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1. Copyright © 2021 pubrica. All rights reserved 1
How to Conduct Abstract Screening for
Systemic Review- From Beginning to End
Dr. Nancy Agnes, Head, Technical Operations, Pubrica, sales@pubrica.com
In brief
Abstract screening is an integral part of doing an
efficient and thorough systematic examination. The
necessary first step in synthesizing the existing
literature is abstract scanning, which helps the review
team narrow down the vast amalgamation of citations
found across academic libraries to the citations that
should be “full text” screened and ultimately used in
the review(1)
.
I. INTRODUCTION
Conducting a thorough analysis, no matter how big or
small, necessitates meticulous preparation, meticulous
data recording, and continuous administrative
supervision. 1 A high-quality analysis depends on the
experience of a group of material and methodological
members, as well as information gained from previous
reviews.Identifying studies suitable for evaluating and
screening these studies to identify others eligible for
review is a major activity of a systematic review. A
high-quality systematic analysis requires searching for
and finding a wide variety of research.
In the social sciences, systematic analysis teams face
difficulty in that certain study issues cross academic
lines, necessitating multiple disciplinary and cross-
sectional datasets to search for applicable findings.
Domain searches yielding over 5000 results are
common in psychology, education, criminal justice, and
medicine (2)
.
Table 1: Abstract screening process, for example, study

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Table 1 summarises a synthesis of course instructions,
expert discussions, and practical practice undertaking or
engaging in various large-evidence systematic reviews.
II. BEFORE SCREENING BEGINS
1. Create an abstract screening method for systematic
review with simple and concise queries. It should
include objects that are (a) factual, (b) “single-
barreled,” (c) have the same sentence structure, and (d)
accept yes/no/unsure responses.
It is the first of many recommendations for the
advancement of scanning and coding forms for
systematic analysis that have been made over the years.
The abstract screening method is dependent on the
study’s inclusion criterion, which should be used in an
analysis procedure created before the literature scan.
2. Ensure the abstract screening method is ordered
logically, with the simplest questions at the top.
Screening a vast number of research abstracts would be
a time-consuming process for review team members.
Abstract screeners naturally want to go as fast as
possible through the process and make assumptions on
each abstract. Their pace also leads to fatigue: less
fatigue means faster and more accurate abstract
scanning; everything is equivalent.
3. Conduct introductory abstract screening training in
which screeners are taught how to use the method and
are given 20 to 30 abstracts to screen. Repeat if
required before the team finds an agreement.
The abstract screening tool will be circulated to the
abstract screening team once it has been developed.
This team’s participants may or may not have prior
experience screening abstracts. Regardless of the team
members’ previous encounters, abstract screening
preparation is important (3)
.

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III. DURING ABSTRACT SCREENING
4. On a weekly or biweekly basis, meet with the
abstract screening team.
The abstract screening team can meet regularly or every
other week after the initial planning and piloting
meetings are completed, and the full team starts abstract
screening in earnest. These meetings aim to foster a
culture of debate, experimentation, and excitement
while also reducing “coder drift.”
5. Reduce the number of modifications to the screening
method.
As previously said, the abstract screening tool should
be piloted and updated at the start of the abstract
screening process. Explanations to the abstract
screening tool should be deemed necessary and
beneficial as more people scan abstracts and work in
the pilot round. Screeners of abstracts should feel free
to make improvements and call for clarification.
6. Make use of a text mining abstract screening
programme.
Traditional abstract screening lists all citations for
screening using reference management software (such
as EndNote or Zotero) or simple spreadsheets. After
that, the abstracts are screened in the order in which
they were downloaded from database searches. The first
abstract screened is likely the last abstract to be kept for
full-text screening.
7. Each abstract must be double-screened
independently.
Double-screening all available abstracts isn’t a new
concept; it’s been recommended as best practice for
decades. Single screening has the power to rule out
trials until they have been thoroughly vetted. It’s just
too quick to make a blunder and lose a report.
8. Disagreements can be resolved in the abstract
screening period.
Screening disputes can arise no matter how successful
the screening method is or how often the abstract
screening committee meets. These are often the result
of mere human error; other times, they result
from“coder drift” or other structural problems.
9. Encourage screeners by limiting time on task,
promoting intellectual buy‐in, and providing
incentives.
As previously said, abstract screening is a thankless and
time-consuming process. As a result, analysis
supervisors, like managers in other industries, must
work diligently to keep abstract screeners motivated to
continue screening on schedule and effectively (4)
.
IV. AFTER SCREENING ENDS
10. Analyze the process and decisions after screening
has been completed.
The abstract scanning process culminates in a
spreadsheet of decisions for each citation found.
Completing abstract screening, particularly for massive
proof programmes, may feel like a significant
achievement (5)
.
V. CONCLUSION
The purpose of this paper was to include a collection of
realistic, abstract screening recommendations to
literature review teams and administrators of broad
evidence evaluations. Our instructions ensure that the
abstract screening process is completed quickly and
with the fewest possible mistakes.While we agree that
these recommendations should be made accessible to
the scientific community at large and that their use
would encourage successful research syntheses, further
research is needed to test our arguments (6)
.
REFERENCES
1. Chai, Kevin EK, et al. “Research Screener: a
machine learning tool to semi-automate abstract
screening for systematic reviews.” Systematic
reviews 10.1 (2021): 1-13.
2. Qin, Xuan, et al. “Natural language processing was
effective in assisting rapid title and abstract
screening when updating systematic
reviews.” Journal of Clinical Epidemiology 133
(2021): 121-129.
3. Wang, Zhen, et al. “Error rates of human reviewers
during abstract screening in systematic
reviews.” PloS one 15.1 (2020): e0227742.
4. Harrison, Hannah, et al. “Software tools to support
title and abstract screening for systematic reviews
in healthcare: an evaluation.” BMC medical
research methodology 20.1 (2020): 1-12.
5. Clark, Justin, et al. “A full systematic review was
completed in 2 weeks using automation tools: a
case study.” Journal of clinical epidemiology 121
(2020): 81-90.
6. Ritchie, Alison, et al. “Do randomized controlled
trials relevant to pharmacy meet best practice
standards for quality conduct and reporting? A

4. Copyright © 2021 pubrica. All rights reserved 2
systematic review.” International Journal of
Pharmacy Practice 28.3 (2020): 220-232.