Course
Systematic approaches to reviewing literature - 4 ECTS
Introduction & objectives of the course
Systematic approaches are increasingly expected in all reviews. This course takes the principles of systematic review, as created for evidence in clinical medicine, and guides participants as they adapt them for application in their own often inter-disciplinary review.
Types of research questions supported:
- What is the evidence on (insert topic)?
- What models/theories are used to study (insert interest)?
- How does the literature understand (insert concept)?
- How is (concept) measured?
- What is known about…?
- What works?
- How is (insert any topic of interest) reported?
This course is spread over a 4 to 6 week period so that participants are able to learn about, adapt and then go through each of
the stages of a review. Specifically:
- Scoping: Identification of a doable and appropriate problem within your study
- Research question: Creating a research question that fits both your study and the requirements of review
- Review design: Deciding which type of review best fits you purposes
- Retrieval: Finding and retrieving records using databases, pearl gathering, network and other manual and automated retrieval methods
- Screening: Human and (semi) automated methods for retrieving records
- Assessment: Deciding on and implementing both manual and (semi) automated assessment strategies
- Analysis: Identification and retrieval of relevant information from records using manual and (semi) automated methods
- Synthesis: Choice and implementation of an appropriate synthesis method
- Reporting: Fitting your report for publication in a target journal
Participants will be introduced to a number of tools to support review. This will include software to enable workflow management, retrieval, screening, extraction of relevant information from records and analysis. Participants would benefit from a basic understanding in Python. Participants who intend meta-analysis should be familiar with R, those who intend a more narrative of qualitative analysis would be helped by familiarity with Atlas.ti.
Programme
Preparatory assignment (approx. 20 hours total effort)
Identification of a problem in your project appropriate for review, initial selection of a type of review, initial proposal of a research question (approx. 10 hours).
The preparatory assignment is submitted 2 days before the first session. It will be returned, with comments, at the start of the first session.
Day 1 (13.30-17.00) October 29:
Introduction to systematic review and its translation into other disciplines, refining questions, screening articles (manual and automated), software to support systematic review workflows, scoping of information retrieval (articles, underlying data, citation trails) and discussion of questions arising from the introductory exercise
Preparatory work: Revise the initial design of review and have a peer review prior to submission for the day in the library.
Day 2 (9.00-17.00) November 5:
Library session
A full day in the library learning about information retrieval and data management strategies.
Preparatory work: Screen articles using manual and automated methods. Finalise samples of articles to be analysed for your review. Read on and make an initial decision about the quality assessment methods you will use.
Submit choice of quality assessment method with justification prior to day three (approx. 20 hours).
Day 3 (13.30-17.00) November 19:
Discussion on quality assessment. Introduction of manual and (semi) automated ways to identify and extract relevant information.
Preparatory work: Refine methods and extract relevant information from a subset of records. Read on candidate analysis methods and make a final choice. Make an initial selection of target journals and identify expectations from scanning similar publications and guidelines for authors.
Submit chosen analysis method, justification for its selection and questions about your chosen method prior to day 4 (approx. 20 hours).
Day 4 (13.30-17.00) December 10:
Analysis and Reporting: Review and discuss submitted analysis methods. Review and discuss lessons learned from (semi) automated methods to identify and extract information. Lecture on reporting/archiving
Preparatory work: Prepare a rough draft of the final product. Share this product with a peer review. Accept review and revise your draft.
Submit draft prior to day 5. This draft should be reviewed by a peer and revised (approx. 20 hours).
Day 5 (13.30-17.00):
Participant presentations of lessons learned. Creation of a joint file containing key pointers for conducting a review.
NOTE: prior to each session participants submit questions that will be taken up in that class.
At the end of the course participants will have at least the skeleton of a publishable review in hand or a completely adequate tested protocol. They will know what is involved in conducting a review, they will know a number of different kinds of systematic review and they will know what machine learning tools are available and what they may offer and they will benefit from both the lessons they learned from their own experience and from that of their peers.
Schedule
| Session 1 | October 29 | afternoon |
| Session 2 | November 5 | full day |
| Session 3 | November 19 | afternoon |
| Session 4 | December 10 | afternoon |
| Session 5 | afternoon | |
Learning outcomes
After successful completion of this course, participants are expected to be able to:
why a systematic approach to reviewing literature in the social sciences is increasingly expected
- where in their PhD trajectory systematic reviews make sense
- which type of review is appropriate for each research question they have
- what time and resources each type of review will require
- what can and cannot claim to be known as the result of a given review
- how to design and, in the most practical terms, execute a review
Target group and min/max number of participants
This course is intended for PhD-candidates and postdocs designing a literature review; 10 min/20 max participants
Assumed prior knowledge
Library information literacy course or equivalent.
Course fee
| WGS PhDs with TSP | € 300 |
| a) All other PhD candidates b) Postdocs and staff of the above mentioned Graduate Schools | € 640 |
| All others | € 900 |
NB: for some courses, PhD candidates from other WUR graduate schools with a TSP are also entitled to a reduced fee. Please consult your Education/PhD Programme Coordinator for more information