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Systematic Literature Reviews

What Data to Collect

Determining what information to collect during the coding phase of a systematic review should be developed in the early planning stages. It is important to have a realistic and clear understanding of the information that will be extracted from each of the articles. Overlooking important information in the initial data extraction phase can weaken the quality of the review and may require extra time to return to each article to gather this information. 

Typically, the data collected will include the following elements:

  • Study methods (study design, statistical analysis, etc.)
  • Participants (setting, geographic location, demographic information, etc.)
  • Intervention (description of how the study is testing/observing the research questions, etc.)
  • Outcomes (dependent variables in the study, including measurement tool or instrument)
  • Results (summary data for study participants/groups, both significant/non-significant findings, etc.)

Coding Data for Analysis

Chart used to collect information about a study for analysis. Categories include study design, outcomes, assessment methods,etc.Prior to extracting data from articles that meet your eligibility criteria, you and your team should develop a codebook that clearly identifies all the data to be collected. This codebook can include brief explanations and other instructions to ensure consistency in data extraction.

It is helpful to conduct a pilot coding session to ensure that all coding variables are clearly defined and that all pertinent data is captured. During this pilot session, all data extractors should test this codebook on a sample of articles to see if the data is collected consistently and without confusion. 

Data should be extracted using some type of data collection form. Typically, this is an electronic form (e.g., Google Form, Qualtrics Survey, Microsoft Access), but paper forms can also be used. Electronic forms have the advantage of allowing easier data manipulation and analysis. Additionally, various data extraction software tools are available to manage extracted data from multiple reviewers.

Codebook example comes from J. January et al. (2018). Prevalence of depression and anxiety among undergraduate university students in low- and middle-income countries: A systematic review protocol. Systematic Reviews, 7(1)DOI:10.1186/s13643-018-0723-8 

Data Extraction Tools

Spreadsheets

You can use spreadsheet or database software to create custom extraction forms. Spreadsheet software (such as Microsoft Excel) has functions such as drop-down menus and range checks that can speed up the process and help prevent data entry errors.

Relational Databases

Relational databases (such as Microsoft Access) can help you extract information from different categories like citation details, demographics, participant selection, intervention, outcomes, etc.

Software

You can create custom forms with many different question types, such as multiple choice, dropdowns, ranking, and more. Content from these tools can often be exported to spreadsheet or database software.