Evidence map›Paper›PMID 34631024›Full record

ArticleF1000Research2021

Rates and predictors of data and code sharing in the medical and health sciences: Protocol for a systematic review and individual participant data meta-analysis.

Daniel G Hamilton, Hannah Fraser, Fiona Fidler, Steve McDonald, Anisa Rowhani-Farid, Kyungwan Hong, Matthew J Page

Abstract read
In one paragraph

Article in F1000Research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

7 authors.

Daniel G HamiltonMetaMelb Research Group, School of BioSciences, University of Melbourne, Parkville, Victoria, 3010, Australia.ORCID 0000-0001-8104-474X
Hannah FraserMetaMelb Research Group, School of BioSciences, University of Melbourne, Parkville, Victoria, 3010, Australia.
Fiona FidlerMetaMelb Research Group, School of BioSciences, University of Melbourne, Parkville, Victoria, 3010, Australia.
Steve McDonaldSchool of Public Health & Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia.ORCID 0000-0003-2832-5205
Anisa Rowhani-FaridDepartment of Pharmaceutical Health Services Research, University of Maryland, Baltimore, Maryland, 21201, USA.
Kyungwan HongDepartment of Pharmaceutical Health Services Research, University of Maryland, Baltimore, Maryland, 21201, USA.
Matthew J PageSchool of Public Health & Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia.ORCID 0000-0002-4242-7526

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Numerous studies have demonstrated low but increasing rates of data and code sharing within medical and health research disciplines. However, it remains unclear how commonly data and code are shared across all fields of medical and health research, as well as whether sharing rates are positively associated with implementation of progressive policies by publishers and funders, or growing expectations from the medical and health research community at large. Therefore this systematic review aims to synthesise the findings of medical and health science studies that have empirically investigated the prevalence of data or code sharing, or both. Objectives include the investigation of: (i) the prevalence of public sharing of research data and code alongside published articles (including preprints), (ii) the prevalence of private sharing of research data and code in response to reasonable requests, and (iii) factors associated with the sharing of either research output (e.g., the year published, the publisher's policy on sharing, the presence of a data or code availability statement). It is hoped that the results will provide some insight into how often research data and code are shared publicly and privately, how this has changed over time, and how effective some measures such as the institution of data sharing policies and data availability statements have been in motivating researchers to share their underlying data and code.

Indexed as

Information DisseminationPublicationsData AnalysisHumansMeta-Analysis as TopicResearch PersonnelSystematic Reviews as TopicCode sharingData sharingHealth sciencesMedicineMeta-analysisSystematic review

Identifiers

PMID34631024
PMCPMC8485098

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.