Clinical trial transparency regulations: Implications to various scholarly publishing stakeholders
Abstract
Abstract As thousands of 2019 Corona virus disease (Covid-19) clinical trials are continuously getting added to various registries these days, good practices on data sharing and transparency have become one of the prime topics of discussion than ever before. Although trial registration is considered a crucial step, there is a lack of integration between registration and published literature. Trial outcomes are a matter of public interest, but sponsor compliances are not adequate with the recommended guidelines. Although the global recognition of data transparency increases day by day, there is still a long journey to travel. It is high time that scholarly publishing stakeholders should put in a collaborative effort to check author compliance. In this article, we aimed to comprehend and discuss the imperative roles of various scholarly publishing stakeholders in improving clinical trial transparency during this pandemic situation and highlight the changing paradigm towards the pressing need for reporting clinical trial data more effectively.
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Clear communication of data collection process may lead to privacy concerns.
“May lead to privacy concerns”
From AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications (2023) · cites this paper as [250]
Providing information on methods and data use increases data sharing and collaboration.
“Increases data sharing and collaboration”
From AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications (2023) · cites this paper as [250]
Providing information on methods and data use has difficulties in balancing transparency.
“Difficulties in balancing transparency”
From AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications (2023) · cites this paper as [250]
Clear communication of data collection process builds trust with data subjects.
“Builds trust with data subjects”
From AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications (2023) · cites this paper as [250]
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AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications
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- Authors
- Abdul Razack, H. I., Aranjani, J. M., & Mathew, S. T.
- Affiliations
- Faculty of Medicine & Health Sciences, University of Putra Malaysia , Serdang, Selangor 43400, Malaysia
- Manipal Academy of Higher Education (IN)
- Researcher & Medical Communications Expert , Flat No. 123, Mahaveer Rhyolite, Bengaluru, Karnataka 560076, India
- Corresponding author
- Mathew, Sam T
- Venue
- Science and Public Policy
- Publisher
- Oxford University Press (OUP)
- Published
- 2022-08-03
- Volume
- 49
- Issue
- 6
- Pages
- 951-961
- ISSN
- 0302-3427 (ISSN-L)
- 1471-5430
- OpenAlex
- W4289549996
- Cited by
- 3
- References
- 61
- Citations by year
- 2025: 1 · 2023: 2
- FWCI
- 0.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Science and Public Policy (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Academic Publishing and Open Access
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmaceutical industry and healthcare
- Keywords
- clinical trial transparency, clinical trial registration, data sharing, reporting guidelines, author compliance, COVID-19 clinical trials, clinical trial registries
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