View clinical trials related to Depressive Disorder, Major.
Filter by:To provide expanded access of REL-1017 to patients with MDD who do not have access to other effective therapy and are not eligible for other clinical trials with REL-1017
The purpose of this randomized controlled trial is to evaluate whether the InMotion intervention, delivered via telehealth (using a HIPAA-compliant video platform or phone), which uses evidence-based behavioral and motivational counseling to increase daily physical activity, is an effective treatment for Major Depressive Disorder (MDD) for people who are at least one year out from sustaining a traumatic brain injury (TBI). The first aim is to compare the efficacy of the InMotion intervention to the waitlist control (WLC) condition on measures of depression severity and associated conditions in under-active adults with TBI and MDD. For the second aim the investigators plan to identify possible moderators of exercise treatment effects. The third aim will examine possible mediators of treatment outcome. In addition, the weekly dose of exercise, the extent to which exercise generates positive affect, and engagement in enjoyable or meaningful aspects of life will be explored.
This study will examine the efficacy of digital CBT versus waitlist in improving symptoms for adults with Major Depressive Disorder.
The investigators propose a randomized 3-arm double-blinded parallel experimental trial (20 sessions over 4 weeks) in 75 patients with TRD. The three arms include (1) the combination of a fully Individualized form of intermittent Theta Burst Stimulation (iTBS) (using BOTH the frequency and electric field (E-field) targeting approaches) (Ind-iTBS)), (2) iTBS individualized using E-field targeting only (targeted-iTBS) and (3) Standard iTBS treatment (i.e., typical iTBS localized to the dorsolateral prefrontal cortex (DLPFC) using the Beam F3 method). Electroencephalography (EEG) data will be collected at rest and during a working memory task, at baseline, and at the end of treatment along with clinical assessments of depression severity. The target engagement dependent variable of interest in these three arms will be fronto-parietal theta connectivity measured through resting-state EEG. The investigators hypothesize that stimulation with Ind-iTBS will lead to greater changes in fronto-parietal theta connectivity than that produced with targeted-TBS and standard iTBS. Aim: To evaluate the effects of two individualized forms of iTBS (i.e., using BOTH the frequency and E-field individualization; Ind-iTBS) compared to iTBS individualized for E-field targeting only (targeted-iTBS) and standard iTBS on fronto-parietal theta connectivity. Hypotheses: (1) Ind-iTBS will lead to greater changes in fronto-parietal theta connectivity compared to both targeted-iTBS and standard iTBS. (2) Ind-iTBS will also lead to a greater reduction in depressive symptoms (as defined by the mean reduction in Montgomery Åsberg Depression Rating Scale Scores (MADRS)) compared to both targeted-iTBS and standard iTBS.
The purpose of the current study is to perform a unified, homogeneous data collection protocol that includes a large cohort of patients undergoing different treatment options for Major Depressive Disorder (MDD) as an avenue for investigating optimal biomarkers for depression treatments on an individual patient level.
This study investigates the effects of a novel intervention approach, intentionally sequencing aerobic exercise immediately prior to therapy sessions (i.e., cognitive behavioral therapy [CBT]) to determine its effects on both specific and common factors underlying the antidepressant effect of CBT (i.e., mechanisms of CBT). To assess the utility of this treatment augmentation, investigators plan to conduct a randomized controlled trial involving 40 adults with Major Depressive Disorder who will watch a nature documentary while either resting quietly (termed 'CalmCBT') or exercising at a moderate intensity ('ActiveCBT') immediately prior to 8 weekly sessions of CBT. It is hypothesized that target CBT mechanisms of antidepressant action (i.e., self-reported working alliance and behavioral activation) will be more effectively engaged by ActiveCBT vs. CalmCBT.
Transcranial magnetic stimulation (TMS) is an effective treatment for depression, but clinical outcome is suboptimal, partially because investigators are missing biologically-grounded brain markers which show that TMS is modifying activity at the intended target in the brain. The goal of this proposal is to characterize the key markers of the brain's response to repeated doses of TMS with high resolution using invasive brain recordings in humans, and relate these brain markers to noninvasive recordings. These markers will improve the understanding of TMS and can be used to optimize and enhance clinical efficacy for depression and other psychiatric disorders.
This study aims to better adapt cognitive behavioral therapy for insomnia (CBTi) for people with comorbid depression by using objective sleep measures to tailor the behavioral interventions components of CBTi. Using ambulatory monitors, we also aim to investigate changes in brain activity and heart rate throughout the intervention. In this parallel-group randomized clinical trial, participants undergo one week of baseline ambulatory monitoring after which they are randomly assigned to one of two intervention arms: 1) digitally delivered CBTi (eCBTi) based on standard subjective sleep measures (sleep diary), or 2) eCBTi based on objective sleep measures (EEG headband). The intervention spans over 5-weeks, followed by a week of ambulatory monitoring and follow-up measures one week and one month after the end of the intervention. The study also includes a post-intervention interview to gather feedback on participant experiences. The overall protocol includes online questionnaires and structured clinical interviews assessing sleep, insomnia, and mental health, as well as treatment-related measures before, during, and after the intervention. It is anticipated that eCBTi using objective sleep measures will lead to better treatment acceptability, satisfaction, and effectiveness, including greater improvements in symptoms of insomnia and depression. It is also anticipated that sleep EEG and heart rate profiles will improve along the course of eCBTi.
Major depressive disorder (MDD) is a mental disorder leading to a variety of emotional and physical problems affecting almost 300 million people worldwide. Long-term treatments for MDD, including medication and therapy, imposes a significant financial burden on society. Mobile-based screening interventions might be a promising approach for effectively reducing MDD symptoms. The investigators hypothesize that the mobile-based screening strategy evaluated in this proposal will substantially reduce the burden of MDD over time, increase participants' quality of life, and decrease MDD-related disparities
The worldwide prevalence of anxiety and depression increased massively during the pandemic, with a 25% rise in the number of patients suffering from psychological distress. Psychiatrists, and even more so general practitioners, need measurement tools that enable them to remotely monitor their patients' psychological state of health, and to be automatically alerted in the event of a break in behavior. In this study, the investigators propose to collect clinical data along with longitudinal measurement of patients' emotions. Emobot proposes to analyze the evolution of mood disorders over time by passively studying people's emotional behavior. The aim of EMOACQ-1 is to acquire knowledge and produce a quantitative link between emotional expression and mood disorders, ultimately facilitating the understanding and management of these disorders. Through this study, could be developed a technological solution to support healthcare professionals and patients in psychiatry, a field known as the "poor relation of medicine" and lacking in resources. Such a solution would enable better understanding, disorders remote & continuous monitoring and, ultimately, better treatment of these disorders. The investigators will process the data by carrying out a number of analyses, including descriptive, comparative and correlation studies of the data from the self-questionnaire results and the emotional signals captured by the devices. Finally, the aim will be to predict questionnaire scores from the emotional signals produced.