Introduction to meta-analyses and systematic reviews

The training will focus on lectures and hands-on exercises during the first three days, with small-group projects scheduled for the final day and a half.

Monday

• Icebreaker and overview of the week
• Introduction to knowledge synthesis
• The systematic review protocol
• Importance of stakeholder engagement
• Literature search: formulating search strings (PECO/PICO approach)
• Literature search: databases
• Building and cleaning the corpus
• Systematic screening of articles: title, abstract, and full-text screening
• Systematic screening of articles: importance of eligibility criteria

Tuesday

• Introduction to AI-assisted screening [ENG]
• Reporting
• Systematic maps and metadata extraction
• Machine learning approaches for metadata extraction [ENG]
• Qualitative syntheses and visualization

Wednesday

• Critical appraisal
• Quantitative approaches: effect sizes, Hedges’ d/g, odds ratios
• Extraction of quantitative data
• Quantitative syntheses and visualization
• Risk of bias and interpretation of results

Thursday

• Group projects

Friday

• Project presentations

Meta analyses and Systematic reviews are becoming more and more popular in the scientific literature. We need such approaches, especially in the field of ecology, because there is an ever-increasing number of studies looking at very similar questions, and frequently with contradictory/differing results. Indeed, it is very challenging for the average reader, clinician, manager, or even researcher to make sense of this mass of scientific literature without it being treated and synthesized in a meaningful way.

Historically, the application of meta-analysis first came from the field of medical research (Cochrane) designed to objectify decision making (medical treatments) through quantitatively synthesizing a large collection of results from individual studies. In ecology, there existed narrative reviews. They were often written by expert opinion leaders, but were done using non-systematic methods, and based on the research that is known to them, as opposed to the full spectrum of existing knowledge.

Today, the importance of using systematic methods to reduce bias in reviews of a body of evidence is somewhat distinguished as an issue separate from meta-analysis. Systematic reviews follow a standardized framework ensuring objectivity, comprehensiveness, transparency, and replicability to identify and synthesize the results of all relevant independent studies (for ecology, the reference association is the Collaboration for Environmental Evidence (CEE)). They are often considered the strongest form of scientific evidence synthesis because they minimize the different types of bias offering increased statistical power and robust results, which can help to resolve conflicting results across primary studies.