管理基于网络的调查欺诈的挑战和经验教训,以便在格鲁吉亚为影响联盟-社区参与联盟调查管理机构获得有效的外联和研究。

IF 3.5 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Leslie S Craig, Christina L Evans, Brittany D Taylor, Jace Patterson, Kaleb Whitfield, Mekhi Hill, Michelle Nwagwu, Mohamed Mubasher, Robert A Bednarczyk, Gail G McCray, Cheryl L R Gaddis, Natasha Taylor, Emily Thompson, Ursula Douglas, Saundra K Latimer, Sedessie G Spivey, Tabia Henry Akintobi, Rakale Collins Quarells
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引用次数: 0

摘要

背景:与基于网络的数据收集相关的便利性、隐私性和成本效益促进了最近基于网络的调查研究的扩展。然而,重要的是,对科学家和参与者来说,基于网络的调查研究的实际好处正在被可疑和欺诈性调查提交的急剧增加所掩盖。与调查欺诈相关的错误信息会损害数据质量和数据完整性,对科学结论、临床实践和社会效益产生重要影响。报告用于防止和管理可疑和欺诈性提交的方法的透明度是保护基于网络的调查数据真实性的关键;然而,关于在调查研究的各个阶段使用反欺骗策略来检测和消除低质量和欺诈反应的讨论有限。目的:本研究旨在通过描述佐治亚州影响联盟-社区参与联盟(Georgia CEAL)针对COVID-19差异项目调查中基于网络管理的研究设计策略和反欺骗工具,为与基于网络的调查研究相关的数据完整性威胁提供不断发展的证据基础。方法:为应对COVID-19大流行以及对快速、有效、社区知情和社区拥有的研究的需求,以指导有针对性地应对动态的公共卫生危机,建立了GEORGIA CEAL。GEORGIA CEAL调查I(2021年4月至2021年6月)和II(2021年11月至2022年1月)获得了莫尔豪斯医学院机构审查委员会的批准,并遵守了cherry(互联网电子调查报告结果清单)。结果:调查一和调查二共收到4934份和4905份意见书。一小部分调查(调查I: n=1336, 27.1%;调查II: n=1024, 20.9%)因参与者不合格而被排除,而更大比例的调查(调查I: n=1516, 42.1%;调查II: n=1423, 36.7%)因可疑活动被标记并移除;格鲁吉亚CEAL调查I和II分别保留2082(42.2%)和2458(50.1%)进行分析。结论:在乔治亚州CEAL调查I管理期间的可疑活动促使在调查II的设计和管理期间包含额外的安全工具(例如,隐藏问题,完全自动化的公共图灵测试来区分计算机和人的验证,以及安全问题),这在管理和检测欺诈方面被证明是有用的,并导致了更高的保留率跨调查波。通过对基于网络的调查研究的经验、教训和未来方向的深入讨论,本研究概述了设计和实施针对调查欺诈的强大防御的挑战和最佳实践。最后,我们认为,除了更大的透明度和讨论之外,社区利益相关者还需要通过基于社区的参与性研究方法,有意识地、谨慎地参与到研究中来,以促进科学发现,从而加速对高质量、合法调查数据的投资。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Challenges and Lessons Learned in Managing Web-Based Survey Fraud for the Garnering Effective Outreach and Research in Georgia for Impact Alliance-Community Engagement Alliance Survey Administrations.

Background: Convenience, privacy, and cost-effectiveness associated with web-based data collection have facilitated the recent expansion of web-based survey research. Importantly, however, practical benefits of web-based survey research, to scientists and participants alike, are being overshadowed by the dramatic rise in suspicious and fraudulent survey submissions. Misinformation associated with survey fraud compromises data quality and data integrity with important implications for scientific conclusions, clinical practice, and social benefit. Transparency in reporting on methods used to prevent and manage suspicious and fraudulent submissions is key to protecting the veracity of web-based survey data; yet, there is limited discussion on the use of antideception strategies during all phases of survey research to detect and eliminate low-quality and fraudulent responses.

Objective: This study aims to contribute to an evolving evidence base on data integrity threats associated with web-based survey research by describing study design strategies and antideception tools used during the web-based administration of the Garnering Effective Outreach and Research in Georgia for Impact Alliance-Community Engagement Alliance (GEORGIA CEAL) Against COVID-19 Disparities project surveys.

Methods: GEORGIA CEAL was established in response to the COVID-19 pandemic and the need for rapid, yet, valid, community-informed, and community-owned research to guide targeted responses to a dynamic, public health crisis. GEORGIA CEAL Surveys I (April 2021 to June 2021) and II (November 2021 to January 2022) received institutional review board approval from the Morehouse School of Medicine and adhered to the CHERRIES (Checklist for Reporting Results of Internet E-Surveys).

Results: A total of 4934 and 4905 submissions were received for Surveys I and II, respectively. A small proportion of surveys (Survey I: n=1336, 27.1% and Survey II: n=1024, 20.9%) were excluded due to participant ineligibility, while larger proportions (Survey I: n=1516, 42.1%; Survey II: n=1423, 36.7%) were flagged and removed due to suspicious activity; 2082 (42.2%) and 2458 (50.1%) of GEORGIA CEAL Surveys I and II, respectively, were retained for analysis.

Conclusions: Suspicious activity during GEORGIA CEAL Survey I administration prompted the inclusion of additional security tools during Survey II design and administration (eg, hidden questions, Completely Automated Public Turing Test to Tell Computers and Humans Apart verification, and security questions), which proved useful in managing and detecting fraud and resulted in a higher retention rate across survey waves. By thorough discussion of experiences, lessons learned, and future directions for web-based survey research, this study outlines challenges and best practices for designing and implementing a robust defense against survey fraud. Finally, we argue that, in addition to greater transparency and discussion, community stakeholders need to be intentionally and mindfully engaged, via approaches grounded in community-based participatory research, around the potential for research to enable scientific discoveries in order to accelerate investment in quality, legitimate survey data.

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来源期刊
CiteScore
13.70
自引率
2.40%
发文量
136
审稿时长
12 weeks
期刊介绍: JMIR Public Health & Surveillance (JPHS) is a renowned scholarly journal indexed on PubMed. It follows a rigorous peer-review process and covers a wide range of disciplines. The journal distinguishes itself by its unique focus on the intersection of technology and innovation in the field of public health. JPHS delves into diverse topics such as public health informatics, surveillance systems, rapid reports, participatory epidemiology, infodemiology, infoveillance, digital disease detection, digital epidemiology, electronic public health interventions, mass media and social media campaigns, health communication, and emerging population health analysis systems and tools.
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