Clinical Research Directory

Transcranial Photobiomodulation for Bipolar Depression

This study the effectiveness and safety of light therapy device targeted at the brain using a wearable device, the Vielight RX Gamma as a treatment for bipolar depression. Up to forty patients with bipolar disorder will be enrolled into the study and will either receive active treatment with the Vielight RX Gamma or sham (inactive device). They will be administered the devices in clinic 5days/week for 6 weeks. Changes in disease symptoms, cognitive function, pain, quality of life and rest EEG changes will be assessed.

Incentives and Long-Acting Injectable Adherence After Involuntary Hospitalization

This study is a randomized controlled trial evaluating the impact of financial incentives on medication adherence among individuals with schizophrenia, schizoaffective disorder, or bipolar disorder and/or co-occurring substance use disorder who are recently discharged from involuntary hospitalization or are at high risk of future involuntary hospitalization. Participants will be randomized to receive financial incentives for adherence to long-acting injectable medications or to a control group.

Time Restricted Eating (TRE) in Bipolar Disorder

This is a randomized controlled trial investigating the effects of an 8-TRE intervention compared to a wait list (control) on metabolic health and body composition in people diagnosed with BD and who are currently obese and at least mildly depressed. Following a 1-week baseline assessment, participants will be randomized to either a TRE or the wait list (1-to-1 ratio) for 8 weeks. At baseline, Week 8 (post treatment), and Week 20 (follow-up), investigators will assess daily eating patterns for one week, followed by collection of fasting lipids, body weight and vital signs. At Week 4 (i.e., mid-treatment), the investigators will assess self-reported outcomes only. Participants assigned to the wait list condition will have the option of receiving the TRE intervention after 20 weeks.

Medication Adherence in Severe Mental Illness: a Promotion Program

People living with serious mental illnesses such as schizophrenia and bipolar disorder often need long-term medication to stay well. However, many patients have difficulty taking medication regularly, which can increase the risk of relapse, hospitalization, and poorer quality of life. Traditionally, treatment adherence has been measured using self-report questionnaires, which may be influenced by memory or social desirability bias. With the recent expansion of electronic prescription systems in Spain, it is now possible to objectively verify whether patients collect their medications from the pharmacy. This provides a new opportunity to better understand and support treatment adherence. The ADHERA study will evaluate how well digital self-report questionnaires reflect real medication use compared with electronic dispensing records. We will also explore patient characteristics that may be associated with difficulties in medication adherence. Finally, we will test a new online psychoeducational program-including sessions led by mental health professionals and supported by peer-experience contributors-to determine whether it can help improve adherence. Participants with schizophrenia or bipolar disorder who are registered in the hospital's digital patient portal and have active antipsychotic prescriptions will be invited to complete brief adherence questionnaires online. Individuals with signs of reduced adherence will then be invited to take part in a telehealth intervention consisting of ten group sessions, where they will receive information, support, and practical strategies to maintain their treatment plan. Medication adherence will be reassessed after six months. If successful, this study may help improve how treatment adherence is measured in clinical practice, guide targeted interventions for individuals at higher risk of non-adherence, and provide evidence for scalable telehealth programs that can be easily implemented in other regions and medical conditions

PROgram To Enhance Cardiovascular Risk Trough an Intervention of Nutrition in Bipolar Disorder

Individuals with Bipolar Disorder (BD) have twice the risk of being affected by metabolic comorbidities and a 1.8-fold increased risk of mortality from cardiovascular diseases when compared to the general population. These factors are fundamental in the 14-year reduction in the life expectancy of people with TB reported in recent meta-analyses. This occurs mainly due to the increased inflammation associated with the disease, the adverse effects of pharmacological treatments and unhealthy lifestyle habits that are more common in people diagnosed with BD. Nutrition has been studied as an adjunctive treatment in other psychiatric disorders, but there is a lack of studies about the role of nutrition in TB. Considering that diet can impact metabolic health, this randomized controlled study aims to evaluate the effect of a nutritional intervention on cardiovascular risk in patients with TB. The intervention is based on the dietary pattern recommended in the Dietary Guidelines for the Brazilian Population and will be applied by a registered dietitian. According to the literature, the sample size will be 72 individuals with TB (36 in the control group with usual treatment + 36 in the intervention group added to the usual treatment). The intervention will be carried out in 7 individual sessions and 8 group sessions with specific themes. The primary aim of this protocol will be an intervention to contribute to cardiovascular health - verified by serum markers, anthropometric measurements and the Framingham Cardiovascular Risk Score (algorithm used to estimate an individual's 10-year cardiovascular risk). The secondary stages will be the adherence of the intervention and the impact on the quality of life of the participants. The possible positive results of this nutritional intervention can open new clinical perspectives. Meaning that might show that better food choices can protect the cardiovascular health of individuals with TB, leading to a reduction in morbidity and mortality associated with the disease.

Psychobiological Markers to Improve Diagnosis and to Predict Affective Episodes in Bipolar Disorder

This trial has two studies. In study 1, the investigators will explore the relationships between three psychobiological factors (sleep patterns, motor activity, and decision-making ability). The investigators aim to investigate how these factors interact in BD patients. This understanding will facilitate the distinction of BD patients from patients with recurrent depressive disorder (MDD) and healthy controls. In study 2, the investigators will continue following patients with bipolar disorder and use the interplay between the three psychobiological factors to develop early markers of full-blown affective episodes.

TMS for Improving Cognitive Function in Bipolar Disorder

Bipolar disorder is a highly disabling psychiatric illness, and cognitive impairment is common in patients with bipolar depression as well as during remission, contributing substantially to functional disability and poorer prognosis. Currently, effective interventions specifically targeting cognitive deficits remain limited, highlighting the need for novel treatment strategies. Transcranial magnetic stimulation, a noninvasive neuromodulation technique, has shown potential benefits for depressive symptoms and cognitive functioning. Based on structural and functional neuroimaging evidence, this study proposes an individualized intermittent theta burst stimulation (iTBS) protocol targeting the primary visual cortex (V1) and its functional pathway to the hippocampus, combined with online cognitive training. This randomized, double-blind, parallel-group, sham-controlled trial will enroll 88 patients with bipolar disorder in remission phase and allocate them to active or sham stimulation. The intervention will be delivered over 5 days, with follow-up assessments through 6 weeks. The primary outcome is change in cognitive performance as measured by the Cambridge Neuropsychological Test Automated Battery (CANTAB). Secondary outcomes include changes in clinical symptom ratings, magnetic resonance imaging (MRI) biomarkers, and the incidence of adverse events. This study aims to evaluate the efficacy and safety of this targeted intervention and to provide evidence for precision treatment approaches to cognitive impairment in bipolar disorder.

Epigenetic Enhancement of Cognitive Training in Aging Mood Disorder Populations

The aim of this clinical trial is to investigate the effects of a three-week virtual reality-based cognitive remediation training (VR-CRT) programme in combination with daily intake of a histone deacetylase inhibitor (HDACi) sodium butyrate on cognition in symptomatically stable patients with mood disorders (depression or bipolar disorder). The investigators hypothesize that the VR-based cognitive remediation training (VR-CRT) combined with HDACi butyrate vs. a VR-based control treatment combined with placebo will improve global cognition (primary outcome measure) over three weeks. Secondly, the investigators hypothesize that VR-CRT with placebo will improve cognition relative to the VR control treatment with placebo, although to a lesser extent than VR-CRT with HDACi butyrate. Thirdly, the investigators hypothesize that the HDACi butyrate with VR control treatment will not produce cognitive improvements relative to placebo with VR control treatment. Finally, the investigators hypothesize that the combined treatment (VR-CRT + HDACi butyrate) will enhance neuroplasticity (exploratory outcome) vs. VR control with placebo, as indicated by increase in hippocampal volume and/or memory-related activity shown with structural and functional MRI.

Adaptation and Validation of the Hypomanic Personality Scale (HPS-6) to Romanian

The HPS-6 (Hypomanic Personality Scale, 6 item version) could prove to be a valuable candidate for screening measures of high risk individuals. In the following study, we aim to validate and adapt the HPS-6 for the Romanian population.

Multimodal Intervention to Support Hospital-to-Community Transition in Bipolar Disorder

People with bipolar disorder (BD) are at high risk of relapse following hospital discharge, partly due to a lack of BD-specific expertise and resources within community services required for comprehensive treatment. Although clinical guidelines recommend combining medication and psychosocial support, and research shows that early intervention is associated with improved outcomes, no structured care programs currently exist for individuals in the early stages of BD, contributing to chronic illness progression and preventable hospitalizations. This open-label pilot trial will assess the feasibility, acceptability, and preliminary effectiveness of a structured care pathway to support the transition from hospital to community care. The intervention includes group-based psychoeducation, individual peer support, and personalized support for community healthcare providers to improve illness insight, treatment adherence, and symptom management.

Conceptualizing Borderline Personality Disorder as a Relationship Use Disorder

This study aims to explore a novel conceptualization of Borderline Personality Disorder (BPD) as a "Relationship Use Disorder." The research proposes that BPD shares key features with behavioral addictions, specifically addiction to interpersonal relationships. The study builds upon previous findings suggesting that individuals with BPD experience intense emotional dysregulation, including negative self-perception, shame, and a compulsive need for external validation. This addiction to relationships, much like substance use disorders, is thought to contribute significantly to the difficulties faced by these individuals, including interpersonal conflicts, self-destructive behaviors, and emotional instability. The study seeks to demonstrate that the relational difficulties central to BPD meet the diagnostic criteria for addiction as defined by the DSM-5. It will also explore how these relational struggles are mediated by dysfunctional self-perception and whether they are linked to behaviors such as compulsive sexual behaviors (CSBD) or suicidal tendencies. Additionally, the research will investigate the relationship between addiction to relationships and neurobiological factors, including endorphin levels, in individuals with BPD compared to those with bipolar disorder and healthy controls. The hypothesis is that individuals with BPD will exhibit higher levels of relationship addiction, with this addiction being tied to their perception of self-worth and emotional experiences in relationships. This innovative approach aims to refine the understanding of BPD, reduce stigma, and improve treatment strategies by providing scientific evidence supporting the conceptualization of BPD as a "Relationship Use Disorder."

Effects of Schizophrenia and Bipolar Disorder on Exercise Capacity, Pulmonary Function, and Quality of Life

This observational study aims to evaluate exercise capacity, pulmonary function, respiratory muscle strength, and quality of life in individuals diagnosed with schizophrenia and bipolar disorder. These psychiatric conditions are associated with sedentary lifestyles, metabolic side effects of psychotropic medications, and increased comorbidity risks, all of which may negatively impact physical fitness and respiratory health. By assessing cardiorespiratory endurance, pulmonary parameters (FVC, FEV₁), and respiratory muscle strength in this population, the study seeks to identify physiological limitations and contribute to the development of more effective rehabilitation strategies. The findings may support multidisciplinary approaches to improving physical health and overall quality of life in individuals with severe mental illness.

Feasibility of eLi12

eLi12 represents a new method to estimate the serum-lithium (Se-Li) concentration at 12 hours after the most recent lithium dose. eLi12 is a mathematical equation that presents the clinician with an estimated 12-hour Se-Li level when the lithium blood test is not taken 12 hours after the most recent lithium dose, but e.g., after 8 or 16 hours. The eLi12 equation is based on a development study and supported by two independent proof-of-concept studies. In these studies, eLi12 estimated a Se-Li concentration that was significantly closer to the 12-hour Se-Li level compared to the actual measured Se-Li in all scenarios between 3 hours and 24 hours after the most recent lithium dose. Before eLi12 can be implemented into a clinical setting, it needs to be tested whether lithium-treated patients actually can register the time for the last lithium intake (prerequisite for eLi12) and if eLi12 can provide improvements for everyday clinical work. The objective of this study is to test 1) whether lithium-treated patients can register the time of the most recent lithium intake at the time of their lithium blood test (which is a necessary data point for the eLi12 equation), 2) the difference between eLi12 and Se-Li, 3) if eLi12 will have less variation compared to the actual measured Se-Li concentrations, 4) patient satisfaction with the eLi12 solution and self-reported symptoms, and 5) clinician satisfaction with the eLi12 solution.

Anticipating Depressive and Manic Episodes in Bipolar Disorders Using Vocal Biomarkers

Bipolar disorder (BD) is a chronic, cyclical mental illness affecting over 1% of the global population. It is characterized by alternating episodes of elevated mood and energy (mania or hypomania) and episodes of decreased mood and energy (depression). Manic episodes involve hyperactivity, decreased need for sleep, grandiosity, accelerated speech, and sometimes psychotic symptoms such as hallucinations or delusions. Depressive episodes, in contrast, are characterized by sadness, low energy, social withdrawal, sleep and appetite disturbances, and low self-esteem. Bipolar patients are at very high risk of suicide, with rates up to 20 times higher than in the general population; nearly half will attempt suicide during their lifetime, and 15-20% of these attempts are fatal. BD is associated with a substantial decrease in quality of life, often greater than that seen in other mood or anxiety disorders. This reduction is primarily driven by depressive symptoms, including residual ones that may persist during remission periods. The frequent comorbidity with anxiety disorders further exacerbates the burden of the illness. Recently, research has turned toward the concept of the digital phenotype to identify early markers of relapse using passive and continuous monitoring. Among potential digital biomarkers, voice has shown particular promise. Automated speech analysis, combined with machine learning algorithms, has demonstrated effectiveness in detecting psychiatric symptoms and differentiating mood states. In BD, vocal and linguistic patterns vary with mood fluctuations, suggesting that voice could serve as a sensitive indicator of relapse risk. The main hypothesis of the present study is that automated analysis of speech and lifestyle data can help develop a predictive model capable of identifying early signs of relapse, whether manic, depressive, or mixed, or transitions to high-risk states in individuals with bipolar disorder.

Characterization of High-Level Cognitive Impairments in Patients With Neuropsychiatric Disorders

Neuropsychiatric disorders are extremely common, severe, and disabling conditions. In the field of psychiatry, they notably include schizophrenia, mood disorders (depressive and bipolar disorders), autism spectrum or neurodevelopmental disorders, obsessive-compulsive disorder, eating disorders, and personality disorders. In the field of neurology, one can cite neurodegenerative diseases (such as Alzheimer's disease, but also frontotemporal dementia or Parkinson's disease, which often represent frequent and challenging differential diagnoses of psychiatric disorders), focal neurological lesions (notably strokes and tumors), or epilepsy. Cognitive impairments are present in nearly all neuropsychiatric disorders and contribute significantly to disability. While impairments in working memory and attention, executive functions, and social cognition have been relatively well studied, other cognitive domains remain largely unexplored in these populations. This is particularly the case for various aspects of motivation, metacognition, conscious access, or causal (Bayesian) inference. Although these domains likely play an important role in prognosis, no consensus currently exists regarding the methods for evaluating these functions. The main objective of this study is to define a multidimensional, transdiagnostic atlas of high-level cognitive impairments-both specific and shared-across severe psychiatric disorders (notably schizophrenia, depressive disorder, bipolar disorder, autism spectrum or neurodevelopmental disorders, and obsessive-compulsive disorder) and neurological disorders (notably neurodegenerative diseases, focal neurological lesions, and epilepsy), by comparing them to healthy volunteers. The investigators also aim to investigate the progression of cognitive impairments over time, across different phases of illness (symptom stabilization or exacerbation) or therapeutic intervention, through longitudinal follow-up of patients being monitored within the recruiting center. Finally, in a more exploratory manner, the investigators aim to investigate the neural correlates of the identified cognitive impairments.

Understanding Mechanisms of Synaptic Degeneration Underlying Clinical Symptoms in Patients With MDs and NDs.

Clinical Study A. Retrospective Neuropathological Study of Synapse dysfunction. This is a cross-sectional study of patients retrospectively collected from existing postmortem collections and from existing collections of iPSC-derived neurons. Postmortem tissue and iPSC-derived neurons from age and sex-matched unaffected volunteers without a MD or ND diagnosis are used as controls.

Multimodal Phenotyping in Adolescent Inpatient Depression: An Observational Study

This cohort study involves the dynamic collection of clinical information from adolescent patients with major depressive episodes (including both major depressive disorder and bipolar disorder), encompassing serum parameters, physiological-behavioral signals, neuroimaging data, and neuropsychological scales. The study aims to summarize the comprehensive clinical characteristics of this population, identify new risk factors, and establish multivariate predictive models for treatment response, cognitive and emotional impairments. Furthermore, this research will thoroughly investigate the underlying neural mechanisms linking clinical manifestations and neuroimaging features in major depressive episodes.

The PEDAL Intervention - Reducing Affective Lability in Bipolar Disorder

PEDAL is a group-based intervention for patients with bipolar disorder that builds on the traditional group psychoeducational program (GPP) by adding digital tools and specific strategies to help manage rapid fluctuations between affective states, known as affective lability. The program's goal is to help patients learn and develop new ways to better manage their condition, with particular attention to affective lability and other difficulties with affect regulation- challenges which are not typically addressed in current treatments. The PEDAL trial will run at five clinical sites around Oslo and Vestre Viken, aiming to recruit 120 participants with bipolar disorder. The program combines existing group sessions from GPP with new components: additional group sessions focusing on strategies for improving affect regulation such as mindfulness and distress tolerance, an online platform with all course materials including instructional videos and other resources, and an app-based mood diary. This framework maintains the benefits of regular group meetings while adding digital support tools to make the intervention more personalized and accessible. The main aim of PEDAL is to see if the new program reduces affective lability more effectively than GPP (treatment-as-usual; TAU), and both intervention groups will be compared on the level of affective lability before and after the intervention. Several secondary outcomes like mood symptoms, suicidal thoughts, perceived stress, and quality of life will also be assessed. In terms of study design, all study sites will run the PEDAL and TAU groups in parallel, and participants will be randomly assigned to either PEDAL or TAU. To qualify for the study, participants must be aged 18-65, diagnosed with bipolar disorder, able to participate in a group intervention, capable of providing informed consent, and have a smartphone or computer. People who have previously completed group psychoeducation, who are unable to complete the study period due to pregnancy or other factors, or those who cannot use the required technology are excluded. In summary, PEDAL is a novel study that modernizes the existing group psychoeducational program for bipolar disorder by targeting affective lability through skills training and digital tools, while also evaluating its reception and effects in a controlled clinical trial.

Validation of a Composite Medical Device Using a Blood Biomarker-based Algorithm and MDQ for the Diagnosis of Bipolar Disorder

The goal of this interventional clinical trial is to assess the diagnostic performance of a composite diagnostic medical devise based on blood-based in vitro diagnostic device and Mood Disorder Questionnaire (MDQ) in identifying bipolar disorder among adult patients presenting with a current major depressive episode in primary care. The study will compare the results of the medical device diagnostic test to those of standardized psychiatric clinical evaluation, to evaluate its sensitivity, specificity, and overall clinical utility. The main research questions are : * Can the investigational medical device accurately distinguish bipolar disorder from unipolar depression ? * How does its diagnostic accuracy compare with validated psychiatric questionnaires commonly used in clinical practice ? Participants will : * Provide a blood sample for biomarker analysis using the investigational diagnostic device. * Complete a few validated psychiatric assessment tools (e.g., MDQ, MINI). * Share sociodemographic and clinical data relevant to psychiatric evaluation.

Creating a Global Research Database That Connects Genetic Information and Long-term Health Data to Improve Personalized Treatment for People With Serious Mental Illness

This observational study aims to provide new insights into the nature and classification of severe mental illness and dementias that in time should help improve diagnostic practise, and enable the development of new and improved treatments. The investigators will achieve aims by gathering information and biological samples from over 50,000 research participants and then linking this information with participants' electronic health records, genetic and other potential markers of mental illnesses (called biomarkers, derived from biological samples). The investigators will use this resource to analyse how potential risk factors - genetic, other biological and non-biological (related to the participants' life circumstances) - influence participants' experiences, symptoms, and outcomes (both mental and physical health). The investigators will also use advanced analysis to assess whether there may be better ways of grouping together and understanding the experiences of those with severe mental illnesses and dementias. Given the value and importance of this resource for advancing mental health research, the investigators will also make the data available to other researchers to pursue these broad research aims.

Real-world Lithium Intake

The aim of the present study is to study compliance with lithium therapy and patterns of lithium intake among a representative group of patients with bipolar disorder in a real-world clinical setting. This will be studied via a pill box that registers the daily time when the participant took the lithium tablet out of the pill box, representing a proxy for the actual lithium intake. Participants will receive a weekly phone call asking for several aspects of lithium intake.

Pain, Sleep Quality, Eating Habits and Physical Activity Level in Patients With Bipolar Disorder

Bipolar disorder (BD) is a complex condition characterized by recurrence of mania, hypomania, and depression. It is characterized by changes in daily life activities, sleep status, focus problems, and cognitive fluctuations. The mortality rate due to suicide and cardiovascular diseases increases in individuals with BD. The DSM-5TR defines BD as Bipolar I Disorder (BD-1) with one or more manic episodes, Bipolar II Disorder (BD-II) with at least one severe depressive episode accompanied by at least one hypomanic episode, Cyclothymia disorder, substance-induced bipolar disorder, bipolar or related disorder related to another medical condition, other defined bipolar and related disorder, and undefined bipolar and related disorder. The lifetime prevalence of BD varies between 0.6% and 1.0% for Type I and 0.4% and 1.1% for Type II. Symptoms usually start between 14-21 years of age. Depressive episodes and lifelong single marital status are more common in females, while substance abuse is more common in males. Depression attacks are longer than manias, but the duration of attacks does not differ between types. The mean duration of depressive and manic periods is 5.2 months and 3.5 months, respectively. Pain is observed in 28.9% of patients with a diagnosis of GI, which decreases the quality of life and is a significant concern in psychological disorders.

Digital Phenotypes for Predicting Depression

This longitudinal study aims to identify and validate digital phenotypes that can predict recurrence of major depressive episodes using passively collected, real-time sensing data from smartphones and wearable devices. Over a 12-month period, 540 participants-including patients with mood disorders and healthy or high-risk controls-will complete five clinical assessments at 3-month intervals, wear a Fitbit device daily, and log daily mood ratings via a mobile app. The study includes the development of AI-based predictive models and the construction of an anonymized wearable big-data repository for mood disorders.

Mental Health, Intellectual and Neurodevelopmental Disorder Detection With Artificial Intelligence Models

This study investigates whether AI-driven analysis of speech can accurately predict clinical diagnoses and assess risk for various mental or behavioral health conditions, including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, bipolar disorder, generalized anxiety disorder, major depressive disorder, obsessive compulsive disorder (OCD), post-traumatic stress disorder (PTSD), and schizophrenia. We aim to develop tools that can support clinicians in making more accurate and efficient diagnoses.