You will need to extract data from the selected studies to synthesize and analyze. In addition to collecting general information about each study and those extracting the data, you may want to consider if they are relevant to your research question.
Category |
Data Elements |
---|---|
Participants | Total number of participants, Setting, Diagnostic criteria, Age, Sex, Race/Ethnicity, Location (country, state, county, etc.), Co-morbidities, Socio-demographics, Spectrum of presenting symptoms and current treatments, Date of study, Date of recruitment and follow-up, Participant sampling |
Intervention | Total number of intervention groups, Specific intervention, Intervention details, Integrity of intervention |
Outcomes | Outcomes and time points (i) collected & (ii) reported, Outcome definition (with diagnostic criteria if relevant), Unit of measurement |
Comparisons | Comparison |
Results | Sample size, Missing participants, Summary data for each intervention group, Estimate of effect with confidence interval ( P value), Subgroup analyses, Adverse events and side effects for each study group |
Interpretation | Overall evidence, Generalizability: external validity of trial findings |
Objectives | Research questions and hypotheses |
Method | Reference standard and its rationale, Technical specifications, Study design, Total study duration, Sequence generation, Allocation sequence concealment, Blinding, Methods used to generate random allocation sequence, implementation, Other concerns about bias, Methods used to compare groups for primary outcomes and for additional analyses, Methods for calculating test reproducibility, Definition and rationale for the units, cutoffs and/or categories of the results of the index tests and reference standard, Number, training, and expertise of the persons executing and reading the index tests and the reference standard, Participant flow |
Qualitative | Noting patterns and themes, Seeing plausibility (ensuring conclusions make good sense), Clustering, Making metaphors, Counting, Making contrasts/comparisons, Partitioning variables, Subsuming particulars into the general, Noting relations between variables, Building a logical chain of evidence, Making conceptual/theoretical coherence |
Miscellaneous | Funding source, Key conclusions of the study authors, Clinical applicability, Miscellaneous comments from the study authors, References to other relevant studies, Correspondence required, Miscellaneous comments by the review authors |
Adapted from Jonnalagadda, S.R., Goyal, P. & Huffman, M.D. Automating data extraction in systematic reviews: a systematic review. Syst Rev 4, 78 (2015). https://doi.org/10.1186/s13643-015-0066-7 and
Booth, A. (2016). Systematic approaches to a successful literature review (Second edition.). Sage.
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