Synthesis is a stage in the systematic review process where extracted data (findings of individual studies) are combined and evaluated. The synthesis part of a systematic review will determine the outcomes of the review. Data synthesis summarises and/or present the charting results (from data extraction) as they relate to the review questions and objectives
There are two commonly accepted methods of synthesis in systematic reviews:
The way the data is extracted from your studies and synthesised and presented depends on the type of data being handled.
If you have quantitative information, some of the more common tools used to summarise data include:
If you have qualitative information, some of the more common tools used to summarise data include:
Whatever tool/s you use, the general purpose of extracting and synthesising data is to show the outcomes and effects of various studies and identify issues with methodology and quality. This means that your synthesis might reveal a number of elements, including:
In a quantitative systematic review, data is presented statistically. Typically, this is referred to as a meta-analysis.
The usual method is to combine and evaluate data from multiple studies. This is normally done in order to draw conclusions about outcomes, effects, shortcomings of studies and/or applicability of findings.
Remember, the data you synthesise should relate to your research question and protocol (plan). In the case of quantitative analysis, the data extracted and synthesised will relate to whatever method was used to generate the research question (e.g. PICO method), and whatever quality appraisals were undertaken in the analysis stage.
One way of accurately representing all of your data is in the form of a forest plot. A forest plot is a way of combining results of multiple clinical trials in order to show point estimates arising from different studies of the same condition or treatment.
It is comprised of a graphical representation and often also a table. The graphical display shows the mean value for each trial and often with a confidence interval (the horizontal bars). Each mean is plotted relative to the vertical line of no difference.
Another quantitative synthesis is Narrative Synthesis (NS): When meta-analysis isn’t feasible (due to diverse study designs or unsuitable data), NS provides an alternative. It involves systematically describing and organizing study results without statistical pooling.
Narrative synthesis is a method used in systematic reviews to summarize and explain findings from multiple studies primarily using words and text. Unlike statistical approaches, which rely on quantitative data, narrative synthesis focuses on organizing and describing study results in a coherent narrative. It’s particularly useful when meta-analysis isn’t feasible due to diverse study designs or unsuitable data.
In a qualitative systematic review, data can be presented in a number of different ways. A typical procedure in the health sciences is thematic analysis.
Thematic synthesis has three stages:
https://rmit.libguides.com/systematicreviews/synthesise