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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

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systematic review.” International Journal of

Pharmacy Practice 28.3 (2020): 220-232.