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Evidence Synthesis and Systematic Review

Types of evidence synthesis

  • Systematic reviews involve the systematic and transparent collection and categorization of existing evidence related to a broad scientific, policy, or management question.
  • They compare, evaluate, and synthesize evidence to assess the effects of interventions. 
  • These reviews are time-intensive, often taking months to a year or more to complete. 
  • Systematic reviews are the most commonly referenced type of evidence synthesis but are sometimes mistakenly used as a blanket term for other types of reviews.
  • A statistical technique used to combine findings from diverse quantitative studies.
  • Utilizes statistical methods to objectively evaluate, synthesize, and summarize results.
  • Can be conducted independently or as part of a systematic review.
  • Applies systematic review methodology within a time-constrained setting.
  • Employs methodological "shortcuts" (such as limiting search terms) at the risk of introducing bias.
  • Useful for addressing urgent issues requiring quick decisions, such as developing policy recommendations.
  • Systematically and transparently collects and categorizes existing evidence related to a broad scientific, policy, or management question.
  • Aims to identify research gaps and opportunities for further evidence synthesis, rather than focusing on the effects of an intervention.
  • May critically evaluate existing evidence but does not synthesize the results in the same way that a systematic review does.
  • Typically takes longer to complete than a systematic review.
  • Reviews existing systematic reviews on a particular topic.
  • Often addresses a broader question than a traditional systematic review.
  • Most useful when comparing competing interventions.
  • A broad term that refers to reviews with wide scope and non-standardized methodology.
  • Search strategies, comprehensiveness, and the time range covered may vary and do not adhere to an established protocol.
  • Combines quantitative and qualitative research methodologies to provide a comprehensive understanding of a research question.
  • Integrates numerical data with descriptive data to allow for a richer interpretation of results.
  • Useful for exploring complex phenomena where both statistical analysis and subjective insights are valuable.
  • May vary in structure, blending findings from different types of studies to draw more nuanced conclusions.
  • Helps identify patterns, themes, and interrelationships that might not be evident when using a single-method approach.