systematic reviews: meta-analysis and meta-synthesis

The systematic and rigorous integration and synthesis of evidence is a cornerstone of EBP.

Impossible to develop “best practice” guidelines, protocols, and procedures without organizing and evaluating research evidence through a systematic review

is a review that methodically integrates research evidence about specific research question using careful sampling and data collection procedures that are spelled out in advance in a protocol

• meta-analysis
• metasynthesis

• statistical integration of results used to compute common effect size. effect sixes are averaged across studies, yielding not only information about the existence of a relationship between variable in many studies but also an estimate of its magnitude across studies
• it is the pinnacle of traditional evidence hierarchies

• theoretical integration and interpretation of qualitative findings
• are products that are more than the sum of the parts - they offer new insights and interpretation of findings

Objectivity—statistical integration eliminates bias in drawing conclusions when results in different studies are at odds.

Increased power—reduces the risk of a type II error compared to a single study

Research question or hypothesis should be essentially identical across studies.–The “fruit” problem—don’t combine apples and oranges!

Must be a sufficient knowledge base—must be enough studies of acceptable quality

Results can be varied but not totally at odds.

Problem formulation: Delineate research question or hypothesis to be tested.

Design of meta-analysis: Identify sampling criteria for studies to be included.

Search for evidence in literature: Develop and implement a search strategy.

Evaluation of study quality: Locate and screen sample of studies meeting the criteria.

Extract and encode data for analysis.

Calculate effects.

Data analysis

• Meta-analysts must make decisions about
• handling study quality

• –Omit low-quality studies (e.g., in
• intervention studies, non-RCTs).

–Give more weight to high-quality studies.

• –Analyze low- and high-quality studies to
• see if effects differ (sensitivity
• analyses).

Whether to exclude low-quality studies

Whether to integrate studies based in multiple qualitative traditions

Various typologies and approaches; differing terminology

Similar to meta-analysis in many ways

–Formulate problem.

• –Decide on design: selection criteria,
• search strategy.

–Search for data in the literature.

–Evaluation of study quality.

–Extract data for analysis.

–Data analysis and interpretation