systematic reviews: meta-analysis and meta-synthesis
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research integration and 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
forms of systematic reviews
- 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
criteria for meta-analysis in systematic review
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.
Steps in a Meta-Analysis
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.
Evaluating Study Quality
- Meta-analysts must make decisions about
- handling study quality
approaches to evaluating 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
Metasynthesis:Some Ongoing Debates
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
- –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
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