Cochrane Handbook for Systematic Reviews of Interventions by
The revised edition of the Handbook offers the only guide on how to conduct, report and maintain a Cochrane Review 
 The second edition of The Cochrane Handbook for Systematic Reviews of Interventions contains essential guidance for preparing and maintaining Cochrane Reviews of the effects of health interventions. Designed to be an accessible resource, the Handbook will also be of interest to anyone undertaking systematic reviews of interventions outside Cochrane, and many of the principles and methods presented are appropriate for systematic reviews addressing research questions other than effects of interventions. This fully updated edition contains extensive new material on systematic review methods addressing a wide-range of topics including network meta-analysis, equity, complex interventions, narrative synthesis, and automation. Also new to this edition, integrated throughout the Handbook, is the set of standards Cochrane expects its reviews to meet. Written for review authors, editors, trainers and others with an interest in Cochrane Reviews, the second edition of The Cochrane Handbook for Systematic Reviews of Interventions continues to offer an invaluable resource for understanding the role of systematic reviews, critically appraising health research studies and conducting reviews.
Evidence Synthesis for Decision Making in Healthcare by
In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish interventions that are both effective and cost-effective. Usually a single study will not fully address these issues and it is desirable to synthesize evidence from multiple sources. This book aims to provide a practical guide to evidence synthesis for the purpose of decision making, starting with a simple single parameter model, where all studies estimate the same quantity (pairwise meta-analysis) and progressing to more complex multi-parameter structures (including meta-regression, mixed treatment comparisons, Markov models of disease progression, and epidemiology models). A comprehensive, coherent framework is adopted and estimated using Bayesian methods. Key features: A coherent approach to evidence synthesis from multiple sources. Focus is given to Bayesian methods for evidence synthesis that can be integrated within cost-effectiveness analyses in a probabilistic framework using Markov Chain Monte Carlo simulation. Provides methods to statistically combine evidence from a range of evidence structures. Emphasizes the importance of model critique and checking for evidence consistency. Presents numerous worked examples, exercises and solutions drawn from a variety of medical disciplines throughout the book. WinBUGS code is provided for all examples. Evidence Synthesis for Decision Making in Healthcare is intended for health economists, decision modelers, statisticians and others involved in evidence synthesis, health technology assessment, and economic evaluation of health technologies.
Evidence Synthesis in Healthcare by
Evidence Synthesis in Healthcare - a Practical Handbook for Clinicians is the first book to reveal the field of Evidence Synthesis, by combining multiple sources of quantitative/qualitative data to derive the best evidence for use in healthcare. Through the use of clearly explained examples and practical explanations, Evidence Synthesis in Healthcare - a Practical Handbook for Clinicians describes the practical tools, techniques, uses and policy considerations of evidence synthesis techniques in modern healthcare practice.
Research Synthesis and Meta-Analysis by
The Fifth Edition of Harris Cooper's bestselling text offers practical advice on how to conduct a synthesis of research in the social, behavioral, and health sciences. The book is written in plain language with four running examples drawn from psychology, education, and health science. With ample coverage of literature searching and the technical aspects of meta-analysis, this one-of-a-kind book applies the basic principles of sound data gathering to the task of producing a comprehensive assessment of existing research. Available with Perusall--an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.
Introduction to Health Research Methods by
Designed to empower new investigators to conduct their own original research projects, the third edition of Introduction to Health Research Methods: A Practical Guide leads the reader step-by-step in performing quantitative and qualitative research in medicine, public health, and other clinical and population health fields. Organized in five sections, the text covers the entire research process from formulating a study question and selecting a study approach to collecting and analyzing data and then disseminating the findings. Chapters about methods for primary studies (collecting new data), secondary analyses (analyzing existing data), and tertiary studies (conducting literature reviews and meta-analyses) provide comprehensive coverage of the scope of health research. By breaking the research process down into a series of achievable steps, Introduction to Health Research Methods shows students and early career scholars how they can contribute to improving the health of individuals and communities through research. The Third Edition has been significantly updated to include: - Expanded coverage of qualitative research methods, including new chapters on qualitative study design, data collection, and data analysis. - Additional glossary terms that clarify key terminology for all stages of the research process and a diversity of study approaches. - Enhanced explanations of how to select and implement quantitative and qualitative research and analysis methodologies. - New and updated coverage of topics such as framing research questions, developing testable hypotheses, defining specific aims, responsibly conducting research, selecting study designs, minimizing bias, applying theoretical paradigms, ensuring rigor and reproducibility, conducting quality assessment, managing grants, and more.
Having identified and selected the studies for your systematic review, the next step is to extract the relevant data from the full-text using a standardised extraction form. The purpose of data extraction is to accurately summarise the studies in a format that will facilitate synthesis - for example, identifying the population, methodology, outcomes, etc.
Cornell University Library's guide on 'Data extraction' provide some useful tips on this stage of a systematic review.
Narrative synthesis uses a textual approach (relying primarily on the use of words and text) to analyse the similarities and differences between studies, relationships with the data, and an overall assessment of the evidence. Narrative synthesis is usually undertaken when included studies are too diverse to utilise meta-analyses. The synthesis should be rigorous and transparent to reduce the potential for bias. Fore more information, see the narrative synthesis section in the University of York's Systematic reviews: CRD's guidance for undertaking reviews in health care:
https://www.york.ac.uk/media/crd/Systematic_Reviews.pdf#page=60
Cochrane Training have produced a five videos series "Narrative synthesis" of quantitative effect data in Cochrane reviews: current issues and ways forward. These are aimed at review authors and editors and are about improving transparent reporting of synthesis without meta-analysis of effect sizes.
See also the SWiM (Synthesis Without Meta-Analysis) website: https://swim.sphsu.gla.ac.uk/
"Meta-analysis is a statistical technique for combining data from multiple studies on a particular topic".
From: https://s4be.cochrane.org/blog/2016/12/02/meta-analysis-what-why-and-how/
The What is meta-analysis? PDF from the 'What is' series provides a useful overview of meta-analysis. This includes sections on: What is meta-analysis?, benefits of meta-analyses, requirements for meta-analysis, conducting meta-analyses, presenting the findings, and limitations.
Crombie, I. K. & Davies, H. T. (2009). What is meta-analysis (2nd ed.). Haywood Medical Publications.
PRISMA is an evidence-based minimum set of items for reporting in systematic reviews and meta-analyses. PRISMA focuses on the reporting of reviews evaluating randomised trials, but can also be used as a basis for reporting systematic reviews of other types of research, particularly evaluations of interventions.
The PRISMA checklist - this 27 item checklist details the qualities a high-quality paper should contain.
The PRISMA Flow Diagram - designed to be used for researchers to depict the flow of information through the different phases of a systematic review. It maps out the number of records identified, included and excluded, and the reasons for exclusions. See example below of the PRISMA flow diagram for new systematic review which included searches of databases and registers only.
The PRISMA Extension for Searching - published in 2021, the checklist includes 16 reporting items, each of which is detailed with exemplar reporting and Rationale.
