Evidence map›Paper›PMID 38429798›Full record

ArticleSystematic reviews2024

The SAFE procedure: a practical stopping heuristic for active learning-based screening in systematic reviews and meta-analyses.

Josien Boetje, Rens van de Schoot

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Systematic reviews, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 21 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
72citing papers in PubMed, 21 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

72 citing papers in PubMed, 21 syntheses or guidelines pooled it.

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  7. Physiological Responses to Virtual Reality-Based Stress Regulation and Relaxation Interventions: A Systematic Review.Stress and health : journal of the International Society for the Investigation of Stress · 2026
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  13. Prevalence of Celiac Disease in Patients With Primary Biliary Cholangitis: A Systematic Review and Meta-Analysis.Liver international : official journal of the International Association for the Study of the Liver · 2025
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  14. A meta-analysis of the effectiveness of gratitude interventions on well-being across cultures.Proceedings of the National Academy of Sciences of the United States of America · 2025
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12 more citing papers are in PubMed but not listed here.

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

2 authors.

Josien BoetjeResearch Group Digital Ethics, Knowledge Center Learning and Innovation (LENI), Archimedes Institute, HU University of Applied Sciences Utrecht, Utrecht, the Netherlands. josien.boetje@hu.nl.ORCID 0000-0003-1542-6672
Rens van de SchootDepartment of Methodology and Statistics, Faculty of Social and Behavioral Sciences, Utrecht University, Utrecht, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Active learning has become an increasingly popular method for screening large amounts of data in systematic reviews and meta-analyses. The active learning process continually improves its predictions on the remaining unlabeled records, with the goal of identifying all relevant records as early as possible. However, determining the optimal point at which to stop the active learning process is a challenge. The cost of additional labeling of records by the reviewer must be balanced against the cost of erroneous exclusions. This paper introduces the SAFE procedure, a practical and conservative set of stopping heuristics that offers a clear guideline for determining when to end the active learning process in screening software like ASReview. The eclectic mix of stopping heuristics helps to minimize the risk of missing relevant papers in the screening process. The proposed stopping heuristic balances the costs of continued screening with the risk of missing relevant records, providing a practical solution for reviewers to make informed decisions on when to stop screening. Although active learning can significantly enhance the quality and efficiency of screening, this method may be more applicable to certain types of datasets and problems. Ultimately, the decision to stop the active learning process depends on careful consideration of the trade-off between the costs of additional record labeling against the potential errors of the current model for the specific dataset and context.

Indexed as

HeuristicsProblem-Based LearningHumansSoftwareSystematic Reviews as TopicActive learningMachine learningMeta-analysisMethodologyScreening prioritizationStopping heuristicStopping ruleSystematic review

Identifiers

PMID38429798
PMCPMC10908130

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.