What is a Literature Review?
A literature review discusses published information in a particular subject area, time period or research. It can be a simple summary of sources but usually combines a summary and a synthesis of material.
1. Define a topic and audience:
must be interesting to you
an important aspect of the field
a well-defined issue
2. Search and Re-Search the Literature:
3. Take NOTES while reading
4. Choose the type of review to write:
5. Keep the review focused, but broad interest. (could discuss other disciplines affected)
6. Be Critical and consistent:
A reader should have an idea of
- The major achievements in the reviewed field.
- The areas of debate.
- The outstanding research questions.
7. Find a logical structure.It can be helpful to use a mind-map to draw a conceptual scheme of the review
8. Make use of feedback. Can be peer-reviewed or someone reading a draft.
9. Include your own relevant research but be objective.
10. Be Up-to-date, do not forget older studies.
Original by Marco Pautasso. PLOS. July 2013, vol. 9, issue 7.
AVOID these traps:
Thank you to Susan Koskinen, email@example.com for sharing this material with Otterbein.
The problems addressed by the review should be in clear, structured questions. Once review questions have been set, modifications should be allowed only if alternative ways of defining the populations, interventions, outcomes or study designs become apparent.
Read review articles. The search for studies should be extensive. Multiple resources should be searched without language restrictions. The study selection criteria should flow directly from the review questions and be specified a priori. Reasons for inclusion and exclusion should be recorded.
Study quality assessment is relevant to every step of a review. Selected studies should get a critical appraisal and design-based quality checklists.
Data synthesis consists of study characteristics, quality and effects of statistical methods.
Be careful of bias, determine whether the overall summary can be trusted, and, if not, the effects observed in high-quality studies should be used for generating inferences.