Cluster randomised trials are trials in which groups (or clusters) of individuals are randomly allocated to different forms of treatment. In health care, these trials often compare different ways of managing a disease or promoting healthy living, in contrast to conventional randomised trials which randomise individuals to different treatments, classically comparing new drugs with a placebo. They are increasingly common in health services research. This book addresses the statistical, practical, and ethical issues arising from allocating groups of individuals, or clusters, to different interventions. Key features: Guides readers through the stages of conducting a trial, from recruitment to reporting. Presents a wide range of examples with particular emphasis on trials in health services research and primary care, with both principles and techniques explained. Topics are specifically presented in the order in which investigators think about issues when they are designing a trial. Combines information on the latest developments in the field together with a practical guide to the design and implementation of cluster randomised trials. Explains principles and techniques through numerous examples including many from the authors own experience. Includes a wide range of references for those who wish to read further. This book is intended as a practical guide, written for researchers from the health professions including doctors, psychologists, and allied health professionals, as well as statisticians involved in the design, execution, analysis and reporting of cluster randomised trials. Those with a more general interest will find the plentiful examples illuminating.

Cluster randomised trials are trials in which groups (or clusters) of individuals are randomly allocated to different forms of treatment. In health care, these trials often compare different ways of managing a disease or promoting healthy living, in contrast to conventional randomised trials which randomise individuals to different treatments, classically comparing new drugs with a placebo. They are increasingly common in health services research. This book addresses the statistical, practical, and ethical issues arising from allocating groups of individuals, or clusters, to different interventions. Key features: Guides readers through the stages of conducting a trial, from recruitment to reporting. Presents a wide range of examples with particular emphasis on trials in health services research and primary care, with both principles and techniques explained. Topics are specifically presented in the order in which investigators think about issues when they are designing a trial. Combines information on the latest developments in the field together with a practical guide to the design and implementation of cluster randomised trials. Explains principles and techniques through numerous examples including many from the authors own experience. Includes a wide range of references for those who wish to read further. This book is intended as a practical guide, written for researchers from the health professions including doctors, psychologists, and allied health professionals, as well as statisticians involved in the design, execution, analysis and reporting of cluster randomised trials. Those with a more general interest will find the plentiful examples illuminating.

A complete guide to understanding cluster randomised trials Written by two researchers with extensive experience in the field, this book presents a complete guide to the design, analysis and reporting of cluster randomised trials. It spans a wide range of applications: trials in developing countries, trials in primary care, trials in the health services. A key feature is the use of R code and code from other popular packages to plan and analyse cluster trials, using data from actual trials. The book contains clear technical descriptions of the models used, and considers in detail the ethics involved in such trials and the problems in planning them. For readers and students who do not intend to run a trial but wish to be a critical reader of the literature, there are sections on the CONSORT statement, and exercises in reading published trials. Written in a clear, accessible style Features real examples taken from the authors’ extensive practitioner experience of designing and analysing clinical trials Demonstrates the use of R, Stata and SPSS for statistical analysis Includes computer code so the reader can replicate all the analyses Discusses neglected areas such as ethics and practical issues in running cluster randomised trials How to Design, Analyse and Report Cluster Randomised Trials in Medicine and Health Related Research provides an excellent reference tool and can be read with profit by statisticians, health services researchers, systematic reviewers and critical readers of cluster randomised trials.

Interest in implementation research is growing, largely in recognition of the contribution it can make to maximizing the beneficial impact of health interventions. As a relatively new and, until recently, rather neglected field within the health sector, implementation research is something of an unknown quantity for many. There is therefore a need for greater clarity about what exactly implementation research is, and what it can offer. This Guide is designed to provide that clarity. Intended to support those conducting implementation research, those with responsibility for implementing programs, and those who have an interest in both, the Guide provides an introduction to basic implementation research concepts and language, briefly outlines what it involves, and describes the many opportunities that it presents. The main aim of the Guide is to boost implementation research capacity as well as demand for implementation research that is aligned with need, and that is of particular relevance to health systems in low- and middle-income countries (LMICs). Research on implementation requires the engagement of diverse stakeholders and multiple disciplines in order to address the complex implementation challenges they face. For this reason, the Guide is intended for a variety of actors who contribute to and/or are impacted by implementation research. This includes the decision-makers responsible for designing policies and managing programs whose decisions shape implementation and scale-up processes, as well as the practitioners and front-line workers who ultimately implement these decisions along with researchers from different disciplines who bring expertise in systematically collecting and analyzing information to inform implementation questions. The opening chapters (1-4) make the case for why implementation research is important to decision-making. They offer a workable definition of implementation research and illustrate the relevance of research to problems that are often considered to be simply administrative and provide examples of how such problems can be framed as implementation research questions. The early chapters also deal with the conduct of implementation research, emphasizing the importance of collaboration and discussing the role of implementers in the planning and designing of studies, the collection and analysis of data, as well as in the dissemination and use of results. The second half of the Guide (5-7) detail the various methods and study designs that can be used to carry out implementation research, and, using examples, illustrates the application of quantitative, qualitative, and mixed-method designs to answer complex questions related to implementation and scale-up. It offers guidance on conceptualizing an implementation research study from the identification of the problem, development of research questions, identification of implementation outcomes and variables, as well as the selection of the study design and methods while also addressing important questions of rigor.

A complete guide to understanding cluster randomised trials Written by two researchers with extensive experience in the field, this book presents a complete guide to the design, analysis and reporting of cluster randomised trials. It spans a wide range of applications: trials in developing countries, trials in primary care, trials in the health services. A key feature is the use of R code and code from other popular packages to plan and analyse cluster trials, using data from actual trials. The book contains clear technical descriptions of the models used, and considers in detail the ethics involved in such trials and the problems in planning them. For readers and students who do not intend to run a trial but wish to be a critical reader of the literature, there are sections on the CONSORT statement, and exercises in reading published trials. Written in a clear, accessible style Features real examples taken from the authors’ extensive practitioner experience of designing and analysing clinical trials Demonstrates the use of R, Stata and SPSS for statistical analysis Includes computer code so the reader can replicate all the analyses Discusses neglected areas such as ethics and practical issues in running cluster randomised trials How to Design, Analyse and Report Cluster Randomised Trials in Medicine and Health Related Research provides an excellent reference tool and can be read with profit by statisticians, health services researchers, systematic reviewers and critical readers of cluster randomised trials.

Cluster Randomised Trials, Second Edition discusses the design, conduct, and analysis of trials that randomise groups of individuals to different treatments. It explores the advantages of cluster randomisation, with special attention given to evaluating the effects of interventions against infectious diseases. Avoiding unnecessary mathematical detail, the book covers basic concepts underlying the use of cluster randomisation, such as direct, indirect, and total effects. In the time since the publication of the first edition, the use of cluster randomised trials (CRTs) has increased substantially, which is reflected in the updates to this edition. There are greatly expanded sections on randomisation, sample size estimation, and alternative designs, including new material on stepped wedge designs. There is a new section on handling ordinal outcome data, and an appendix with descriptions and/or generating code of the example data sets. Although the book mainly focuses on medical and public health applications, it shows that the rigorous evidence of intervention effects provided by CRTs has the potential to inform public policy in a wide range of other areas. The book encourages readers to apply the methods to their own trials, reproduce the analyses presented, and explore alternative approaches.

The book focuses on the design of rigorous trials rather than their statistical underpinnings, with chapters on: pragmatic designs; placebo designs; preference approaches; unequal allocation; economics; analytical approaches; randomization methods. It also includes a detailed description of randomization procedures and different trial designs.