How can you synthesize findings from multiple studies using meta-analysis?

1 Define your research question and criteria

The first step is to define your research question and the criteria for selecting studies to include in your meta-analysis. Your question should be clear, focused, and relevant to your field of interest. Your criteria should specify the population, intervention, comparison, outcome, and study design (PICOS) of the studies you are looking for. You should also decide on the keywords, databases, and search strategies you will use to find the studies.

2 Screen and select the studies

The second step is to screen and select the studies that meet your criteria and are suitable for your meta-analysis. You should use a systematic and transparent process to identify, assess, and exclude studies based on their titles, abstracts, and full texts. You should also document the reasons for exclusion and report the number of studies at each stage of screening. You can use a PRISMA flow diagram to illustrate your selection process.

3 Extract and code the data

The third step is to extract and code the data from the selected studies. You should create a data extraction form or spreadsheet to collect the relevant information from each study, such as the authors, year, sample size, outcome measures, effect sizes, and confounding variables. You should also code the studies based on their characteristics, such as the type of intervention, the setting, the quality, and the risk of bias. You should check the accuracy and consistency of your data extraction and coding.

4 Analyze and synthesize the data

The fourth step is to analyze and synthesize the data using statistical methods and software. You should choose the appropriate model, measure, and method for your meta-analysis, depending on the type and distribution of your data, the heterogeneity of the studies, and the assumptions of the analysis. You should also perform sensitivity, subgroup, and meta-regression analyses to explore the sources of variation and moderation in your results. You should report the summary effect size, the confidence interval, the heterogeneity statistics, and the forest plot for your meta-analysis.

5 Assess and report the quality and validity

The fifth step is to assess and report the quality and validity of your meta-analysis. You should evaluate the quality of the studies included in your meta-analysis using a standardized tool or checklist, such as the Cochrane risk of bias tool or the GRADE approach. You should also assess the validity of your meta-analysis using methods such as funnel plot, Egger's test, or trim-and-fill method to detect and correct for publication bias, selective reporting, or small-study effects. You should report the results of your quality and validity assessments and discuss their implications for your meta-analysis.

6 Interpret and communicate the findings

The sixth and final step is to interpret and communicate the findings of your meta-analysis. You should summarize the main findings, the strengths and limitations, and the implications and recommendations of your meta-analysis. You should also compare and contrast your findings with the existing literature and explain the possible reasons for agreement or disagreement. You should communicate your findings in a clear, concise, and coherent way, using tables, graphs, and text. You should also follow the reporting guidelines, such as the PRISMA statement or the MOOSE checklist, to ensure the transparency and completeness of your meta-analysis.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?