View clinical trials related to Depressive Disorder, Major.
Filter by:Major depression is the leading cause of disability in the United States and is a major contributor to suicide, a leading cause of premature death. The majority of individuals with depression do not receive adequate pharmacologic or psychotherapeutic treatment due to difficulty accessing services or stopping treatment due to side effects, non-response, or the stigma associated with attending mental health clinic visits. Mobile health information technology services, such as text messaging, have the potential to provide effective self-management support for depression to nearly every adult in the US with depression. Guided self-help via text messaging has been shown to be effective for improving a range of health behaviors as well as symptoms of depression. However, previously studied depression text messaging services have not utilized the breadth of psychotherapeutic techniques shown to be effective for depression nor have they attempted to tailor the psychotherapeutic content to the individual in order to improve acceptability and outcomes. Advanced artificial intelligence methods (e.g., reinforcement learning) offers the capability to weed out ineffective messages and to target messages to individuals in order to substantially improve program effectiveness. This pilot study is the first step in towards developing an artificially intelligent text message service for depression. The specific aims of the study are to: 1) demonstrate the feasibility of recruiting and enrolling participants from the general population of US adults and delivering a text-messaging intervention for depression, 2) determine whether there are differences in the perceived helpfulness of messages derived from different psychotherapeutic treatment modalities, and whether these differences are moderated by participant characteristics (e.g., age, gender, depression symptom severity), 3) determine whether messages derived from different psychotherapeutic treatment modalities or their perceived helpfulness are associated with changes in depression symptoms, and whether these relationships are moderated by participant characteristics.
The project aims to investigate markers of neural activity and connectivity, neurochemistry, hypothalamic-pituitary-adrenal (HPA) axis activity, inflammation and neuronal plasticity underlying treatment response and remission after ECT. These measures will be assessed in depressive patients prior, during and after ECT and also after 6 months. Furthermore, we will investigate a control group of depressive patients treated with antidepressants.
Major Depressive Disorder (MDD) is one of the most severe and frequently occurring brain disorders worldwide. It has been linked to serotonergic dysfunction, sexual dysfunction, vulnerability to stress and neuro-inflammation. However, at the same time the etiological understanding is limited. Most antidepressants act on the serotonin (5- HT) system, yet between 30-50 % of patients with MDD does not respond successfully to 5-HT acting drugs. Recent experimental models from our group suggest that cerebral 5-HT levels in vivo can be indexed through molecular brain imaging of the 5-HT 4 receptor (5-HT4R) with a novel Positron Emission Tomography (PET) ligand (11C-SB207145). Also, our human studies have confirmed that cerebral synaptic 5-HT is inversely related to 5-HT4R binding and this technique thus can be used to investigate the role of 5-HT tone in the brain in MDD with differential responses to standard antidepressant treatment. By using multimodal neuroimaging technology, we aim to determine the status of the 5-HT system prior to and after either successful or failed neuropharmacological intervention in a non-randomized longitudinal open clinical trial. 100 untreated patients with moderate to severe MDD will be included. Data collection from various neurobiological domains (i.e, 5-HT4R PET imaging, Magnetic Resonance Imaging (MRI), functional MRI (fMRI), electroencephalogram (EEG), psychometrics, neuropsychological tests, and peripheral biomarkers) will be conducted before, during and after 12 weeks of antidepressant treatment. The objective is to identify predictors of pharmacological antidepressant treatment response in depressed individuals before and after 8 weeks of antidepressant treatment.
A proof-of-concept study to determine the antidepressant potential of Dextromethorphan for treating depression associated with Major Depressive Disorder in inpatients.
The general objective of this study is to advance insight into non-pharmacological treatments for maturing women that impact psychological health and wellbeing of women adapting to menopause, a natural but often challenging developmental milestone.
Anhedonia (the lack of pleasure in normally pleasurable things) is a common symptom of major depressive disorder (MDD), and it may impact how patients with depression experience reward. Understanding how anhedonia is related to the experience of reward may help improve how depression is treated. Computer tasks can be used to measure how reward is experienced, and these measures might be able to predict things like who is likely to become depressed, or who will respond to antidepressant medication. Studying the relationship between anhedonia and reward in patients with depression might also tell us something about how to improve diagnosis and treatment of other psychiatric disorders.This is an open label controlled treatment study lasting 8 weeks. The brain scans will be used to find changes in brain areas that may be related to how people perform on the tasks. The investigators goal is to use this information to help us find a reliable predictor that can be used to guide MDD treatment.
Suicidal behavior (SB) is a major public health problem in France, with more than 10,000 suicides and 220,000 suicide attempts per year. According to the commonly accepted model for understanding suicidal behavior, individuals who carry a suicidal act when subjected to stress factors (environmental stress, depression, substance ...) are those which have a specific vulnerability. These vulnerabilities can be considered as clinical parameters (propensity to despair, aggressive and/or impulsive traits), neurobiological parameters (dysfunction of the serotonergic system, ...) and cognitive parameters (taking disadvantageous decision ...). Suicidal vulnerability is partly underpinned by genetic factors. The interest of current researches is to identify biomarkers that will improve the opportunities for early identification of subject with a risk for SB. Numerous scientific studies, including post-mortem studies of the brains of suicide completers, have established a link between dysregulation of the ribonucleic acids editing (RNA) of certain genes, the enzymatic activity of Adenosine deaminases acting on RNA (ADARS) responsible for this edition and suicidal behavior. A prospective study is needed to quantify and qualify in the blood of depressed patients (with or without a history of suicide) and healthy controls, the editing changes and the expression and alteration of the activity of ADARS.
The purpose of this study is to examine the feasibility, acceptability, and utility of pharmacogenomic (PGX) testing (specifically for the cytochrome P450 2D6 and 2C19 genes) prior to initiating treatment with an antidepressant (AD) among children and adolescents in the University of Florida Child Psychiatry clinics.
The overall aim of this study is to test the effect of academic detailing (i.e. provider-level educational intervention focused on evidence-based smoking cessation treatment for those with psychiatric illness) and community health worker (CHW) support on the provision and utilization of standard of care smoking cessation treatment to those with serious mental illness (SMI) and smoking cessation rates for adults with SMI who smoke.
The overarching goal of this research program is to elucidate causal and directional neural network- level abnormalities in depression, and how they are modulated by an individually-tailored, circuit-directed intervention. By using concurrent TMS and EEG, the investigators can overcome a major limitation of EEG - the inability to demonstrate causality. Here, we plan to recruit patients with medication-resistant depression undergoing rTMS treatment. At multiple time points, we will perform TMS-EEG to investigate the excitability and connectivity profiles of brain networks and how they are modulated during treatment. This study aims to provide objective brain network measures that can predict and track clinical response to TMS treatment. Findings from this study will be utilized to develop a novel, personalized treatment protocol based on individual brain networks.