Systematic Reviews & Meta-analyses: Data
Extraction

Guidance on conducting systematic reviews and meta-analyses.

Consultations

Request a consultation:

  • Email: srconsultation-g@vt.edu
  • In your email, let us know your current project research focus, planning stage, timeline, and goals. 

Cozette Comer, Evidence Synthesis Librarian, Liaison Librarian: Statistics and Computational Modeling & Data Analytics, cozette@vt.edu

Kiri DeBose, Head, Veterinary Medicine Library & Liaison to Animal Sciences, kdebose@vt.edu

Ginny Pannabecker, Liaison Librarian: Biochemistry, Biocomplexity Institute, Biological Sciences, Biomedical Engineering and Mechanics, Neuroscience, and Systems Biology; Director, RCE, vpannabe@vt.edu

Data Extraction

At a minimum, Data Extraction includes: Study Characteristics; with particular detail related to characteristics, Outcome Measures of interest, and Results that you may use in data synthesis.

Data Extraction Planning:

  • Develop and pilot test a form for data extraction to:
    • Ensure that you are including a prompt to pull information you will need to describe the studies and for data synthesis/analysis
    • Test and ensure inter-rater reliability in extracting data from studies 

Data Extraction Elements:

  • Consider your research question components and objectives
  • Consider your study eligibility (inclusion / exclusion) criteria
  • Study characteristics - This information, or a summarized version will form a preliminary table summarizing all included studies, titled as (or similar to): TABLE 1 - Study Characteristics. Examples of characteristics included:
    • Full citation 
    • Location
    • Duration
    • Objectives
    • Intervention / object of study
    • Study Design and Methodology
    • Outcome Measures
    • Results