Evidence map›Paper›PMID 39619069›Full record

ArticleJournal of clinical and translational science2024

Clinical researchers' insights on key data for eligibility screening in clinical studies.

Betina Idnay, Emily R Gordon, Aubrey S Johnson, Jordan G Nestor, Karen Marder, Chunhua Weng

Abstract read
In one paragraph

Article in Journal of clinical and translational science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Betina IdnayDepartment of Biomedical Informatics, Columbia University, New York, NY, USA.ORCID https://orcid.org/0000-0002-4318-5987
Emily R GordonDepartment of Biomedical Informatics, Columbia University, New York, NY, USA.
Aubrey S JohnsonDepartment of Neurology, Columbia University, New York, NY, USA.
Jordan G NestorDepartment of Medicine, Columbia University, New York, NY, USA.
Karen MarderDepartment of Neurology, Columbia University, New York, NY, USA.
Chunhua WengDepartment of Biomedical Informatics, Columbia University, New York, NY, USA.

Funding

Training in Biomedical Informatics at Columbia UniversityT15LM007079 · NLM · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI NOEMIE ELHADAD, GEORGE M HRIPCSAK · 1992 to 2026
$28.9M
Digital Tools for Precision NephrologyK08DK138280 · NIDDK · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Jordan Gabriela Nestor · 2024 to 2026
$500k
NIDDK NIH HHS K08 DK138280NLM NIH HHS T15 LM007079
6 · The paper itself

Abstract

Introduction: Clinical research is critical for healthcare advancement, but participant recruitment remains challenging. Clinical research professionals (CRPs; e.g., clinical research coordinator, research assistant) perform eligibility prescreening, ensuring adherence to study criteria while upholding scientific and ethical standards. This study investigates the key information CRP prioritizes during eligibility prescreening, providing insights to optimize data standardization, and recruitment approaches. Methods: We conducted a freelisting survey targeting 150 CRPs from diverse domains (i.e., neurological disorders, rare diseases, and other diseases) where they listed essential information they look for from medical records, participant/caregiver inquiries, and discussions with principal investigators to determine a potential participant's research eligibility. We calculated the salience scores of listed items using Anthropac, followed by a two-level analytic procedure to classify and thematically categorize the data. Results: The majority of participants were female (81%), identified as White (44%) and as non-Hispanic (64.5%). The first-level analysis universally emphasized age, medication list, and medical history across all domains. The second-level analysis illuminated domain-specific approaches in information retrieval: for instance, history of present illness was notably significant in neurological disorders during participant and principal investigator inquiries, while research participation was distinctly salient in potential participant inquiries within the rare disease domain. Conclusion: This study unveils the intricacies of eligibility prescreening, with both universal and domain-specific methods observed. Variations in data use across domains suggest the need for tailored prescreening in clinical research. Incorporating these insights into CRP training and refining prescreening tools, combined with an ethical, participant-focused approach, can advance eligibility prescreening practices.

Indexed as

clinical researchclinical research staffeligibility prescreeningfreelistingInformatics

Identifiers

PMID39619069
PMCPMC11604510

What OpenQuestion holds

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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.