Types of Synthesis
Evidence synthesis refers to the systematic process of identifying, collecting, appraising, and integrating evidence from multiple studies to provide a clearer, more comprehensive understanding of a given question.
This section provides an overview of the most important methodological types of evidence synthesis. It can help you decide which type of synthesis best suits your needs.
What is evidence synthesis?
Evidence synthesis refers to the process of systematically collecting, aggregating, and integrating existing evidence from multiple sources to draw more comprehensive and reliable conclusions than any individual studies can provide. It moves beyond summarizing individual findings by addressing variation across studies, assessing the quality and certainty of evidence, and highlighting patterns, gaps, and areas of consensus or disagreement. Evidence synthesis underpins informed decision-making in research, clinical practice, and policy by translating complex bodies of evidence into coherent, usable insights.
Choosing the right method
Choosing the appropriate synthesis method depends on factors such as the research question, the purpose of the review, and the type and amount of evidence available. It also influences how the results will be produced. Below, we outline some of the important synthesis methods: what kind of review it is, and what it is used for.
Want to read more about taxonomy in evidence synthesis? Have a look here
ESCA focuses primarily on scoping and systematic reviews
Why one type doesn’t fit all
Approach within one methodological type of synthesis, can still vary based on what kind of research question you are asking. ESCA also provides five major thematic areas of evidence synthesis, outlined further below on this page.
Systematic Review
A systematic review is a structured synthesis that follows a transparent, comprehensive, and predefined protocol. It involves identifying the evidence and appraising them, connecting the dots, and synthesizing new insights. The predefined methodology and appraisal process help minimize bias (1). Decision-makers consider systematic reviews an essential source of evidence-based information (2, 3).
Meta-Analysis
Meta-analysis refers to the statistical synthesis of results from a series of prior studies. It combines quantitative findings to produce a pooled estimate. While such statistical techniques can, in principle, be applied to any set of data, a meta-analysis yields meaningful results only when the evidence has been selected through a systematic and transparent process (1).
This statistical approach is appropriate, and often valuable, when multiple studies address the same or a very similar question, the outcomes are sufficiently similar (i.e., they measure the same thing in similar ways), the study populations are comparable, and the data reported are usable. In such cases, meta-analysis provides a pooled, more powerful estimate than any single study alone. If these conditions are not met, a systematic review can still be conducted to describe and summarize the findings or to apply synthesis without meta-analysis.
Synthesis Without Meta-Analysis (SWiM)
SWiM is a structured approach used when a meta-analysis is not feasible for some or all outcomes. SWiM provides a clear framework for summarizing prior evidence and ensures that findings are reported transparently and consistently, preserving the integrity of the review (4)
Scoping Review
Scoping reviews are used to explore the breadth, depth, and abundance of evidence on a topic, helping to identify gaps in the literature or examine how research is conducted. Unlike systematic reviews, they do not focus on narrowly defined questions or statistically synthesizing effect estimates. Instead, they serve as useful precursors, guiding future researchers on what evidence exists, and, more importantly, what does not.
While their aims differ from those of systematic reviews, scoping reviews similarly start with a predefined protocol (5), but typically do not include quality appraisal.
Evidence Gap Map
An evidence gap map is a visual tool that displays the availability, or lack of evidence across a given topic. Gap maps support scoping reviews by presenting their findings visually.
Umbrella Review
Also known as a review of reviews, an umbrella review synthesizes existing systematic reviews to provide a high-level overview of evidence on a topic. It enables comparison and contrast of findings when multiple systematic reviews are available, on a broad question, helping decision-makers navigate complex, conflicting, and often overlapping bodies of evidence (6). It helps to identify areas of consensus, uncertainty, or contradiction and avoid duplication when high quality systematic reviews already exist.
Guideline
Guidelines are recommendations for practice or policy that are developed using evidence syntheses. They are one way to translate evidence into actionable guidance (7). This process often involves the GRADE approach, which helps assess the certainty of evidence and guide the strength of recommendations. Guideline development typically considers benefits and harms, values and preferences, costs, and issues of equity and feasibility.
Living Review
A living systematic review is a continually updated review that incorporates new evidence as it becomes available, ensuring that the findings remain current and relevant. living systematic reviews are especially valuable in rapidly evolving fields where timely evidence can influence clinical, policy, or research decisions (8).
Advanced yet relative methods
Network Meta-Analysis
Network meta-analysis allows for the comparison of multiple interventions within a single analytical framework, even when direct comparisons are limited. This approach is especially useful in fields with several treatment options, where the goal is not just to assess whether a treatment works, but which treatment works best. In other words, by forming a network of comparisons across studies with a common control group, network meta-analysis enables a comprehensive understanding of relative efficacy (9).
Bayesian meta-analysis
Bayesian meta-analysis is a statistical approach to evidence synthesis that applies Bayesian inference. It is a more flexible and sometimes more sophisticated extension of traditional meta-analysis, grounded in Bayes’ theorem and the use of prior distributions.
Thematic areas of evidence synthesis
And external Methodological Guidance
1. Intervention Reviews
These reviews assess the effects of therapeutic, preventive, (medication or medical devices) or policy interventions. They typically use randomized controlled trials but may include observational non-randomized studies, and commonly include meta-analysis to quantify treatment effects.
2. Diagnostic Test Accuracy Reviews
These reviews evaluate how well a test identifies a condition compared to a reference standard. They usually involve statistical synthesis of sensitivity, specificity, and related measures.
3. Qualitative Evidence Syntheses
These syntheses usually explore people’s experiences, perspectives, or contextual factors in health and healthcare. They are used to understand how and why interventions work, for whom, and under what conditions.
4. Measurement Properties Review
Measurement reviews assess the measurement properties (e.g., validity, reliability, responsiveness) of outcome instruments. They are essential when selecting appropriate tools for research or practice.
5. Mixed Methods Reviews
These reviews combine quantitative and qualitative evidence to provide a more comprehensive understanding of complex questions. They are often used when both efficacy and contextual insights (i.e., in what setting does it work (or fail), what barriers or facilitators affect implementation?) are important.Introduction to mixed methods systematic reviews – JBI Manual for Evidence Synthesis – JBI Global Wiki