Indiscriminate use has led critics to warn against potential abuses.Ĭriteria for Using Meta-Analytic Techniques in a Systematic Review In a narrative review, 10 nonsignificant findings would almost surely be interpreted as lack of evidence of a true effect, which could be the wrong conclusion.ĭespite these advantages, meta-analysis is not always appropriate. In a meta-analysis, it is possible to conclude that a relationship is real (e.g., an intervention is effective), even when several small studies yielded nonsignificant findings. By combining effects across multiple studies, power is increased. Readers of a meta-analysis can be confident that another analyst using the same data set and analytic decisions would come to the same conclusions.Īnother advantage of meta-analysis concerns power, i.e., the probability of detecting a true relationship between variables (see Chapter 14). The integration itself also is objective because it uses statistical formulas. Meta-analysts make decisions that are explicit and open to scrutiny. Narrative reviewers make subjective decisions about how much weight to give findings from different studies, and so different reviewers may reach different conclusions in reviewing the same studies. It is difficult to draw objective conclusions about a body of evidence using narrative methods when results are inconsistent, as they often are. Meta-analysis offers a simple advantage as an integration method: objectivity. Effect size values are averaged across studies, yielding information about the relationship between variables across multiple studies. The essence of a meta-analysis is that findings from each study are used to compute a common index, an effect size. Meta-analyses of randomized controlled trials (RCTs) are at the pinnacle of traditional evidence hierarchies for Therapy questions (see Fig. This chapter provides a brief introduction to this important and complex topic. The field of research integration is expanding steadily. Many terms exist for such endeavors (e.g., meta-study, meta-ethnography), but the one that has emerged as the top term is metasynthesis. Qualitative researchers have also developed techniques to integrate findings across studies. Statistical integration, however, is sometimes inappropriate, as we shall see. Most reviews in the Cochrane Collaboration, for example, are meta-analyses. Narrative systematic reviews continue to be published, but meta-analytic techniques that use statistical integration are widely used. Twenty years ago, systematic reviews usually involved narrative integration, using nonstatistical methods to synthesize research findings. The review process is disciplined and transparent so that readers of a systematic review can assess the integrity of the conclusions. This chapter provides guidance in helping you to understand and evaluate systematic research integration.Ī systematic review integrates research evidence about a specific research question using careful sampling and data collection procedures that are spelled out in advance. Systematic reviews, a cornerstone of evidence-based practice (EBP), are inquiries that follow many of the same rules as those for primary studies, i.e., original research investigations. This chapter also discusses reviews of existing evidence but focuses on systematic reviews, especially those in the form of meta-analyses and metasyntheses. In Chapter 7, we described major steps in conducting a literature review. Discuss alternative approaches to integrating research evidence and advantages to using systematic methodsĭescribe key decisions and steps in doing a meta-analysis and metasynthesisĬritique key aspects of a written systematic review
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