How can we review evidence to inform our work? In this course you will learn about types of evidence reviews relevant for public health, including systematic reviews and meta-analysis.
Researchers and practitioners often have to consolidate and review evidence to inform their work. However, assessing the quality of evidence, or knowing what type of review needs to be done, is not always straight forward. Therefore, this course is aimed at researchers and public health practitioners at any level who are interested in evaluating scientific evidence and/or conducting systematic reviews and meta-analyses of published work.
In the course, we will learn about the types of evidence reviews relevant for public health practice and research, including systematic review and meta-analysis. Starting with the definition of the question and problem specification, search methodology and screening, data extraction, and assessment of the quality of the papers. We have an introduction to the most important study designs that can inform research and practice, describing their characteristics and how to appraise them. This is essential to allow participants to perform a risk-of-bias assessment for each primary study included in the reviews.
Particular emphasis will be then given to meta-analytic methods to pool the quantitative evidence available, describing the different types of models available and how to assess quantitative heterogeneity (ie. variability of intervention effects across studies) including specific test of homogeneity, outlier detection and meta-regression analysis. We will also examine methods to assess small studies effects, ways to assess publication bias and sensitivity analyses. We will describe how to interpret and report meta-analysis results via forest plots and how they can complete a systematic reviews.
Finally we will discuss how systematic reviews and meta-analysis can be planned, performed and reported in a reliable, transparent and reproducible way.
By the end of the course participants should be able to:
No pre-knowledge of statistical models is required although a degree of familiarity with basic epidemiological concepts and outcomes would be preferable. Ideally, every participant should install on their laptop (whether Windows or Mac) the freely-available softwares R and its graphical interface R-Studio so to perform hands-on meta-analyses.
This 3-day course is a mixture of theoretical lectures, tutor-facilitated small group sessions, hands-on tutorials and computer exercises with presentations and feedback given.
At least one facilitator will be on-site in Lugano, and some will join online. Participants are welcomed to join either on-site in Lugano, or online. In case of a change of regional policies (e.g., Covid) or personal reasons, the course could change to online.