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).