Active clinical trials for "Depression"

The overall goal of this proposal is to study quantitative electroencephalography (QEEG ) as a method for the detection of antidepressant treatment response. The investigators have developed a QEEG algorithm called "cordance" that appears to provide much the same information about brain function as PET or SPECT scanning, and has shown patterns of brain function that appear to be indicative of depression. Of greatest interest is that these patterns appear to normalize in response to antidepressant treatment.

Shared decision making (SDM) has been advocated as an appropriate approach for physician patient communication. Positive effects of SDM are e.g higher patient satisfaction, greater treatment adherence, lower decisional conflict and better clinical outcomes. The Section of Clinical Epidemiology and Health Services Research at the University Medical Center in Freiburg (Germany) is developing and evaluating a web-based interactive decision aid ("patient dialogue") to support shared decision making in cooperation with the Techniker Krankenkasse, a large German health insurance company. Both development and evaluation are conducted along the International Patient Decision Aid Standards (IPDAS). The decision aid contains information on acute low back pain and depression and addresses insurance members who are facing a treatment decision in one of the indications. It aims at the development of patient competencies for participating in decision making, the support of constructive health behavior and patients' acceptance of evidence based treatment options. In an RCT the decision aid will be compared to a regular patient information on a sample of N=500 patients in each group. Data collection will take place at three points of time: before and after use of the decision aid as well as 3 months later.

The study will randomize 54 primary care practices to two intervention and a comparison groups. Both interventions will involve an on-site Improvement Facilitator who will assist the practice in forming an Improvement Team, using rapid-cycle tests of change, and implementing chronic care office systems for type 2 diabetes and depression. One intervention is based on complexity science and the other is a traditional QI intervention.

Across the country, Community Health Centers are participating in the Health Disparities Collaboratives sponsored by the Health Services Resources and Services Administration (HRSA). The Health Disparities Collaboratives integrate three complementary conceptual frameworks: 1) the Institute for Healthcare Improvement's (IHI) Breakthrough Series Model; 2) the Improvement Model (i.e., Plan-Do-Study-Act cycles); and 3) Wagner's Chronic Care Model. The Chronic Care model uses patient self-management, delivery system re-design, decision support, and clinical information systems to maximize the effectiveness of interactions between prepared proactive care teams and informed activated patients with chronic illnesses such as diabetes, asthma, and depression. The Chronic Care model for depression, also known as Collaborative Care, involves primary care providers working with a depression care team comprising non-physicians (e.g., nurses, pharmacists) and mental health specialists (e.g., psychiatrists). Practice-based collaborative care involves primary care providers working with an on-site depression care team. In contrast, telemedicine-based collaborative care involves primary care providers working with an off-site depression care team using telemedicine technologies. The purpose of this research project is to compare the effectiveness and cost effectiveness of practice-based and telemedicine-based collaborative care in Community Health Centers (without on-site mental health specialists) implementing the Health Disparities Collaborative for depression.

This project aims to identify brain and behavioral characteristics of individuals experiencing symptoms of depression that will predict the effectiveness of Behavioral Activation Therapy. Brain imaging aspects of the study will use functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Behavioral assessments will include self-report questionnaires, computer-based and observational tasks, and interviews. Assessments will focus on how individuals process positive information (such as reward) and negative information (such as distressing images), as well as how people make decisions. These assessments will be conducted across 2-3 in-person sessions prior to beginning the treatment, and will be repeated across 2-3 in-person sessions after completing treatment. A blood draw will also be conducted pre- and post- treatment. Behavior Activation therapy will consist of 10, 90-minute weekly therapy sessions conducted in small groups.

The purpose of this study is to determine whether Cymbalta (duloxetine) is effective to improve cognition in individuals with Mild Cognitive Impairment.

The overall objective of this project is to demonstrate that a low cost, cell phone-delivered intervention is a promising, feasible and acceptable way to improve the prevention and treatment outcomes of women in India who are affected by HIV and inter-related mental health and psychosocial risk factors.

This project will be the first to evaluate the Moving Forward app in VA. Identifying an effective treatment for anxiety and depression in primary care is imperative within Veterans Health Administration as they are both common, chronic, and debilitating conditions associated with a number of personal and health-related costs. In close partnership with app developers at Mental Health Services, a major contribution of this research is the actionable feedback on the acceptability, feasibility and effectiveness of augmenting traditional Problem Solving Therapy with the Moving Forward app for future app development. If effectiveness can be established, Moving Forward has the potential for integration into the larger continuum of care for depression and anxiety in Primary Care-Mental Health Integration (e.g., care management, co-located collaborative care). Lastly, this pilot project will provide preliminary data for future research on SmartPhone technology. Veteran feedback on treatment components, ease of executing the study successfully and preliminary effect size calculations, will inform the design of the larger project.

This study is to compare the pharmacokinetics of FK949E low dose tablets and FK949E high dose tablets in non-elderly patients with major depressive disorder. The safety of FK949E in the population was also evaluated.

CPIC is a community initiative and research study funded by the NIH. CPIC was developed and is being run by community and academic partners in Los Angeles underserved communities of color. CPIC compares two ways of supporting diverse health and social programs in under-resourced communities to improve their services to depressed clients. One approach is time-limited expert technical assistance coupled with culturally-competent community outreach to individual programs, on how to use quality improvement toolkits for depression that have already been proven to be effective or helpful in primary care settings, but adapted for this study for use in diverse community-based programs in underserved communities. The other approach brings different types of agencies and members in a community together in a 4 to 6-month planning process, to fit the same depression quality improvement programs to the needs and strengths of the community and to develop a network of programs serving the community to support clients with depression together. The study is designed to determine the added value of community engagement and planning over and above what might be offered through a community-oriented, disease management company. Both intervention models are based on the same quality improvement toolkits that support team leadership, care management, Cognitive Behavioral Therapy, medication management, and patient education and activation. Investigators hypothesized that the community engagement approach would increase agency and clinician participation in evidence-based trainings and improve client mental health-related quality of life. In addition, during the design phase, community participants prioritized adding as outcomes indicators of social determinants of mental health, including physical functioning, risk factors for homelessness and employment. Investigators hypothesized by activating community agencies that can address health and social services needs to engage depressed clients, these outcomes would also be improved more in the collaboration condition. Investigators also hypothesized that the collaboration approach would increase use of services.