Data Collection/Extraction

A data extraction form should be developed early in the review planning process using the research question and inclusion criteria to customize the form to meet the needs of the project. Carefully and thoroughly extract all relevant information from studies to be included in your systematic review. Relevant information will depend on the research question and and whether you are using quantitative or qualitative information, and/or the conventions of the journal to which you will submit for publication. The information extracted will predominantly relate to your study inclusion criteria; and may cover definition or conceptualization, measures/key variables, research design, participants, year of publication, data/results, study design, study setting, etc. (Siddaway et al., 2019).

Commonly extracted fields for SRs include:

• Article citation with corresponding author
• Study characteristics such as study type/research design
• Year of publication
• Participant characteristics
• Interventions and study setting
• Outcome data & results

A Practical Guide to Data Extraction for Intervention Systematic Reviews This guide from Covidence can help streamline your data extraction processes, avoid unnecessary work, and deliver high-quality outcomes, regardless of which data extraction tool you are using. It offers definitions, practical advice, links to the Cochrane Handbook, downloadable templates, and real-world examples from studies. Diagrams and illustrations courtesy of Covidence: https://www.covidence.org/resource/data-extraction-for-intervention-systematic-reviews/

Building an Evidence Table Tips from Rutgers University Libraries.

Data Extraction & Management Tools

More Resources:

Büchter, R.B., Weise, A., & Pieper, D. (2020).  Development, testing and use of data extraction forms in systematic reviews: a review of methodological guidance. BMC Medical Research Methodology, 20(1), 1-14. https://doi.org/10.1186/s12874-020-01143-3

Aromataris E, Munn Z, (Eds.).(2020). JBI manual for evidence synthesis. JBI. https://doi.org/10.46658/JBIMES-20-01 See 11.2.7 Data extraction

Li, T., Higgins, J.P.T., & Deeks, J.J. (2023). Chapter 5: Collecting data. In J.P.T. Higgins, J. Thomas, J. Chandler, M. Cumpston, T. Li, M.J. Page, & V.A. Welch (Eds.), Cochrane handbook for systematic reviews of interventions. Cochrane.

Pollock, D., Peters, M. D. J., Khalil, H., McInerney, P., Alexander, L., Tricco, A. C., Evans, C., de Moraes, É. B., Godfrey, C. M., Pieper, D., Saran, A., Stern, C., & Munn, Z. (2023). Recommendations for the extraction, analysis, and presentation of results in scoping reviews. JBI evidence synthesis, 21(3), 520–532. https://doi.org/10.11124/JBIES-22-00123

Siddaway, A. P., Wood, A. M., & Hedges, L. V. (2019). How to do a systematic review: a best practice guide for conducting and reporting narrative reviews, meta-analyses, and meta-syntheses. Annual Review of Psychology, 70(1), 747-770.

Taylor, K. S., Mahtani, K. R., & Aronson, J. K. (2021). Summarising good practice guidelines for data extraction for systematic reviews and meta-analysis. BMJ Evidence-Based Medicine, 26(3), 88-90. http://dx.doi.org/10.1136/bmjebm-2020-111651

Wilson, P. M., Farley, K., Bickerdike, E. C., Booth, A. M., Chambers, D., Lambert, M., Thompson, C., Turner, R. & Watt, I. S. (2017). Effects of a demand-led evidence briefing service on the uptake and use of research evidence by commissioners of health services: A controlled before-and-after study. Health Services and Delivery Research, 5(5). See Appendix 2, Example data extraction form for systematic reviews.