Steps in Systematic Data Analysis

Stepping Your Way through Effective Systematic Data Analysis

  1. Formulate the research question – Like any research process, a clear, unambiguous research question will help set the direction for your study, i.e. what type of health promotions campaigns have been most effective in reducing smoking rates of Australian teenagers or Does school leadership makes a difference to educational standards?

  2. Develop and use an explicit, reproducible methodology – Key to systematic reviews are that bias is minimized and that methods are transparent and reproducible.

  3. Develop and use clear inclusion/ exclusion criteria – The array of literature out there is vast. Determining clear selection criteria for inclusion is essential.

  4. Develop and use an explicit search strategy – It is important to identify all studies that meet the eligibility criteria set in #3. The search for studies need to be extensive should be extensive and draw on multiple databases.

  5. Critically assess the validity of the findings in included studies – This is likely to involve critical appraisal guides and quality checklists that cover participant recruitment, data collection methods, and modes of analysis. Assessment is often conducted by two or more reviewers who know both the topic area and commonly used methods.

  6. Analysis of findings across the studies – This can involve analysis, comparison, and synthesis of results using methodological criteria. This is often the case for qualitative studies. Quantitative studies generally attempt to use statistical methods to explore differences between studies and combine their effects (see meta analysis below). If divergences are found, the source of the divergence is analysed.

  7. Synthesis and interpretation of results – synthesized results need to be interpreted in light of both the limitations of the review and the studies it contains. An example here might be the inclusion of only studies reported in English. This level of transparency allows readers to assess the review credibility and applicability of findings.​