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This guide will:
Start with this systematic review workbook, developed by the UOW library team. This workbook provides in-depth guidance on search experimentation, effective search strategies, replicating searches across databases, and options for tracking results.
A systematic review is an authoritative account of existing evidence using reliable, objective, thorough and reproducible research practices.
It is a method of making sense of large bodies of information and contributes to the answers to questions about what works and what doesn't.
Systematic reviews map areas of uncertainty and identify where little or no relevant research has been done, but where new studies are needed.
It is a good idea to familiarise yourself with the systematic review process before beginning your review. You can do this by searching for other systematic reviews to look at as examples, by reading a glossary of commonly used terms, and by learning how to distinguish between types of systematic review.
Some of the ways a systematic review differs from a literature review are outlined below.
| Systematic review | Literature review |
|---|---|
| High-level overview of primary research on a focused question that identifies, selects, synthesises, and appraises all high-quality research evidence relevant to that question | Qualitatively summarises evidence on a topic using informal or subjective methods to collect and interpret studies |
| Pre-specified eligibility or exclusion criteria | Pre-specified exclusion criteria not necessary |
| Systematic search strategy | Systematic search strategy not necessary |
| More than one author | Commonly one author |
| Eliminating bias is a key intention | Summarising literature on a topic is the key intention |
| Takes months to years to complete | Takes weeks to months to complete |
Kysh, Lynn (2013): Difference between a systematic review and a literature review. [figshare]
Systematic reviews help make sense of many kinds of data in a standardised, systematic way.
Watch this video from the Cochrane Library for more information about systematic reviews.
Systematic reviews help make sense of many kinds of data. They're a way of reviewing all the data and results from research about a particular question in a standardised, systematic way.
A systematic review helps give an objective and transparent overview of all eidence surrounding a particular question.
The Cochrane Collaboration logo visually represents how results from some systematic review works. First a question must be defined and an objective method for asking the question is agreed.
Imagine a circle as the area defined by a question. Everything inside it concerns the question; everything outside of it does not. In this circle, relevant data will be included. A search for relevant data begins.
This data can come from many sources including data from clinical trials. Imagine the shapes represent datasets from different research, for example, different clinical trials. The dataset must be the right shape to fit.
Only data from research that matches certain criteria can be included so that the results are reliable. For example, selecting research that is good quality and answers the defined question.
If the research meets the criteria, more detailed information about the research can be collected or extracted. Information extracted can include:
This information is judged against criteria in order to access the quality of the research. Once the information is extracted, it can be combined using complex statistical methods to give an overall result from all of the data.
(Video shows a circle with a line down the middle. Short and long lines come off the centre line.) This circle is one way of representing this data visually. It's called a blob-o-gram or a forest plot.
The area of inquiry, defined by the question, can be divided into a "yes" and "no" half; a positive and a negative side. The shorter the line, the more confident we are of what the data is telling us. Think of a longer line as less focused and scattered data, and shorter as more focused and bunched.
Imagine knowledge is light and ignorance is darkness. The more spread out the focus of the light, the weaker it is and the less clear things are. If the light is focused and the data is grouped more clearly, we can be more confident of what we see.
(A diamond appears at the bottom of the forest plot circle.) The diamond represents the combined results of all the data included because this combined result uses data from more sources than just one dataset. It's considered more reliable and better evidence; the more data there is, the more confident we can be.
You can always ask us for help.
We can assist you with the searching component of your systematic review including:
For more in-depth information about the systematic review process, see: