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The case for practical clinical trials in psychiatry
Authors:March John S  Silva Susan G  Compton Scott  Shapiro Mark  Califf Robert  Krishnan Ranga
Institution:Department of Psychiatry and Behavioral Sciences, Duke Child and Family Study Center, 718 Rutherford St., Durham, NC 27705, USA. jsmarch@acpub.duke.edu
Abstract:OBJECTIVE: Clinical trials in psychiatry frequently fail to maximize clinical utility for practicing clinicians, or, stated differently, available evidence is not perceived by clinicians (and other decision makers) as sufficiently relevant to clinical practice, thereby diluting its impact. To attain maximum clinical relevance and acceptability, researchers must conduct clinical trials designed to meet the needs of clinicians and others who are making decisions about patients' care. The authors present the case for psychiatry's adoption of the practical clinical trials model, which is widely used in research in other areas of medicine. METHOD: The authors outline the characteristics and scope of practical clinical trials, give examples of practical clinical trials, and discuss the challenges of using the practical clinical trials model in psychiatry, including issues of funding. RESULTS: Practical clinical trials, which are intended to provide generalizable answers to important clinical questions without bias, are characterized by eight key features: a straightforward clinically relevant question, a representative sample of patients and practice settings, sufficient power to identify modest clinically relevant effects, randomization to protect against bias, clinical uncertainty regarding the outcome of treatment at the patient level, assessment and treatment protocols that enact best clinical practices, simple and clinically relevant outcomes, and limited subject and investigator burden. CONCLUSIONS: To implement the practical clinical trials model in psychiatry will require stable funding for network construction and maintenance plus methodological innovation in governance and trial selection, assessment, treatment, data management, site management, and data analytic procedures.
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