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研究电子数据采集(REDCap)在序贯多重分配随机试验(SMART)中的应用:双随机化自动化的实例

Use of research electronic data capture (REDCap) in a sequential multiple assignment randomized trial (SMART): A practical example of automating double randomization.

作者信息

Lee Carol A, Gamino Danilo, Lore Michelle, Donelson Curt, Windsor Liliane C

机构信息

Addiction Center, University of Michigan, North Campus Research Complex Building 16, 2800 Plymouth Rd., Ann Arbor, MI 48109, USA.

North Jersey Community Research Initiative, 393 Central Ave., Newark, NJ 07103.

出版信息

Res Sq. 2023 Feb 24:rs.3.rs-2573133. doi: 10.21203/rs.3.rs-2573133/v1.

Abstract

Adaptive interventions are often used in individualized health care to meet the unique needs of clients. Recently, more researchers have adopted the Sequential Multiple Assignment Randomized Trial (SMART), a type of research design, to build optimal adaptive interventions. SMART requires research participants to be randomized multiple times over time, depending upon their response to earlier interventions. Despite the increasing popularity of SMART designs, conducting a successful SMART study poses unique technological and logistical challenges (e.g., effectively concealing and masking allocation sequence to investigators, involved health care providers, and subjects) in addition to other challenges common to all study designs (e.g., study invitations, eligibility screening, consenting procedures, and data confidentiality protocols). Research Electronic Data Capture (REDCap) is a secure, browser-based web application widely used by researchers for data collection. REDCap offers unique features that support researchers’ ability to conduct rigorous SMARTs. This manuscript provides an effective strategy for performing automatic double randomization for SMARTs using REDCap. Between January and March 2022, we conducted a SMART using a sample of adult (age 18 and older) New Jersey residents to optimize an adaptive intervention to increase COVID-19 testing uptake. In the current report, we discuss how we used REDCap for our SMART, which required double randomization. Further, we share our REDCap project XML file for future investigators to use when designing and conducting SMARTs. We report on the randomization feature that REDCap offers and describe how the study team automated an additional randomization that was required for our SMART. An application programming interface was used to automate the double randomizations in conjunction with the randomization feature provided by REDCap. REDCap offers powerful tools to facilitate the implementation of longitudinal data collection and SMARTs. Investigators can make use of this electronic data capturing system to reduce errors and bias in the implementation of their SMARTs by automating double randomization. The SMART study was prospectively registered at Clinicaltrials.gov; registration number: NCT04757298, date of registration: 17/02/2021. Keywords: Research Electronic Data Capture (REDCap), randomized controlled trials (RCT), adaptive interventions, Sequential Multiple Assignment Randomized Trial (SMART), randomization, experimental design, reducing human errors, automation.

摘要

适应性干预措施常用于个性化医疗保健,以满足客户的独特需求。最近,越来越多的研究人员采用了序贯多重分配随机试验(SMART)这种研究设计类型,来构建最佳的适应性干预措施。SMART要求研究参与者根据他们对早期干预措施的反应,在一段时间内多次进行随机分组。尽管SMART设计越来越受欢迎,但除了所有研究设计都面临的其他挑战(如研究邀请、资格筛选、同意程序和数据保密协议)之外,开展一项成功的SMART研究还存在独特的技术和后勤挑战(例如,有效地向研究人员、相关医疗保健提供者和受试者隐瞒和掩盖分配序列)。研究电子数据采集(REDCap)是一种安全的、基于浏览器的网络应用程序,被研究人员广泛用于数据收集。REDCap提供了独特的功能,支持研究人员开展严格的SMART研究。本手稿提供了一种使用REDCap对SMART进行自动双重随机化的有效策略。在2022年1月至3月期间,我们对新泽西州成年(18岁及以上)居民样本进行了一项SMART研究,以优化一种适应性干预措施,提高新冠病毒检测的接受度。在本报告中,我们讨论了如何将REDCap用于我们需要双重随机化的SMART研究。此外,我们分享我们的REDCap项目XML文件,供未来的研究人员在设计和开展SMART研究时使用。我们报告了REDCap提供的随机化功能,并描述了研究团队如何自动进行我们的SMART研究所需的额外随机化。使用了一个应用程序编程接口,结合REDCap提供的随机化功能,实现双重随机化的自动化。REDCap提供了强大的工具,以促进纵向数据收集和SMART研究的实施。研究人员可以利用这个电子数据采集系统,通过自动双重随机化来减少他们的SMART研究实施过程中的错误和偏差。该SMART研究已在Clinicaltrials.gov上进行前瞻性注册;注册号:NCT04757298,注册日期:2021年2月17日。关键词:研究电子数据采集(REDCap)、随机对照试验(RCT)、适应性干预、序贯多重分配随机试验(SMART)、随机化、实验设计、减少人为错误、自动化

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cb9/9980278/d236637a82ad/nihpp-rs2573133v1-f0001.jpg

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