3.8 Step 8: Data synthesis
Data synthesis is the combined evaluation of extracted data – qualitative, quantitative, or mixed for evidence and decision-making. It is about the organization and presentation of data from the findings of the actual review to draw conclusion about a body of evidence. The implication of this stage/activity in SLR is the systematic and holistic assessment of results of individual study included with particular attention paid to key features of the studies, which may include but may not be limited to study design, study subjects, etc. Depending on what the purpose and the criteria set for the study are, data from both qualitative and quantitative studies can serve complementing or triangulating role for the purpose of exploratory or explanatory of evidence. For qualitative data, a narrative or meta-synthesis allows the SLR and combination findings and “offer an appropriate balance between an objective framework, a rigorously scientific approach to data analysis and the necessary contribution of the researcher’s subjectivity in the construction of the final work” (Lachal, Revah-Levy, Orri, & Moro, 2017. p.1). Meta-synthesis builds a rigorous foundation for reporting given that it is not constrained to synthesising studies for the purpose of comparison, which is largely great when reporting findings. For quantitative data, a statistical synthesis is employed in the context of meta-analysis, the combination of statistical results from multiple studies. Like in the medical field, in the domain of IS the implementation of new systems and the application of digital health interventions carry potential for change. As such the application of data synthesis methodologies such as realistic synthesis helps in the categorizations of these changes for evidence-based decision making. A good SLR should make it easier for the practitioner to understand the research by synthesizing extensive primary research papers from which it was derived (Tranfield et al., 2003).