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Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical example
BACKGROUND: Randomized controlled trials (RCT) are considered the ideal design for evaluating the efficacy of interventions. However, conducting a successful RCT has technological and logistical challenges. Defects in randomization processes (e.g., allocation sequence concealment) and flawed masking...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8380110/ https://www.ncbi.nlm.nih.gov/pubmed/34418958 http://dx.doi.org/10.1186/s12874-021-01362-2 |
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author | Kianersi, Sina Luetke, Maya Ludema, Christina Valenzuela, Alexander Rosenberg, Molly |
author_facet | Kianersi, Sina Luetke, Maya Ludema, Christina Valenzuela, Alexander Rosenberg, Molly |
author_sort | Kianersi, Sina |
collection | PubMed |
description | BACKGROUND: Randomized controlled trials (RCT) are considered the ideal design for evaluating the efficacy of interventions. However, conducting a successful RCT has technological and logistical challenges. Defects in randomization processes (e.g., allocation sequence concealment) and flawed masking could bias an RCT’s findings. Moreover, investigators need to address other logistics common to all study designs, such as study invitations, eligibility screening, consenting procedure, and data confidentiality protocols. Research Electronic Data Capture (REDCap) is a secure, browser-based web application widely used by researchers for survey data collection. REDCap offers unique features that can be used to conduct rigorous RCTs. METHODS: In September and November 2020, we conducted a parallel group RCT among Indiana University Bloomington (IUB) undergraduate students to understand if receiving the results of a SARS-CoV-2 antibody test changed the students’ self-reported protective behavior against coronavirus disease 2019 (COVID-19). In the current report, we discuss how we used REDCap to conduct the different components of this RCT. We further share our REDCap project XML file and instructional videos that investigators can use when designing and conducting their RCTs. RESULTS: We reported on the different features that REDCap offers to complete various parts of a large RCT, including sending study invitations and recruitment, eligibility screening, consenting procedures, lab visit appointment and reminders, data collection and confidentiality, randomization, blinding of treatment arm assignment, returning test results, and follow-up surveys. CONCLUSIONS: REDCap offers powerful tools for longitudinal data collection and conduct of rigorous and successful RCTs. Investigators can make use of this electronic data capturing system to successfully complete their RCTs. TRIAL REGISTRATION: The RCT was prospectively (before completing data collection) registered at ClinicalTrials.gov; registration number: NCT04620798, date of registration: November 9, 2020. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01362-2. |
format | Online Article Text |
id | pubmed-8380110 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-83801102021-08-23 Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical example Kianersi, Sina Luetke, Maya Ludema, Christina Valenzuela, Alexander Rosenberg, Molly BMC Med Res Methodol Research Article BACKGROUND: Randomized controlled trials (RCT) are considered the ideal design for evaluating the efficacy of interventions. However, conducting a successful RCT has technological and logistical challenges. Defects in randomization processes (e.g., allocation sequence concealment) and flawed masking could bias an RCT’s findings. Moreover, investigators need to address other logistics common to all study designs, such as study invitations, eligibility screening, consenting procedure, and data confidentiality protocols. Research Electronic Data Capture (REDCap) is a secure, browser-based web application widely used by researchers for survey data collection. REDCap offers unique features that can be used to conduct rigorous RCTs. METHODS: In September and November 2020, we conducted a parallel group RCT among Indiana University Bloomington (IUB) undergraduate students to understand if receiving the results of a SARS-CoV-2 antibody test changed the students’ self-reported protective behavior against coronavirus disease 2019 (COVID-19). In the current report, we discuss how we used REDCap to conduct the different components of this RCT. We further share our REDCap project XML file and instructional videos that investigators can use when designing and conducting their RCTs. RESULTS: We reported on the different features that REDCap offers to complete various parts of a large RCT, including sending study invitations and recruitment, eligibility screening, consenting procedures, lab visit appointment and reminders, data collection and confidentiality, randomization, blinding of treatment arm assignment, returning test results, and follow-up surveys. CONCLUSIONS: REDCap offers powerful tools for longitudinal data collection and conduct of rigorous and successful RCTs. Investigators can make use of this electronic data capturing system to successfully complete their RCTs. TRIAL REGISTRATION: The RCT was prospectively (before completing data collection) registered at ClinicalTrials.gov; registration number: NCT04620798, date of registration: November 9, 2020. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01362-2. BioMed Central 2021-08-21 /pmc/articles/PMC8380110/ /pubmed/34418958 http://dx.doi.org/10.1186/s12874-021-01362-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Kianersi, Sina Luetke, Maya Ludema, Christina Valenzuela, Alexander Rosenberg, Molly Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical example |
title | Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical example |
title_full | Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical example |
title_fullStr | Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical example |
title_full_unstemmed | Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical example |
title_short | Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical example |
title_sort | use of research electronic data capture (redcap) in a covid-19 randomized controlled trial: a practical example |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8380110/ https://www.ncbi.nlm.nih.gov/pubmed/34418958 http://dx.doi.org/10.1186/s12874-021-01362-2 |
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