy for manufacturers, patients, and healthcare organizations. Conclusions The use of IoT devices will increase throughout psychiatry. The scale, complexity and passive nature of data collection with IoT devices presents unique challenges related to security, privacy and personal safety. While the IoT offers many potential benefits, there are risks associated with IoT devices, and from the connectivity between patients, healthcare providers, and device makers. Security, privacy and personal safety issues related to IoT devices are changing the roles of manufacturers, patients, physicians and healthcare IT organizations. Effective and safe use of IoT devices in psychiatry requires an understanding of these changes.

Background Bipolar disorder is associated with circadian disruption and a high risk of suicidal behavior. In a previous exploratory study of patients with bipolar I disorder, we found that a history of suicide attempts was associated with differences between winter and summer levels of solar insolation. The purpose of this study was to confirm this finding using international data from 42% more collection sites and 25% more countries. Methods Data analyzed were from 71 prior and new collection sites in 40 countries at a wide range of latitudes. The analysis included 4876 patients with bipolar I disorder, 45% more data than previously analyzed. Of the patients, 1496 (30.7%) had a history of suicide attempt. Solar insolation data, the amount of the sun’s electromagnetic energy striking the surface of the earth, was obtained for each onset location (479 locations in 64 countries). Results This analysis confirmed the results of the exploratory study with the same best model and slightly better statistical significance. There was a significant inverse association between a history of suicide attempts and the ratio of mean winter insolation to mean summer insolation (mean winter insolation/mean summer insolation). This ratio is largest near the equator which has little change in solar insolation over the year, and smallest near the poles where the winter insolation is very small compared to the summer insolation. Other variables in the model associated with an increased risk of suicide attempts were a history of alcohol or substance abuse, female gender, and younger birth cohort. The winter/summer insolation ratio was also replaced with the ratio of minimum mean monthly insolation to the maximum mean monthly insolation to accommodate insolation patterns in the tropics, and nearly identical results were found. All estimated coefficients were significant at p < 0.01. Conclusion A large change in solar insolation, both between winter and summer and between the minimum and maximum monthly values, may increase the risk of suicide attempts in bipolar I disorder. With frequent circadian rhythm dysfunction and suicidal behavior in bipolar disorder, greater understanding of the optimal roles of daylight and electric lighting in circadian entrainment is needed.

Bipolare Störungen sind psychiatrische Erkrankungen mit einem großen Symptomspektrum. Der Verlauf ist von euthymen, depressiven, gemischten und (hypo)manischen Episoden ge­ kennzeichnet. Bei schweren affektiven Episoden treten nicht selten psychotische Symptome auf. Für Deutschland ist die im Jahr 2019 revidierte S3­Leitlinie „Diagnostik und Therapie Bipolarer Störungen“ sowohl für die Akut­ als auch für die Langzeitbehandlung von besonderer Relevanz. Lithium stellt nach wie vor den Goldstandard in der Rezidivprophylaxe bipolarer Störungen dar.

Abstract Background Using U.S. pharmacy and medical claims, medication adherence patterns of patients with serious mental illness suggest that adherence to atypical antipsychotics may be related to adherence to other prescription drugs. This study investigated whether adherence to an atypical antipsychotic was related to adherence to other prescribed psychiatric drugs using self-reported data from patients with bipolar disorder. Methods Daily self-reported medication data were available from 123 patients with a diagnosis of bipolar disorder receiving treatment as usual who took at least 1 atypical antipsychotic over a 12-week period. Patients took a mean of 4.0±1.7 psychiatric drugs including the antipsychotic. The adherence rate for the atypical antipsychotic was compared to that for other psychiatric drugs to determine if the adherence rate for the atypical antipsychotic differed from that of the other psychiatric drug by at least ±10%. Results Of the 123 patients, 58 (47.2%) had an adherence rate for the atypical antipsychotic that differed from the adherence rate for at least 1 other psychiatric drug by at least±10%, and 65 (52.8%) patients had no difference in adherence rates. The patients with a difference took a larger total number of psychiatric drugs (p<0.001), had a larger daily pill burden (p=0.020) and a lower adherence rate with the atypical antipsychotic (p=0.007), and were more likely to take an antianxiety drug (p<0.001). Conclusion Adherence with an atypical antipsychotic was not useful for estimating adherence to other psychiatric drugs in about half of the patients with bipolar disorder.

Bipolar disorder (BD) is a major healthcare and socio-economic challenge. Despite its substantial burden on society, the research activity in BD is much smaller than its economic impact appears to demand. There is a consensus that the accurate identification of the underlying pathophysiology for BD is fundamental to realize major health benefits through better treatment and preventive regimens. However, to achieve these goals requires coordinated action and innovative approaches to boost the discovery of the neurobiological underpinnings of BD, and rapid translation of research findings into development and testing of better and more specific treatments. To this end, we here propose that only a large-scale coordinated action can be successful in integrating international big-data approaches with real-world clinical interventions. This could be achieved through the creation of a Global Bipolar Disorder Foundation, which could bring government, industry and philanthropy together in common cause. A global initiative for BD research would come at a highly opportune time given the seminal advances promised for our understanding of the genetic and brain basis of the disease and the obvious areas of unmet clinical need. Such an endeavour would embrace the principles of open science and see the strong involvement of user groups and integration of dissemination and public involvement with the research programs. We believe the time is right for a step change in our approach to understanding, treating and even preventing BD effectively.

Background Major depressive disorder is a common, recurrent, disabling and costly disorder that is often severe and/or chronic, and for which non-remission on guideline concordant first-line antidepressant treatment is the norm. A sizeable percentage of patients diagnosed with MDD do not achieve full remission after receiving antidepressant treatment. How to understand or approach these 'refractory', 'TRD' or 'difficult to treat' patients need to be revisited. Treatment resistant depression (TRD) has been described elsewhere as failure to respond to adequate treatment by two different antidepressants. This definition is problematic as it suggests that TRD is a subtype of major depressive disorder (MDD), inferring a boundary between TRD and depression that is not treatment resistant. However, there is scant evidence to suggest that a discrete TRD entity exists as a distinct subtype of MDD, which itself is not a discrete or homogeneous entity. Similarly, the boundary between TRD and other forms of depression is predicated at least in part on regulatory and research requirements rather than biological evidence or clinical utility. Aim This paper aims to investigate the notion of treatment failure in order to understand (i) what is TRD in the context of a broader formulation based on the understanding of depression, (ii) what factors make an individual patient difficult to treat, and (iii) what is the appropriate and individualised treatment strategy, predicated on an individual with refractory forms of depression? Method Expert contributors to this paper were sought internationally by contacting representatives of key professional societies in the treatment of MDD - World Federation of Societies for Biological Psychiatry, Australasian Society for Bipolar and Depressive Disorders, International Society for Affective Disorders, Collegium Internationale Neuro-Psychopharmacologium and the Canadian Network for Mood and Anxiety Treatments. The manuscript was prepared through iterative editing. Outcomes The concept of TRD as a discrete subtype of MDD, defined by failure to respond to pharmacotherapy, is not supported by evidence. Between 15 and 30% of depressive episodes fail to respond to adequate trials of 2 antidepressants, and 68% of individuals do not achieve remission from depression after a first-line course of antidepressant treatment. Failure to respond to antidepressant treatment, somatic therapies or psychotherapies may often reflect other factors including; biological resistance, diagnostic error, limitations of current therapies, psychosocial variables, a past history of exposure to childhood maltreatment or abuse, job satisfaction, personality disorders, co-morbid mental and physical disorders, substance use or non-adherence to treatment. Only a subset of patients not responding to antidepressant treatment can be explained through pharmacokinetic or pharmacodynamics mechanisms. We propose that non remitting MDD should be personalised, and propose a strategy of 'deconstructing depression'. By this approach, the clinician considers which factors contribute to making this individual both depressed and 'resistant' to previous therapeutic approaches. Clinical formulation is required to understand the nature of the depression. Many predictors of response are not biological, and reflect a confluence of biological, psychological, and sociocultural factors, which may influence the illness in a particular individual. After deconstructing depression at a personalised level, a personalised treatment plan can be constructed. The treatment plan needs to address the factors that have contributed to the individual's hard to treat depression. In addition, an individual with a history of illness may have a lot of accumulated life issues due to consequences of their illness, and these should be addressed in a recovery plan. Limitations A 'deconstructing depression' qualitative rubric does not easily provide clear inclusion and exclusion criteria for researchers wanting to investigate TRD. Conclusions MDD is a polymorphic disorder and many individuals who fail to respond to standard pharmacotherapy and are considered hard to treat. These patients are best served by personalised approaches that deconstruct the factors that have contributed to the patient's depression and implementing a treatment plan that adequately addresses these factors. The existence of TRD as a discrete and distinct subtype of MDD, defined by two treatment failures, is not supported by evidence.

The editorial by Malhi et al1 is a timely and most welcome wake-up call regarding the declining use of lithium in the long-term maintenance treatment of bipolar disorders. In support of the issues discussed, we would like to stress several topics which we believe can further help to make a better life for as many patients with bipolar disorders as possible. Given its long-term effectiveness as evidenced in randomized controlled studies as well as in naturalistic observational studies,2 lithium is the gold standard in the maintenance treatment of bipolar disorders. When used properly, lithium can bring about dramatic improvements in the course of this disease, with, in general, good tolerability, also in comparison with other approved treatment options. However, it is not a panacea for every individual patient at every stage of the disease. There is a significant number of patients who do not respond to or do not tolerate the usually recommended therapeutic serum concentrations of 0.6–0.8 mmol/L3. Given its potential toxicity, lithium is a drug for the informed cooperating patient, who has developed an acceptance regarding his illness and the need for long-term medication and regular check-ups. As suggested by Malhi et al,1 high-quality group psychoeducation may greatly help for the majority of patients for successful long-term treatment with lithium based on “shared decision making” with an openness to flexible patient-centered solutions with regard to dosage issues, side-effect management,4 and stand-by add-on/combination treatment. Under the above conditions, lithium should be offered and recommended to every patient with bipolar disorders early in the course of the disease as the mainstay of long-term treatment. Against this background, lithium should also be used more often in the acute treatment of manic episodes, if needed in combination with other mood-stabilizing drugs that are approved for this purpose and may have a more rapid onset of action, in order to facilitate the path to successful long-term treatment with lithium. Do we still need "better" drugs for treating bipolar disorders5? Of course we do! Until then, however, we should use lithium, the best currently available treatment option we have for treating bipolar disorders, much more frequently—corresponding to the available scientific evidence.

There has been increasing interest in the use of smartphone applications (apps) and other consumer technology in mental health care for a number of years. However, the vision of data from apps seamlessly returned to, and integrated in, the electronic medical record (EMR) to assist both psychiatrists and patients has not been widely achieved, due in part to complex issues involved in the use of smartphone and other consumer technology in psychiatry. These issues include consumer technology usage, clinical utility, commercialization, and evolving consumer technology. Technological, legal and commercial issues, as well as medical issues, will determine the role of consumer technology in psychiatry. Recommendations for a more productive direction for the use of consumer technology in psychiatry are provided.