Table of Contents
How you organize your research is incredibly important; whether you’re preparing a report, research review, thesis or an article to be published. What methodology you choose can make or break your work getting out into the world, so let’s take a look at two main types: systematic review and meta-analysis.
Let’s start with what they have in common – essentially, they are both based on high-quality filtered evidence related to a specific research topic. They’re both highly regarded as generally resulting in reliable findings, though there are differences, which we’ll discuss below. Additionally, they both support conclusions based on expert reviews, case-controlled studies, data analysis, etc., versus mere opinions and musings.
A systematic review is a form of research done collecting, appraising and synthesizing evidence to answer a particular question, in a very transparent and systematic way. Data (or evidence) used in systematic reviews have their origin in scholarly literature – published or unpublished. So, findings are typically very reliable. In addition, they are normally collated and appraised by an independent panel of experts in the field. Unlike traditional reviews, systematic reviews are very comprehensive and don’t rely on a single author’s point of view, thus avoiding bias.
Systematic reviews are especially important in the medical field, where health practitioners need to be constantly up-to-date with new, high-quality information to lead their daily decisions. Since systematic reviews, by definition, collect information from previous research, the pitfalls of new primary studies is avoided. They often, in fact, identify lack of evidence or knowledge limitations, and consequently recommend further study, if needed.
Why are systematic reviews important?
This form of research relies on combining statistical results from two or more existing studies. When multiple studies are addressing the same problem or question, it’s to be expected that there will be some potential for error. Most studies account for this within their results. A meta-analysis can help iron out any inconsistencies in data, as long as the studies are similar.
For instance, if your research is about the influence of the Mediterranean diet on diabetic people, between the ages of 30 and 45, but you only find a study about the Mediterranean diet in healthy people and another about the Mediterranean diet in diabetic teenagers. In this case, undertaking a meta-analysis would probably be a poor choice. You can either pursue the idea of comparing such different material, at the risk of findings that don’t really answer the review question. Or, you can decide to explore a different research method (perhaps more qualitative).
Why is meta-analysis important?
Undertaking research approaches, like systematic reviews and/or meta-analysis, involve great responsibility. They provide reliable information that has a real impact on society. Elsevier offers a number of services that aim to help researchers achieve excellence in written text, suggesting the necessary amendments to fit them into a targeted format. A perfectly written text, whether translated or edited from a manuscript, is the key to being respected within the scientific community, leading to more and more important positions like, let’s say…being part of an expert panel leading a systematic review or a widely acknowledged meta-analysis.
Check why it’s important to manage research data.
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