This can get messy

In an ideal world, all of your studies would use consistent and unambiguous approaches to reporting their data and each paper’s abstract would clearly state the key information about the research and the results.

Unfortunately, this is rarely the case. Data extraction is not always as simple as copying and pasting numbers from a report into a spreadsheet. Sometimes you will have to do some calculations to standardize your numbers. Other times, you’ll have to do an interpretation of the results or the author’s intentions.

Very often, you’ll find mistakes and inconsistencies in the research. Here’s what two systematic review experts had to say about the data extraction process:


In other words, as you carefully pull out and organize the data in each of your studies, you’ll start to notice all kinds of errors and mistakes you might have otherwise missed.

When you see conflicting data or poorly reported methods, this is often a red flag that the research might be unreliable. That, or the authors made a typo. Get ready to think carefully about how to put all of this information into a clear, useful format.