Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical example

Abstract 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...

Full description

Bibliographic Details
Main Authors: Sina Kianersi, Maya Luetke, Christina Ludema, Alexander Valenzuela, Molly Rosenberg
Format: Article
Language:English
Published: BMC 2021-08-01
Series:BMC Medical Research Methodology
Subjects:
RCT
Online Access:https://doi.org/10.1186/s12874-021-01362-2
id doaj-cba60db819e5465480355c85e8061a54
record_format Article
spelling doaj-cba60db819e5465480355c85e8061a542021-08-22T11:44:22ZengBMCBMC Medical Research Methodology1471-22882021-08-012111910.1186/s12874-021-01362-2Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical exampleSina Kianersi0Maya Luetke1Christina Ludema2Alexander Valenzuela3Molly Rosenberg4Department of Epidemiology and Biostatistics, Indiana University School of Public Health-BloomingtonDepartment of Epidemiology and Biostatistics, Indiana University School of Public Health-BloomingtonDepartment of Epidemiology and Biostatistics, Indiana University School of Public Health-BloomingtonAssociate Application Administrator, REDCap, Advanced Biomedical IT Core, UITS Research Technologies, Indiana UniversityDepartment of Epidemiology and Biostatistics, Indiana University School of Public Health-BloomingtonAbstract 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.https://doi.org/10.1186/s12874-021-01362-2REDCapRCTRandomized controlled trialsRandomizationRisk of bias
collection DOAJ
language English
format Article
sources DOAJ
author Sina Kianersi
Maya Luetke
Christina Ludema
Alexander Valenzuela
Molly Rosenberg
spellingShingle Sina Kianersi
Maya Luetke
Christina Ludema
Alexander Valenzuela
Molly Rosenberg
Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical example
BMC Medical Research Methodology
REDCap
RCT
Randomized controlled trials
Randomization
Risk of bias
author_facet Sina Kianersi
Maya Luetke
Christina Ludema
Alexander Valenzuela
Molly Rosenberg
author_sort Sina Kianersi
title 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_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_sort use of research electronic data capture (redcap) in a covid-19 randomized controlled trial: a practical example
publisher BMC
series BMC Medical Research Methodology
issn 1471-2288
publishDate 2021-08-01
description Abstract 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.
topic REDCap
RCT
Randomized controlled trials
Randomization
Risk of bias
url https://doi.org/10.1186/s12874-021-01362-2
work_keys_str_mv AT sinakianersi useofresearchelectronicdatacaptureredcapinacovid19randomizedcontrolledtrialapracticalexample
AT mayaluetke useofresearchelectronicdatacaptureredcapinacovid19randomizedcontrolledtrialapracticalexample
AT christinaludema useofresearchelectronicdatacaptureredcapinacovid19randomizedcontrolledtrialapracticalexample
AT alexandervalenzuela useofresearchelectronicdatacaptureredcapinacovid19randomizedcontrolledtrialapracticalexample
AT mollyrosenberg useofresearchelectronicdatacaptureredcapinacovid19randomizedcontrolledtrialapracticalexample
_version_ 1721199474241437696