Data synthesis
Different studies addressing the same question can have varying results. It is the aggregation of all these studies that provides a clearer and more comprehensive picture. Data synthesis is a crucial stage in any evidence synthesis, as it combines the data from all included studies to answer the review question.
The synthesis stage of a literature review involves combining the extracted data to find new meaning. Different synthesis techniques are used depending on the type of data.
Techniques for data synthesis
The techniques used to synthesise data depend on the type of data and the nature of the review. Quantitative data can be combined using statistical or graphical methods, while qualitative data can be organised into themes.
Common techniques for synthesising data are:
- Summarising data
- Coding data into themes
- Representing data graphically (e.g., forest plots or bubble plots)
- Presenting data in tables
- Pooling data for additional statistical analysis (if suitable)
Tip
It is important to check for available statistical software to support quantitative syntheses and refer to review guidelines for specific synthesis methods.
Presenting data synthesis in a review
The analysis of data presented in the final review should include a narrative summary of the data synthesis process. This summary should explain the review findings and their implications for the real world.
Note
For further information on the synthesis stage of a literature, check out the following resources: Introduction to Meta-Analysis, Synthesizing and presenting findings using other methods, and Synthesising quantitative and qualitative evidence to inform guidelines on complex interventions.