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Prabha Sunderajan

Publications and source records attributed to Prabha Sunderajan.

2 recordsLinked to original sources

TREAD: TReatment with Exercise Augmentation for Depression: study rationale and design.

BACKGROUND: Despite recent advancements in the pharmacological treatment of major depressive disorder (MDD), over half of patients who receive treatment with antidepressant medication do not achieve full remission of symptoms. There is evidence that exercise can reduce depressive symptomatology when used as a treatment for MDD. However, no randomized controlled trials have evaluated exercise as an augmentation strategy for patients with carefully diagnosed MDD who remain symptomatic following an adequate acute phase trial of antidepressant therapy. PURPOSE: TReatment with Exercise Augmentation for Depression (TREAD) is an NIMH-funded, randomized, controlled trial designed to assess the relative efficacy of two doses of aerobic exercise to augment selective serotonin reuptake inhibitor (SSRI) treatment of MDD. METHODS: The TREAD study includes 12 weeks of acute phase treatment with a 12-week post-treatment follow-up. In addition to looking at change in depressive symptoms as a primary outcome, it also includes comprehensive assessment of psychosocial function and treatment adherence. RESULTS: This paper reviews the rationale and design of TREAD and illustrates how we address several key issues in contemporary patient-oriented research on MDD: 1) the use of augmentation strategies in the treatment of depressive disorders in general, 2) the use of non-pharmacological strategies in the treatment of depressive disorders, 3) the considerations of designing a well-controlled trial using two active treatment groups, and 4) the implementation of an adherence program for the use of exercise as a treatment strategy. CONCLUSIONS: The TREAD study is uniquely designed to overcome sources of potential bias and threats to internal and external validity that have limited prior research on the mental health effects of exercise. The study is facilitated by the development of a multidisciplinary research team that includes experts in both depression treatment and exercise physiology, as well as other related fields.

Adolescent↗

A computerized clinical decision support system as a means of implementing depression guidelines.

The authors describe the history and current use of computerized systems for implementing treatment guidelines in general medicine as well as the development, testing, and early use of a computerized decision support system for depression treatment among "real-world" clinical settings in Texas. In 1999 health care experts from Europe and the United States met to confront the well-documented challenges of implementing treatment guidelines and to identify strategies for improvement. They suggested the integration of guidelines into computer systems that is incorporated into clinical workflow. Several studies have demonstrated improvements in physicians' adherence to guidelines when such guidelines are provided in a computerized format. Although computerized decision support systems are being used in many areas of medicine and have demonstrated improved patient outcomes, their use in psychiatric illness is limited. The authors designed and developed a computerized decision support system for the treatment of major depressive disorder by using evidence-based guidelines, transferring the knowledge gained from the Texas Medication Algorithm Project (TMAP). This computerized decision support system (CompTMAP) provides support in diagnosis, treatment, follow-up, and preventive care and can be incorporated into the clinical setting. CompTMAP has gone through extensive testing to ensure accuracy and reliability. Physician surveys have indicated a positive response to CompTMAP, although the sample was insufficient for statistical testing. CompTMAP is part of a new era of comprehensive computerized decision support systems that take advantage of advances in automation and provide more complete clinical support to physicians in clinical practice.

Algorithms↗