Evidence map›Paper›PMID 36352397›Full record

SynthesisSystematic reviews2022

Characteristics and recovery methods of studies falsely excluded during literature screening-a systematic review.

Lisa Affengruber, Andreea Dobrescu, Emma Persad, Irma Klerings, Gernot Wagner, Isolde Sommer, Gerald Gartlehner

Abstract readSystematic Review
In one paragraph

Synthesis in Systematic reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Lisa AffengruberDepartment for Evidence-Based Medicine and Evaluation, Cochrane Austria, Danube University Krems, Dr. Karl Dorrek Strasse 30, 3500, Krems, Austria. lisa.affengruber@donau-uni.ac.at.ORCID 0000-0002-7721-8732
Andreea DobrescuDepartment for Evidence-Based Medicine and Evaluation, Cochrane Austria, Danube University Krems, Dr. Karl Dorrek Strasse 30, 3500, Krems, Austria.
Emma PersadDepartment for Evidence-Based Medicine and Evaluation, Cochrane Austria, Danube University Krems, Dr. Karl Dorrek Strasse 30, 3500, Krems, Austria.
Irma KleringsDepartment for Evidence-Based Medicine and Evaluation, Cochrane Austria, Danube University Krems, Dr. Karl Dorrek Strasse 30, 3500, Krems, Austria.
Gernot WagnerDepartment for Evidence-Based Medicine and Evaluation, Cochrane Austria, Danube University Krems, Dr. Karl Dorrek Strasse 30, 3500, Krems, Austria.
Isolde SommerDepartment for Evidence-Based Medicine and Evaluation, Cochrane Austria, Danube University Krems, Dr. Karl Dorrek Strasse 30, 3500, Krems, Austria.
Gerald GartlehnerDepartment for Evidence-Based Medicine and Evaluation, Cochrane Austria, Danube University Krems, Dr. Karl Dorrek Strasse 30, 3500, Krems, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDue to the growing need to provide evidence syntheses under time constraints, researchers have begun focusing on the exploration of rapid review methods, which often employ single-reviewer literature screening. However, single-reviewer screening misses, on average, 13% of relevant studies, compared to 3% with dual-reviewer screening. Little guidance exists regarding methods to recover studies falsely excluded during literature screening. Likewise, it is unclear whether specific study characteristics can predict an increased risk of false exclusion. This systematic review aimed to identify supplementary search methods that can be used to recover studies falsely excluded during literature screening. Moreover, it strove to identify study-level predictors that indicate an elevated risk of false exclusions of studies during literature screening.

methodsWe performed literature searches for eligible studies in MEDLINE, Science Citation Index Expanded, Social Sciences Citation Index, Current Contents Connect, Embase, Epistemonikos.org, and Information Science & Technology Abstracts from 1999 to June 23, 2020. We searched for gray literature, checked reference lists, and conducted hand searches in two relevant journals and similar article searches current to January 28, 2021. Two investigators independently screened the literature; one investigator performed the data extraction, and a second investigator checked for correctness and completeness. Two reviewers assessed the risk of bias of eligible studies. We synthesized the results narratively.

resultsThree method studies, two with a case-study design and one with a case-series design, met the inclusion criteria. One study reported that all falsely excluded publications (8%) could be recovered through reference list checking compared to other supplementary search methods. No included methods study analyzed the impact of recovered studies on conclusions or meta-analyses. Two studies reported that up to 8% of studies were falsely excluded due to uninformative titles and abstracts, and one study showed that 11% of non-English studies were falsely excluded.

conclusionsDue to the limited evidence based on two case studies and one case series, we can draw no firm conclusion about the most reliable and most valid method to recover studies falsely excluded during literature screening or about the characteristics that might predict a higher risk of false exclusion. SYSTEMATIC REVIEW REGISTRATION: https://osf.io/v2pjr/.

Indexed as

Mass ScreeningHumansMEDLINEFalsely excluded studiesRapid reviewSingle screeningSystematic review

Identifiers

PMID36352397
PMCPMC9644550

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.