Portable technologies for digital phenotyping of bipolar disorder: A systematic review

Sleep and circadian disruption in bipolar disorders: From psychopathology to digital phenotyping in clinical practice

Sleep and biological rhythms are integral to mood regulation across the lifespan, particularly in bipolar disorder (BD), where alterations in sleep phase, structure, and duration occur in all mood states. These disruptions are linked to poorer quality of life, heightened suicide risk, impaired cognitive function, and increased relapse rates. This review highlights the pathophysiology of sleep disturbances in BD and aims to consolidate understanding and clinical applications of these phenomena. It also summarizes the evolution of sleep and biological rhythms assessment methods, including ecological momentary assessment (EMA) and digital phenotyping. It underscores the importance of recognizing circadian rhythm involvement in mood regulation, suggesting potential therapeutic targets. Future research directions include elucidating circadian clock gene mechanisms, understanding environmental impacts on circadian rhythms, and investigating the bidirectional relationship between sleep disturbances and mood regulation in BD. Standardizing assessment methods and addressing privacy concerns related to EMA technology and digital phenotyping are essential for advancing research. Collaborative efforts are crucial for enhancing clinical applicability and understanding the broader implications of biological rhythms in BD diagnosis and treatment. Overall, recognizing the significance of sleep and biological rhythms in BD offers promise for improved outcomes through targeted interventions and a deeper understanding of the disorder's underlying mechanisms.

Interventions targeting emotion regulation: A systematic umbrella review

BACKGROUND

Emotion dysregulation (ED), the difficulty in modulating which emotions are felt, and when and how they are expressed or experienced, has been implicated in an array of psychological disorders. Despite potentially different manifestations depending on the disorder, this symptom is emerging as a transdiagnostic construct that can and should be targeted early, given the associations with various maladaptive behaviors as early as childhood and adolescence. As such, our goal was to investigate the psychotherapeutic interventions used to address ED and gauge their effectiveness, safety, and potential mechanisms across various populations.

METHODS

This umbrella systematic review, pre-registered under PROSPERO (registration: CRD42023411452), consolidates evidence from systematic reviews and meta-analyses on psychotherapeutic interventions targeting ED, in accordance with PRISMA guidelines.

RESULTS

Our synthesis of quantitative and qualitative evidence from 21 systematic reviews (including 11 meta-analyses) points-with moderate overall risk of bias-to the effectiveness of Dialectical Behavior Therapy and Cognitive Behavioral Therapy in reducing ED in a wide range of adult transdiagnostic psychiatric patients and healthy participants. Similar results have emerged in other less extensively researched methods as well. However, results on adolescents and children are sparse, highlighting the need for additional research to tailor these interventions to the unique challenges of ED in younger populations with diverse externalizing and internalizing disorders.

CONCLUSIONS

These demonstrated transdiagnostic advantages of psychotherapy for ED underscore the potential for specifically designed interventions that address this issue directly, particularly for high-risk individuals. In these individuals, early interventions targeting transdiagnostic core dimensions may mitigate the emergence of full-blown disorders. Future research on the mediating factors, the durability of intervention effects, and the exploration of understudied interventions and populations may enhance prevention and treatment efficiency, enhancing the quality of life for those affected by varied manifestations of ED.

Digital Tools to Facilitate the Detection and Treatment of Bipolar Disorder: Key Developments and Future Directions

Bipolar disorder (BD) impacts over 40 million people around the world, often manifesting in early adulthood and substantially impacting the quality of life and functioning of individuals. Although early interventions are associated with a better prognosis, the early detection of BD is challenging given the high degree of similarity with other psychiatric conditions, including major depressive disorder, which corroborates the high rates of misdiagnosis. Further, BD has a chronic, relapsing course, and the majority of patients will go on to experience mood relapses despite pharmacological treatment. Digital technologies present promising results to augment early detection of symptoms and enhance BD treatment. In this editorial, we will discuss current findings on the use of digital technologies in the field of BD, while debating the challenges associated with their implementation in clinical practice and the future directions.

Psychiatric manifestations in moyamoya disease: more than a puff of smoke? a systematic review and a case-reports meta-analysis

Introduction

Moyamoya disease (MMD) is a life-threatening condition characterized by stenosis of intracranial arteries. Despite the frequency and the impact of psychiatric symptoms on the long-term prognosis and quality of life of MMD patients, no systematic review on this topic exists.

Methods

This systematic review and meta-analysis included 41 studies (29 being case reports), from PubMed, Scopus, Embase until 27/3/2023, on MMD patients exhibiting psychiatric symptoms.

Results

Despite a fair average quality of the articles, quantitative synthesis through logistic regression was possible only for case reports, due to heterogeneity between the other studies. Psychosis, the most frequent psychiatric symptom reported in case reports, was more frequent in MMD patients with left hemisphere involvement. Neurological symptoms occurrence increased the odds of MMD diagnosis preceding psychiatric symptoms. Psychiatric symptoms are highly prevalent in MMD patients and are relatively often the only presenting symptoms.

Discussion

We discuss the diagnostic, therapeutic, and prognostic implications of recognizing and characterizing specific psychiatric symptoms in MMD, outlining preliminary guidelines for targeted pharmacological and psychotherapeutic interventions. Lastly, we outline future research and clinical perspectives, striving to enhance the oft-overlooked psychiatric care for MMD patients and to ameliorate their long-term outcome.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023406303.

What digital health technology types are used in mental health prevention and intervention? Review of systematic reviews for systematization of technologies

Digital health technology has been widely applied to mental health interventions worldwide. Using digital phenotyping to identify an individual's mental health status has become particularly important. However, many technologies other than digital phenotyping are expected to become more prevalent in the future. The systematization of these technologies is necessary to accurately identify trends in mental health interventions. However, no consensus on the technical classification of digital health technologies for mental health interventions has emerged. Thus, we conducted a review of systematic review articles on the application of digital health technologies in mental health while attempting to systematize the technology using the Delphi method. To identify technologies used in digital phenotyping and other digital technologies, we included 4 systematic review articles that met the inclusion criteria, and an additional 8 review articles, using a snowballing approach, were incorporated into the comprehensive review. Based on the review results, experts from various disciplines participated in the Delphi process and agreed on the following 11 technical categories for mental health interventions: heart rate estimation, exercise or physical activity, sleep estimation, contactless heart rate/pulse wave estimation, voice and emotion analysis, self-care/cognitive behavioral therapy/mindfulness, dietary management, psychological safety, communication robots, avatar/metaverse devices, and brain wave devices. The categories we defined intentionally included technologies that are expected to become widely used in the future. Therefore, we believe these 11 categories are socially implementable and useful for mental health interventions.

Digital Phenotyping in Adults with Schizophrenia: A Narrative Review

PURPOSE OF REVIEW

As care for older adult patients with schizophrenia lacks innovation, technology can help advance the field. Specifically, digital phenotyping, the real-time monitoring of patients' behaviors through smartphone sensors and symptoms through surveys, holds promise as the method can capture the dynamicity and environmental correlates of disease.

RECENT FINDINGS

Few studies have used digital phenotyping to elucidate adult patients' experiences with schizophrenia. In this narrative review, we summarized the literature using digital phenotyping on adults with schizophrenia. No study focused solely on older adult patients. Studies including all adult patients were heterogeneous in measures used, duration, and outcomes. Despite limited research, digital phenotyping shows potential for monitoring outcomes such as negative, positive, and functional symptoms, as well as predicting relapse. Future research should work to target the symptomology persistent in chronic schizophrenia and ensure all patients have the digital literacy required to benefit from digital interventions and homogenize datasets to allow for more robust conclusions.

Dynamic functional hippocampal markers of residual depressive symptoms in euthymic bipolar disorder

OBJECTIVES

Bipolar disorder (BD) is a severe, chronic, affective disorder characterized by recurrent switching between mood states, psychomotor and cognitive symptoms, which can linger in euthymic states as residual symptoms. Hippocampal alterations may play a key role in the neural processing of BD symptoms. However, its dynamic functional connectivity (dFC) remains unclear. Therefore, the present study explores hippocampal dFC in relation to BD symptoms.

METHODS

We assessed hippocampus-based dFC coactivation patterns (CAPs) on resting-state fMRI data of 25 euthymic BD patients and 25 age- and sex-matched healthy controls (HC).

RESULTS

Bilateral hippocampal dFC with somatomotor networks (SMN) was reduced in BD, compared to HC, while at the same time dFC between the left hippocampus and midcingulo-insular salience system (SN) was higher in BD. Correlational analysis between CAPs and clinical scores revealed that dFC between the bilateral hippocampus and the default-like network (DMN) correlated with depression scores in BD. Furthermore, pathological hyperconnectivity between the default mode network (DMN) and SMN and the frontoparietal network (FPN) was modulated by the same depression scores in BD.

CONCLUSIONS

Overall, we observed alterations of large-scale functional brain networks associated with decreased flexibility in cognitive control, salience detection, and emotion processing in BD. Additionally, the present study provides new insights on the neural architecture underlying a self-centered perspective on the environment in BD patients. dFC markers may improve detection, treatment, and follow-up of BD patients and of disabling residual depressive symptoms in particular.

Limbic and cortical regions as functional biomarkers associated with emotion regulation in bipolar disorder: A meta-analysis of neuroimaging studies

BACKGROUND

Bipolar disorder (BD) is a psychiatric disorder characterized by episodes of depression and mania, associated with impaired emotion processing. Several functional MRI (fMRI) studies have been used to investigate the structural and functional alteration in BD. Here, we aim to investigate the current fMRI findings of brain activation during emotion-regulation tasks between BD patients and healthy controls (HC).

METHODS

A systematic search through PubMed database for fMRI studies on bipolar patients and HC yielded 685 studies. We performed an activation likelihood estimation (ALE) on 21 studies for emotion regulation in BD patients and HC. Furthermore, we performed subgroup analyses for task performances in response time and accuracy between bipolar patients and HC.

RESULTS

The total sample included 21 fMRI studies, comprising 543 BD patients, compared to 565 HC. ALE maps for emotion-related tasks showed hyperactivation in BD patients in the caudate, amygdala, precentral gyrus, middle frontal gyri, and sub-gyrus. Whereas hypoactivation was seen in the inferior frontal gyrus and anterior cingulate gyrus.

LIMITATIONS

We could not apply a correction for p-value thresholds, as it needs large number of foci. Second, functional abnormalities were investigated for adult BD patients only, as BD patients have functional differences correlated with age.

CONCLUSIONS

Our results showed that limbic and cortical regions can represent a potential biomarker for the diagnosis and management of BD, by showing clustered brain regions of abnormal patterns of increased activation between BD patients and HC.

Ubiquitous computing in light of human phenotypes: foundations, challenges, and opportunities

The interest in human phenotypes has leveraged interdisciplinary efforts encouraging a better understanding of the broad spectrum of psychological and behavioral disorders. Moreover, the usage of mobile and wearable devices along with unobtrusive computational capabilities provides an extensive amount of information that allows the characterization of phenotypes. This article describes the human phenotype through the lens of computational range and reviews state-of-the-art computational phenotyping. Furthermore, the article discusses computational phenotyping's extension concerning the combination of intelligent environments and personal mobile devices, addressing technical, managerial, and ethical challenges. This combination reinforces ubiquitous computational capabilities for phenotyping as a facilitator of interdisciplinary information convergence in favor of clinical and biomedical research.

Applications of Mendelian randomization in psychiatry: a comprehensive systematic review

Psychiatric diseases exact a heavy socioeconomic toll, and it is particularly difficult to identify their risk factors and causative mechanisms due to their multifactorial nature, the limited physiopathological insight, the many confounding factors, and the potential reverse causality between the risk factors and psychiatric diseases. These characteristics make Mendelian randomization (MR) a precious tool for studying these disorders. MR is an analytical method that employs genetic variants linked to a certain risk factor, to assess if an observational association between that risk factor and a health outcome is compatible with a causal relationship. We report the first systematic review of all existing applications and findings of MR in psychiatric disorders, aiming at facilitating the identification of risk factors that may be common to different psychiatric diseases, and paving the way to transdiagnostic MR studies in psychiatry, which are currently lacking. We searched Web of Knowledge, Scopus, and Pubmed databases (until 3 May 2022) for articles on MR in psychiatry. The protocol was preregistered in PROSPERO (CRD42021285647). We included methodological details and results from 50 articles, mainly on schizophrenia, major depression, autism spectrum disorders, and bipolar disorder. While this review shows how MR can offer unique opportunities for unraveling causal links in risk factors and etiological elements of specific psychiatric diseases and transdiagnostically, some methodological flaws in the existing literature limit reliability of results and probably underlie their heterogeneity. We highlight perspectives and recommendations for future works on MR in psychiatry.

Smartphone-based interventions in bipolar disorder: Systematic review and meta-analyses of efficacy. A position paper from the International Society for Bipolar Disorders (ISBD) Big Data Task Force

BACKGROUND

The clinical effects of smartphone-based interventions for bipolar disorder (BD) have yet to be established.

OBJECTIVES

To examine the efficacy of smartphone-based interventions in BD and how the included studies reported user-engagement indicators.

METHODS

We conducted a systematic search on January 24, 2022, in PubMed, Scopus, Embase, APA PsycINFO, and Web of Science. We used random-effects meta-analysis to calculate the standardized difference (Hedges' g) in pre-post change scores between smartphone intervention and control conditions. The study was pre-registered with PROSPERO (CRD42021226668).

RESULTS

The literature search identified 6034 studies. Thirteen articles fulfilled the selection criteria. We included seven RCTs and performed meta-analyses comparing the pre-post change in depressive and (hypo)manic symptom severity, functioning, quality of life, and perceived stress between smartphone interventions and control conditions. There was significant heterogeneity among studies and no meta-analysis reached statistical significance. Results were also inconclusive regarding affective relapses and psychiatric readmissions. All studies reported positive user-engagement indicators.

CONCLUSION

We did not find evidence to support that smartphone interventions may reduce the severity of depressive or manic symptoms in BD. The high heterogeneity of studies supports the need for expert consensus to establish ideally how studies should be designed and the use of more sensitive outcomes, such as affective relapses and psychiatric hospitalizations, as well as the quantification of mood instability. The ISBD Big Data Task Force provides preliminary recommendations to reduce the heterogeneity and achieve more valid evidence in the field.