Systematic Review

Systematic Review

Definition:
A systematic review is a rigorous, methodical, and transparent synthesis of research evidence on a specific question or topic. Unlike traditional narrative reviews, systematic reviews follow a predefined, replicable protocol to identify, appraise, and summarize all relevant studies, with the goal of minimizing bias and providing the most accurate and reliable answer possible.

Key Characteristics:

• Comprehensive and systematic search strategy
• Explicit inclusion and exclusion criteria
• Data extraction and, where possible, quantitative synthesis (meta-analysis)
• Transparent reporting of methods and results

Historical Context:
The systematic review framework emerged prominently in the 1970s and 1980s as researchers sought more objective, evidence-based approaches to summarizing medical literature. Organizations such as the Cochrane Collaboration helped formalize systematic review standards, which are now widely used in health sciences and other fields.

Applied Example:
A systematic review might address whether progressive resistance training improves strength in older adults, including a systematic search of randomized controlled trials, risk-of-bias assessments, and, if feasible, a meta-analysis to pool effect sizes.

Related Terms:

• Evidence-based practice
• Levels of evidence
• Meta-analysis

FAQ:

Q: How is a systematic review different from a narrative review?
A narrative review is more descriptive and often subjective, whereas a systematic review follows a structured, replicable methodology to minimize bias.

Q: What is the difference between a systematic review and a meta-analysis?
No. A systematic review is the broader process of collecting and synthesizing evidence; a meta-analysis is a statistical technique that may be included within a systematic review to combine numerical results.

Q: Why are systematic reviews important?
They help clinicians, researchers, and policymakers make evidence-informed decisions by summarizing high-quality, relevant studies in a transparent and unbiased way.

Brookbush Institute Recommended Approach for Systematic Reviews

• Include all available peer-reviewed and published original research
  • Prevents selection bias by avoiding arbitrary exclusion based on oversimplified evidence hierarchies
  • Ensures data that might challenge prior assumptions is not ignored
• Do not begin with a narrowly defined research question
  • Avoids confirmation bias from testing a predetermined hypothesis
  • Supports conclusions that emerge organically from the comprehensive data set
• Prioritize comparative research whenever available
  • Provides the most precise estimates of relative intervention effectiveness
  • Strengthens probabilistic models for optimizing intervention selection
• Recognize that study design alone does not guarantee methodological rigor
  • Understand that RCTs, observational studies, and cohort studies can be well-designed or poorly executed
  • Match study designs to the research question (e.g., RCTs for acute effects, cohort for longitudinal outcomes, observational for rare harms)
  • Apply a more defensible hierarchy based on controls (peer review, replication, blinding, statistical methods) rather than assuming one study type is always superior
• Apply a structured vote-counting method
  • Synthesizes directional trends across studies to identify the most likely superior intervention
  • Minimizes the influence of regression to the mean that may distort meta-analyses
  • Reduces errors from combining heterogeneous studies with unknown or unmeasured confounding variables
  • Follows a clearly defined rubric to interpret comparative research:
    • If A is better than B in most studies → Choose A
    • If trends are mixed but generally similar → Results are likely similar
    • Use moderator variables (e.g., age, sex, injury status) to explain divergent results when possible
• Be cautious with meta-analyses
  • Acknowledge they aggregate averages, which can obscure important patterns
  • Understand that combining heterogeneous studies may compound bias and inflate error
  • Avoid elevating meta-analyses above a clear trend established by direct comparative studies
• Incorporate systematic, objective in-practice comparisons where research is lacking
  • Approximate controlled experiments in clinical practice
  • Use objective outcome measures to track intervention effects within and across patients
  • Support Bayesian updating of expected-value estimates over time
• Integrate decision-theoretic frameworks
  • Prioritize interventions through expected-value optimization
  • Align systematic reviews with probabilistic models for better clinical and educational decision-making
• Commit to a fully evidence-driven curriculum
  • Develop every course and educational resource from a systematic review of all relevant, peer-reviewed research
  • Ensure educational content is maximally accurate, up-to-date, and focused on optimizing patient and client outcomes

References:

• Higgins JPT, Thomas J, Chandler J, et al., eds. Cochrane Handbook for Systematic Reviews of Interventions. Version 6.3. Cochrane, 2022.
• Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097.