This document outlines the process for selecting eligible studies for a systematic literature review. It describes the main stages as screening the search output, assessing studies for eligibility by examining full texts, and extracting relevant data from included studies. Key steps involve removing duplicates, having two reviewers independently screen studies and resolve discrepancies, retrieving full texts of potentially eligible studies, and making final inclusion decisions based on pre-specified criteria. Maintaining clear documentation of decisions is important for transparency and reproducibility.
2. Learning outcomes
o Describe the main stages involved in selecting studies
o Apply inclusion criteria to assess eligibility of study abstracts
and full text articles
3. Influential decision
“Decisions about which studies to include and which data to
extract are among the most influential that are made in the
review process – but they involve judgement”
Higgins J et al. Chapter 7. Cochrane Handbook for Systematic
Reviews of Interventions. Wiley & Sons.
4. Valid & reliable data collection
What you need:-
Importance of clear, well-defined PICOS
Pre-specified, explicit, reproducible protocol
Measures to minimise bias and error
5. Steps
SCREEN SEARCH OUTPUT
Merge search output and remove duplicates
Identify studies that are potentially eligible for inclusion
ASSESS FOR ELIGIBILITY
Retrieve full texts of potentially eligible studies
Make decision to include studies by examining full texts
EXTRACT DATA
Extract data of interest to review question
6. Step 1 Merge search output and remove
duplicates
What you may have:-
• Large sample of records (100s, 1000s, 10,000s..!)
• Duplicate records
• You will hopefully include all eligible studies as well as many
studies that do not meet inclusion criteria
• ‘Small’ % eligible for inclusion
8. Removing duplicates
First merge all searches into a manageable format e.g.
EndNote database or Mendeley or other reference management software
Then can de-duplicate in two ways:
1. Using automated methods
2. Manually
Note even after this process there may still be ‘duplicate’
publications of very similar data by the same research group
so need to be careful to exclude before meta-analysis
9. Step 2 Identify studies that are potentially
eligible for inclusion -screening
inclusion (screening)
o Each record in the search output is examined
o ‘Mark’ records of studies which are judged to be potentially
eligible
o Be over-inclusive
o subset of original search output left
10. To minimize bias and error...
Two authors independently screen records
Software allows datasets to be merged and discrepancies identified -
DistillerSR
Discrepancies may result from either oversight or differences in
interpretation
Discrepancies resolved through discussion/ referral to 3rd author
Left with agreed subset of search output containing records of potentially
eligible studies
11. Step 3 Retrieve full texts of potentially
eligible studies
Aim to retrieve full texts of all potentially eligible studies
identified by screening
o Online
o Libraries
o Original authors
Labor intensive, time consuming
Cost
12. Step 4 Make decision to include studies by
examining full texts
Decide to include studies by assessing full texts against
PICOS
Only studies that meet all criteria will be included
Consider translation of foreign language articles (cost, how
much of article needs to be translated?)
13. Good record keeping is essential!
Document decisions
Decisions may be queried later
List of excluded studies with reason. It is a good idea to have a
hierarchy of reasons for exclusion, otherwise the different
reviewers may select different reasons
Complete PRISMA flow chart as you go
15. This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence.
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