Public Health Randomized Controlled Trials
Christine Paul, Robert Sanson-Fisher, Mariko Carey
  • LAST REVIEWED: 05 May 2017
  • LAST MODIFIED: 31 August 2015
  • DOI: 10.1093/obo/9780199756797-0047


Randomized controlled trials (RCTs) have become the accepted approach, or “gold standard,” for producing robust evidence to guide decisions about the effectiveness of proposed public health interventions, programs, or practices. While other research designs are in common use, the “levels of evidence” concept clearly places RCTs as the peak or most preferred approach to the production of evidence. The historical roots of RCTs lie in recognition of the important information to be gained from having comparison or control groups. However, attempts to translate the clinical framework underlying the classical RCT design into the complex public health context have illuminated the limitations of RCTs as a tool for public health evaluation. This conundrum has also been associated with a rise in the use and sophistication of variants on the RCT design such as cluster randomization. These designs bring with them additional challenges that must be considered at trial development. A thorough understanding of the ethical issues and key criteria for methodological rigor is also key to a best-practice approach to understanding, designing, and reporting RCTs in the public health context.

Texts and Reference Works

Works such as Bulpitt 1996 and Matthews 2006 describe the principles of randomized controlled trials (RCTs) in the clinical setting, much of which is directly relevant to ensuring that RCTs in the public health arena are designed to provide the greatest possible statistical power. Torgerson and Torgerson 2008 addresses the complexities and additional challenges to rigor that often occur in conducting RCTs in the public health context. Hayes and Moulton 2009 provides a thorough exploration of issues related to cluster randomized trials, which are increasingly being used in health contexts where complete randomization is not appropriate.

  • Bulpitt, C. J. 1996. Randomised controlled clinical trials. 2d ed. Dordrecht, The Netherlands: Kluwer.

    DOI: 10.1007/978-1-4615-6347-1E-mail Citation »

    This older text provides a comprehensive background to the history and ethics of conducting RCTs, with a focus on clinical trials. Various types of RCT design options are described along with issues relating to sampling, recruitment, avoiding bias, cost-effectiveness, and the advantages and disadvantages of RCTs.

  • Hayes, R. J., and L. H. Moulton. 2009. Cluster randomised trials. Interdisciplinary Statistics. Boca Raton, FL: CRC Press.

    DOI: 10.1201/9781584888178E-mail Citation »

    Important concepts (including conditions when cluster designs are appropriate), design issues, and analysis issues for cluster randomized trials are addressed in this text. A range of key issues are explored, including variability between clusters, choice of clusters, matching and stratification, randomization procedures, sample size, and alternative designs. This text provides many examples and detailed instructions regarding statistical analysis.

  • Matthews, J. N. S. 2006. Introduction to randomized controlled clinical trials. Texts in Statistical Science. Boca Raton, FL: CRC Press.

    DOI: 10.1201/9781420011302E-mail Citation »

    Matthews provides a clear introduction to the RCT from a clinical perspective, describing key features and discussing issues of bias and methods of randomization, along with issues regarding the analysis of sample-size calculation. A strong focus is on issues key to clinical drug trials, such as blinding, placebos, and protocol violations.

  • Torgerson, D. J., and C. Torgerson. 2008. Designing randomised trials in health, education, and the social sciences: An introduction. New York: Palgrave Macmillan.

    DOI: 10.1057/9780230583993E-mail Citation »

    A range of research designs is covered, including RCTs, from a social sciences rather than clinical perspective. Chapters address topics such as placebo designs, sources of bias, cluster randomized trials, preference approaches, unequal allocation, sample-size issues, and the importance of assessing economic costs. Analytical approaches are addressed but are not a major focus of the text.

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