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Good review practice: a researcher guide to systematic review methodology in the sciences of food and health

Data synthesis and summary

Data Synthesis and Summary 

Data synthesis includes synthesising the findings of primary studies and when possible or appropriate some forms of statistical analysis of numerical data. Synthesis methods vary depending on the nature of the evidence (e.g., quantitative, qualitative, or mixed), the aim of the review and the study types and designs.  Reviewers have to decide and preselect a method of analysis based on the review question at the protocol development stage. 

Synthesis Methods

Synthesis Methods

Narrative summary: is a summary of the review results when meta-analysis is not possible. Narrative summaries describe the results of the review, but some can take a more interpretive approach in summarising the results. [8] These are known as "evidence statements" and can include the results of quality appraisal and weighting processes and provide the ratings of the studies.

Meta-analysis: is a quantitative synthesis of the results from included studies using statistical analysis methods that are extensions to those used in primary studies. [9] Meta-analysis can provide a more precise estimate of the outcomes by measuring and counting for uncertainty of outcomes from individual studies by means of statistical methods. However, it is not always feasible to conduct statistical analyses due to several reasons including inadequate data, heterogeneous data, poor quality of included studies and the level of complexity. [10]

Qualitative Data Synthesis (QDS): is a method of identifying common themes across qualitative studies to create a great degree of conceptual development compared with narrative reviews. The key concepts are identified through a process that begins with interpretations of the primary findings reported to researchers which will then be interpreted to their views of the meaning in a second-order and finally interpreted by reviewers into explanations and generating hypotheses. [11]

Mixed methods synthesis: is an advanced method of data synthesis developed by EPPI-Centre to better understand the meanings of quantitative studies by conducting a parallel review of user evaluations to traditional systematic reviews and combining the findings of the syntheses to identify and provide clear directions in practice. [11]

Good Practice points: The proposed methods of analysis, type and range of data, and the framework for grouping studies should be planned and documented at the protocol development stage and before conduct. It is advised to consult and ask for help from statisticians for appropriate guidance