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REDbox: a comprehensive semantic framework for data collection and management in tuberculosis research.

Authors :
Lima, Vinícius Costa
Rijo, Rui Pedro Charters Lopes
Bernardi, Filipe Andrade
Filho, Márcio Eloi Colombo
Barbosa-Junior, Francisco
Pellison, Felipe Carvalho
Galliez, Rafael Mello
Kritski, Afrânio Lineu
Alves, Domingos
Source :
Scientific Reports; 5/11/2023, Vol. 13 Issue 1, p1-14, 14p
Publication Year :
2023

Abstract

Clinical research outcomes depend on the correct definition of the research protocol, the data collection strategy, and the data management plan. Furthermore, researchers often need to work within challenging contexts, as is the case in tuberculosis services, where human and technological resources for research may be scarce. Electronic Data Capture Systems mitigate such risks and enable a reliable environment to conduct health research and promote result dissemination and data reusability. The proposed solution is based on needs pinpointed by researchers, considering the need for an accommodating solution to conduct research in low-resource environments. The REDbox framework was developed to facilitate data collection, management, sharing, and availability in tuberculosis research and improve the user experience through user-friendly, web-based tools. REDbox combines elements of the REDCap and KoBoToolbox electronic data capture systems and semantics to deliver new valuable tools that meet the needs of tuberculosis researchers in Brazil. The framework was implemented in five cross-institutional, nationwide projects to evaluate the users' perceptions of the system's usefulness and the information and user experience. Seventeen responses (representing 40% of active users) to an anonymous survey distributed to active users indicated that REDbox was perceived to be helpful for the particular audience of researchers and health professionals. The relevance of this article lies in the innovative approach to supporting tuberculosis research by combining existing technologies and tailoring supporting features. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20452322
Volume :
13
Issue :
1
Database :
Complementary Index
Journal :
Scientific Reports
Publication Type :
Academic Journal
Accession number :
163725436
Full Text :
https://doi.org/10.1038/s41598-023-33492-6