Editor’s choice
Editor’s choice
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Systematic evidence syntheses bring clarity and confidence to decision-making by rigorously collating and synthesizing scientific findings on complex environmental and development challenges.
Decision-makers need reliable science-based information on what works, for whom and under which conditions. Systematic evidence syntheses, including systematic reviews and systematic maps, use structured, transparent and reproducible methods to identify, assess and combine findings from research. They provide robust and comprehensive evidence to support decision making in policy, planning or practice.
These syntheses can clarify conflicting findings, highlight knowledge gaps, inform research priorities and support funding decisions.
Unlike conventional literature reviews, systematic evidence syntheses follow predefined protocols, comprehensive literature searches, screening and critical appraisal of study quality. Evidence is synthesized using rigorous qualitative, quantitative or mixed methods.
SEI continuously contributes to the methodological development of evidence syntheses. See some examples below. For all our work in this field, visit this archive.
Journal article / This article aims to identify major pitfalls in the conduct and reporting of systematic reviews, making use of recent examples from across the field.
Journal article / This new CEE checklist helps editors and reviewers assess whether environmental reviews truly follow systematic methods.
Journal article / The paper discusses how qualitative evidence synthesis methods developed in other fields could be applied to evidence on environmental management and policy.
Journal article / This comment piece argues that l while literature reviews may be subject to bias if not conducted as systematic reviews.
Journal article / ROSES is a pro forma and flow diagram designed for systematic reviews and systematic maps in the field of conservation and environmental management.
Journal article / A consensus-driven definition of rapid evidence assessment for environmental applications, aimed at improving consistency and transparency.
SEI is advancing systematic evidence synthesis through methodological innovation. We are currently testing and developing AI-assisted approaches to improve efficiency of literature screening and qualitative data extraction.
Journal article / A large language model performed well when used for title and abstract eligibility screening of scientific articles and within a (systematic) literature review.
SEI brief / A pilot study explores the promise and limitations of AI tools to deliver accurate, consistent policy analysis at scale, through the SEI AI Reader.
Journal article / This position statement advocates for the responsible use of AI and automation in evidence synthesis.
Journal article / The authors examine the potential of AI to accelerate and improve evidence synthesis in conservation.
Project / This project develops a tool for AI-powered text analysis to be tested in systematic evidence synthesis reviews of research and policy papers.
SEI has been producing systematic evidence syntheses across a wide range of sustainability challenges. Below are some examples of our recent evidence synthesis publications.
Journal article / This systematic review and meta-analysis evaluates time use and time-savings related to WASH interventions in low- and middle-income countries.
Journal article / This systematic map provides an overview of research on technologies for recovering plant nutrients from human excreta and wastewater for agricultural reuse.
Journal article / This systematic review examines how forest vegetation and invertebrates are affected by manipulating grazing and browsing patterns.
Journal article / The authors present a protocol to systematically map the application of "charisma" in biodiversity conservation within peer-reviewed academic literature.
Journal article / This article systematically reviews global research on electric vehicle charging infrastructure demand.
Journal article / Find out the potential to mitigate emissions across the consumption domains of food, housing, transport and others.
Journal article / This article uses machine learning methods to create an evidence base on climate change and human health.
Journal article / This review examines interventions that guide consumer behaviour toward reducing food waste and adopting environmentally sustainable diets.
Past event / Join international experts for this webinar to explore how rapid and living evidence synthesis approaches can help deliver research findings to decision makers.
