Complementary and alternative medicine (CAM) use is widespread among cancer patients. Information on safety and efficacy of CAM therapies is needed for both patients and healthcare providers. Well-designed randomized clinical trials of CAM therapy interventions can inform both clinical research and practice.
The aim of this study was to review important issues that affect the design of randomized clinical trials for CAM interventions.
Using the methods component of the Consolidated Standards for Reporting Trials as a guiding framework and a National Cancer Institute-funded reflexology study as an exemplar, methodological issues related to participants, intervention, objectives, outcomes, sample size, randomization, blinding, and statistical methods were reviewed.
Trials of CAM interventions designed and implemented according to appropriate methodological standards will facilitate the needed scientific rigor in CAM research. Interventions in CAM can be tested using proposed methodology, and the results of testing will inform nursing practice in providing safe and effective supportive care and in improving the well-being of patients.
Alla Sikorskii, PhD, is Assistant Professor, Department of Statistics and Probability, College of Natural Science; and Gwen Wyatt, RN, PhD, is Professor, College of Nursing, Michigan State University, East Lansing.
David Victorson, PhD, is Research Assistant Professor, Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Gwen Faulkner, BA, is Research Assistant, Center on Outcomes, Research and Education, NorthShore University HealthSystem, Evanston, Illinois.
Mohammad Hossein Rahbar, PhD, is Professor of Epidemiology and Biostatistics; and is Director, Biostatistics/Epidemiology/Research Design (BERD) Core, Center for Clinical and Translational Sciences, The University of Texas Health Science Center at Houston.
Editor's Note Materials documenting the review process for this article are posted at http://www.nursing-research-editor.com
Accepted for publication July 13, 2009.
This research was supported by grant R01 CA104883 from the National Cancer Institute. The contents represent original work and have not been published elsewhere. No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit on the authors or on any organization with which the authors are associated.
Corresponding author: Alla Sikorskii, PhD, Department of Statistics and Probability, A423 Wells Hall, Michigan State University, East Lansing, MI 48824 (e-mail: firstname.lastname@example.org).