About Systematic Reviews
Meta-Analysis Data Extraction
Meta-analysis involves statistically assessing quantitative results from previous studies to derive conclusions. Meta-analysis is conducted when several studies around an intervention question have different results; it aims to analyze the variations in these results and establish statistical differences.
Meta-analysis can be part of the systematic review process—you may have to perform meta-analysis to summarize and quantify the data extracted from the individual studies. In this article, you’ll learn about meta-analysis data extraction and examples of data extraction forms for systematic reviews.
Meta-Analysis and Systematic Review
Meta-analysis is the process of using statistical methods to combine the results of different studies. It aims to integrate the findings, pool the data, and identify the overall trend of results. It is primarily a quantitative method that uses and meticulously analyzes data from multiple individual studies to arrive at one or more conclusions
Since meta-analyses are statistical procedures for combining data from multiple separate studies, they should only ever be conducted in the context of systematic reviews.
Think of meta-analysis as an approach to combine data derived in a systematic review process. Because systematic reviews involve collecting data from individual studies that are relevant to a specific question, meta-analysis can be used to synthesize the extracted data.
However, not all systematic review processes involve meta-analysis. These types of systematic review processes are known as narrative synthesis–they rely on using words and text to summarize and explain findings rather than a meta-analysis of standardized effect sizes.
Data Extraction for Meta-Analysis
Data extraction is the process that occurs after identifying the relevant studies and before data analysis in a systematic review process. In the case of meta-analysis, data extraction aims to collect the data necessary to identify trends across the individual studies included in the review.
Data extraction forms are used to extract data from the studies that match the review question. You’ll have to design and test a data extraction form to ensure that it will collect the right data from the individual studies.
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How to Create Data Extraction Forms
1. Spreadsheets and Database Software
You can create data extraction forms using spreadsheet software like Microsoft Excel and Google Spreadsheets. These softwares have functions that enable you to speed up the data entry process and reduce the number of errors that may occur. Databases like Microsoft Access also help you extract information on categories such as citation details, participant selection, intervention, and outcomes.
2. Systematic Review Software
Systematic review software has numerous functions, including machine learning, visualization, and reporting. Other systematic review software usually have data extraction functionality, so you can create and publish a data extraction template to capture useful data from relevant studies.
3. Electronic Documents
Data extraction from unstructured documents for living reviews can be accomplished using Google Docs, but unstructured data must be rearranged into a defined model before being analyzed. For example, data from physical sources such as newspapers and journals must be manually keyed into Google Docs for the reviewer to begin the meta-analysis process.
Meta-analysis is a statistical procedure used to summarize data from multiple studies. It can be a key part of the systematic review process by which researchers uncover trends across individual studies.