Critical appraisal is the process of judging the validity and quality of a research paper.
Major points to consider when appraising systematic reviews include:
Is the study valid?
What are the results, and are they significant?
Are the results applicable?
Critical Appraisal Skills Programme (CASP)
Ten questions to help you make sense of a systematic review
AMSTAR 2
A critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both
STROBE
Designed for epidemiological studies
EQUATOR
Network listing over 300 sets of reporting guidlelines
Crowe, M., & Sheppard, L. (2011). A review of critical appraisal tools show they lack rigor: alternative tool structure is proposed. Journal of clinical epidemiology, 64(1), 78-89.
PRISMA checklist
Not a quality instrument but helpful for identifying elements to look for in a systematic review.
SPIRIT checklist
Not a quality instrument but helpful for identifying elements to look for in a systematic review.
Greenhalgh, T. (1997). The Medline database. BMJ, 315(7101), 180-183. Full Text
Greenhalgh, T. (1997). Getting your bearings (deciding what the paper is about). BMJ, 315(7102), 243-247. Full Text
Greenhalgh, T. (1997). Assessing the methodological quality of published papers. BMJ, 315(7103), 305-308. Full Text
Greenhalgh, T. (1997). Statistics for the non-statistician: different types of data need different statistical tests. BMJ, 315(7104), 364-366. Full Text
Greenhalgh, T. (1997). Statistics for the non-statistician. II:“Significant” relations and their pitfalls. BMJ, 315(7105), 422-425. Full Text
Greenhalgh, T. (1997). Papers that report drug trials. BMJ, 315(7106), 480-483. Full Text
Greenhalgh, T. (1997). Papers that report diagnostic or screening tests. BMJ, 315(7107), 540-543. Full Text
Greenhalgh, T. (1997). Papers that tell you what things cost (economic analyses). BMJ, 315(7108), 596-599. Full Text
Greenhalgh, T. (1997). Papers that summarise other papers (systematic reviews and meta-analyses). BMJ, 315(7109), 672-675 Full Text
Greenhalgh, T., & Taylor, R. (1997). Papers that go beyond numbers (qualitative research). BMJ, 315(7110), 740-743. Full Text
Data extraction is the process of transcribing information from the primary studies under review to a standard form or template that has been designed to capture all of the detail relevant to the meta-analysis.
Double data extraction is preferred for accuracy - this is when two researchers extract the data independently and discuss any discrepancies or consult a moderator to arrive at consensus.
Buscemi, N., Hartling, L., Vandermeer, B., Tjosvold, L., & Klassen, T. P. (2006). Single data extraction generated more errors than double data extraction in systematic reviews. Journal of clinical epidemiology, 59(7), 697-703. Full Text