Evidence map›Paper›PMID 40348959›Full record

ArticleBMC medical research methodology2025

Data sharing practices in high-impact rehabilitation journals.

Ahmed Elghzali, Daniel Molina, Mahad Chaudhry, Jacob Duncan, Annes Elfar, Eli Oldham, Brody Dennis, Eli Paul, Alicia Ito Ford, Matt Vassar

Abstract read
In one paragraph

Article in BMC medical research methodology, 2025. 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.

Ahmed ElghzaliOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, 1111 W 17 St, Tulsa, OK, 74107, USA. ahmed.elghzali.research@gmail.com.
Daniel MolinaOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, 1111 W 17 St, Tulsa, OK, 74107, USA.
Mahad ChaudhryOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, 1111 W 17 St, Tulsa, OK, 74107, USA.
Jacob DuncanOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, 1111 W 17 St, Tulsa, OK, 74107, USA.
Annes ElfarOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, 1111 W 17 St, Tulsa, OK, 74107, USA.
Eli OldhamOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, 1111 W 17 St, Tulsa, OK, 74107, USA.
Brody DennisOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, 1111 W 17 St, Tulsa, OK, 74107, USA.
Eli PaulOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, 1111 W 17 St, Tulsa, OK, 74107, USA.
Alicia Ito FordOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, 1111 W 17 St, Tulsa, OK, 74107, USA.
Matt VassarOffice of Medical Student Research, Oklahoma State University Center for Health Sciences, 1111 W 17 St, Tulsa, OK, 74107, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe demand for rehabilitation services is rising due to the aging population and increasing number of chronic conditions. High-quality research is essential to address these challenges, with recent mandates emphasizing the importance of data sharing for transparency and reproducibility. However, data sharing remains limited across clinical research. Data sharing statements (DSS) have been proposed to improve accessibility, but their implementation and effectiveness in rehabilitation research remain unclear. We aim to identify barriers and guide future policies for standardizing data sharing in the field of rehabilitation.

methodsOn June 6th, 2024, a PubMed/MEDLINE search identified clinical studies from five top rehabilitation journals based on impact factor. We extracted DSS and general characteristics in a duplicated and masked fashion to identify influential factors on DSS inclusion and then used a hierarchical logistic regression and thematic analysis. Email requests were sent to authors to verify their willingness to share data.

resultsOf 1,278 studies that underwent data extraction, 25.5% of studies in our sample featured a DSS; however, this figure was significantly influenced by one journal with a 99% inclusion rate, while the other four journals collectively had only a 5% rate. Further analysis of 314 DSS revealed the majority designated a gatekeeper role for handling data requests. After emailing authors to verify their commitment to the reported DSS, only 22.7% adhered to them.

conclusionsOur study found substantial variation in DSS inclusion across rehabilitation journals, reflecting inconsistencies in how data sharing policies are implemented. We also identified a significant gap between stated data sharing intentions and actual author follow-through. These findings highlight the need for stronger accountability mechanisms. We recommend adopting the Transparency and Openness Promotion (TOP) to provide a framework for data sharing in the field of rehabilitation. Further standardization of DSS is needed, as alternative methods like data repositories have been shown to improve transparency and reproducibility.

trial registrationClinical trial number: not applicable.

Indexed as

Information DisseminationJournal Impact FactorPeriodicals as TopicRehabilitation ResearchHumansCross-Sectional AnalysisData SharingData Sharing StatementsRehabilitation

Identifiers

PMID40348959
PMCPMC12065141

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.