从MOMENT研究中学到的教训:如何在线,跨境以及通过自动化远程数据收集来招募和保留目标人群
Andrew Belfiglio1, Shayleigh Dickson Page2, Sara Pettersson3
1University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States of America.
PloS one
|September 16, 2024
概括
在线研究研究面临来自欺诈参与者的数据完整性威胁. 实施注意力检查等保护措施显著减少了MOMENT研究中的欺诈性数据,改善了在线健康研究的数据质量.
科学领域:
- 数字健康数字健康
- 研究方法研究方法研究方法学
- 数据完整性 数据完整性
背景情况:
- 通过社交媒体在线招聘在研究中越来越普遍.
- 参与者补偿可以激励欺诈性数据创建,威胁研究完整性.
- 这项MOMENT研究旨在监测症状,并为慢性疾病提供自我护理.
研究的目的:
- 在线研究研究中评估数据完整性保护措施的有效性.
- 为了减轻在通过社交媒体招募参与者的研究中欺诈性数据收集.
- 提高在线症状监测研究数据的可靠性.
主要方法:
- 通过社交媒体 (Facebook,Twitter) 和四个国家的患者组织进行招聘.
- 没有强有力的保障措施的初始启动导致了高比例的欺诈性响应.
- 实施包括reCAPTCHA和注意力检查在内的安全措施,然后进行手动数据检查.
主要成果:
- 最初的研究启动有64.5%的受访者报名,99%被确定是欺诈性的.
- 在实施保障措施后,只有12.2%的新受访者是欺诈性的.
- 一个单一的注意力检查问题在重新启动中发现了大多数欺诈案件.
结论:
- 数据完整性的保障对于通过互联网招募参与者的在线研究研究至关重要.
- 有效的保障措施可以显著减少欺诈性数据,确保更高质量的研究成果.
- 在研究出版物中,报告数据完整性策略至关重要.
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