Evidence map›Paper›PMID 35571360›Full record

ArticleJAMIA open2022

Evaluation of publication type tagging as a strategy to screen randomized controlled trial articles in preparing systematic reviews.

Jodi Schneider, Linh Hoang, Yogeshwar Kansara, Aaron M Cohen, Neil R Smalheiser

Open access · goldAbstract read
In one paragraph

Article in JAMIA open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.3field-weighted citation impact, top 18% of its field
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

8 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Goals and strategies for the indexing of publication types and study designs.Database : the journal of biological databases and curation · 2026
    Article
  5. Article
  6. Publication Type Tagging using Transformer Models and Multi-Label Classification.medRxiv : the preprint server for health sciences · 2025
    Article
  7. Article
  8. Publication Type Tagging using Transformer Models and Multi-Label Classification.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024
    Article
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

5 authors at 2 institutions in 1 country.

Jodi SchneiderSchool of Information Sciences, University of Illinois Urbana-Champaign, Champaign, Illinois, USA.ORCID https://orcid.org/0000-0002-5098-5667
Linh HoangSchool of Information Sciences, University of Illinois Urbana-Champaign, Champaign, Illinois, USA.ORCID https://orcid.org/0000-0002-5565-1586
Yogeshwar KansaraSchool of Information Sciences, University of Illinois Urbana-Champaign, Champaign, Illinois, USA.ORCID https://orcid.org/0000-0002-3861-5540
Aaron M CohenDepartment of Medical Informatics and Clinical Epidemiology (DMICE), School of Medicine, Oregon Health & Science University, Portland, Oregon, USA.ORCID https://orcid.org/0000-0002-4610-9912
Neil R SmalheiserDepartment of Psychiatry, College of Medicine, University of Illinois Chicago, Chicago, Illinois, USA.ORCID https://orcid.org/0000-0003-1079-3406
University of Illinois Urbana-Champaign · USOregon Health & Science University · US

Funding

Text Mining Pipeline to Accelerate Systematic Reviews in Evidence-Based MedicineR01LM010817 · NLM · UNIVERSITY OF ILLINOIS AT CHICAGO · PI COHEN, AARON M., SMALHEISER, NEIL R · 2010 to 2019
$4.5M
NLM NIH HHS R01 LM010817
6 · The paper itself

Abstract

Objectives: To produce a systematic review (SR), reviewers typically screen thousands of titles and abstracts of articles manually to find a small number which are read in full text to find relevant articles included in the final SR. Here, we evaluate a proposed automated probabilistic publication type screening strategy applied to the randomized controlled trial (RCT) articles (i.e., those which present clinical outcome results of RCT studies) included in a corpus of previously published Cochrane reviews. Materials and Methods: We selected a random subset of 558 published Cochrane reviews that specified RCT study only inclusion criteria, containing 7113 included articles which could be matched to PubMed identifiers. These were processed by our automated RCT Tagger tool to estimate the probability that each article reports clinical outcomes of a RCT. Results: Removing articles with low predictive scores Discussion: This scenario, based on real SRs, demonstrates that automated tagging can identify RCT articles accurately while maintaining very high recall. However, we also found that even SRs whose inclusion criteria are restricted to RCT studies include not only clinical outcome articles per se, but a variety of ancillary article types as well. Conclusions: This encourages further studies learning how best to incorporate automated tagging of additional publication types into SR triage workflows.

Indexed as

information retrievalrandomized controlled trialsRCT Taggersystematic review automation

Identifiers

PMID35571360
PMCPMC9097760
OpenAlexW4220842251

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.