Evidence map›Paper›PMID 41963762›Full record

ReviewCanadian journal of anaesthesia = Journal canadien d'anesthesie2026

Data sharing statements in five high-impact anesthesiology journals (2020-2023): a cross-sectional study.

Tag Harris, Bryce Sanchez, Alex Hagood, Annes Elfar, Jacob Duncan, Taylor Gardner, Eli Paul, Chase Ladd, Alicia Ito Ford, Matt Vassar

Abstract readReview
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In one paragraph

Review in Canadian journal of anaesthesia = Journal canadien d'anesthesie, 2026. 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

10 authors.

Tag HarrisOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, Tulsa, OK, USA. tagharr17@gmail.com.ORCID 0009-0003-7979-5343
Bryce SanchezOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, Tulsa, OK, USA.
Alex HagoodOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, Tulsa, OK, USA.
Annes ElfarOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, Tulsa, OK, USA.
Jacob DuncanOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, Tulsa, OK, USA.
Taylor GardnerOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, Tulsa, OK, USA.
Eli PaulOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, Tulsa, OK, USA.
Chase LaddDepartment of Anesthesiology, Detroit Medical Center, Detroit, MI, USA.
Alicia Ito FordOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, Tulsa, OK, USA.
Matt VassarOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, Tulsa, OK, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIn this study, we sought to evaluate the presence, quality, and accessibility of data sharing statements (DSS) in research articles published in five high-impact anesthesiology journals from 2020 to 2023. Data sharing is foundational to research transparency and reproducibility. As anesthesiology evolves, understanding how DSS are implemented in selected high-impact journals can inform open science efforts within anesthesiology research.

methodsWe conducted a cross-sectional study of five top-ranked anesthesiology journals selected using 2023 Clarivate Journal Impact Factor (JIF) rankings. Eligible studies (2020-2023) were screened in duplicate using Rayyan, and data were extracted using a structured Google Form. We used a large language model (ChatGPT, GPT-4) to aid in the exploratory thematic development of DSS, with manual validation by investigators.

resultsAmong 1,123 included articles, DSS prevalence varied by journal and year. In Anaesthesia, Critical Care & Pain Medicine, articles with DSS increased from 15% (4/26) in 2020 to 30% (9/30) in 2023, whereas the prevalence of DSS remained below 8% in Anesthesia & Analgesia. Government-funded studies were more likely to include DSS (β = 0.734, P = 0.047), while higher JIF was negatively associated with DSS inclusion (β = -0.298, P = 0.008). Thematic analysis showed "Conditional Data Availability" was the most frequent DSS type (74%). Of authors contacted, 28% responded, and 14% ultimately agreed to share data for replication.

conclusionsWe found that DSS were underused in leading anesthesiology journals. Strengthening journal policies, funder mandates, and education on data sharing practices may promote greater transparency in anesthesia research. Because our analysis focused on a limited sample of journals, findings may not be generalizable to the entire field of anesthesiology.

Indexed as

AnesthesiologyInformation DisseminationPeriodicals as TopicCross-Sectional StudiesHumansJournal Impact FactorLarge Language ModelsReproducibility of Resultsanesthesiologydata sharingdata sharing statementsmeta-researchtransparency

Identifiers

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.