Le Ha Thanh, Vu Dung Viet Tien, Nguyen Thi Ngoc Anh, Tran Thi Hang, Nguyen Tan Viet, Tran Thao Phuong, Kekalih Aria, Rijal Samita, Friska Dewi, L Hamers Raph, Karkey Abhilasha, Chambers Mary, Ilo Van Nuil Jennifer, Lewycka Sonia
Oxford University Clinical Research Unit, Hanoi, Vietnam.
Community Medicine Department, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia.
J Med Internet Res. 2025 Jun 11;27:e65377. doi: 10.2196/65377.
Health research requires high-quality data, and population-based health research comes with specific opportunities and challenges for data collection. Electronic data capture can mitigate some of the challenges of working with large populations in multiple, sometimes difficult-to-reach, locations. This viewpoint paper aims to describe experiences during the implementation of two mixed methods studies in Vietnam, Nepal, and Indonesia, focusing on understanding lived experiences of the COVID-19 pandemic across 3 countries and understanding knowledge and behaviors related to antibiotic use in Vietnam. We present the opportunities, challenges, and solutions arising through using Research Electronic Data Capture (REDCap) for designing, collecting, and managing data. Electronic data capture using REDCap made it possible to collect data from large populations in different settings. Challenges related to working in multiple languages, unstable internet connections, and complex questionnaires with nested forms. Some data collectors lacked the digital skills to comfortably use REDCap. To overcome these challenges, we included regular team meetings, training, supervision, and automated error-checking procedures. The main types of errors that remained were incomplete and duplicate records due to disruption during data collection. However, with immediate access to data, we were able to identify and troubleshoot these problems quickly, while data collection was still in progress. By detailing our lessons learned-such as the importance of iterative testing, regular intersite meetings, and customized modifications-we provide a roadmap for future projects to boost productivity, enhance data quality, and effectively conduct large-scale population-based research. Our suggestions will be beneficial for research teams working with electronic data capture for population-based data.
健康研究需要高质量的数据,而基于人群的健康研究在数据收集方面有着特定的机遇和挑战。电子数据采集可以缓解在多个地点(有时是难以到达的地点)对大量人群开展研究的一些挑战。本观点论文旨在描述在越南、尼泊尔和印度尼西亚开展两项混合方法研究期间的经验,重点是了解这三个国家新冠疫情期间的实际经历,以及了解越南与抗生素使用相关的知识和行为。我们介绍了使用研究电子数据采集(REDCap)进行数据设计、收集和管理过程中出现的机遇、挑战及解决方案。使用REDCap进行电子数据采集使得在不同环境下从大量人群中收集数据成为可能。面临的挑战包括多语言工作、网络连接不稳定以及带有嵌套表单的复杂问卷。一些数据收集人员缺乏熟练使用REDCap的数字技能。为克服这些挑战,我们安排了定期的团队会议、培训、监督以及自动错误检查程序。遗留的主要错误类型是数据收集期间因干扰导致的记录不完整和重复。然而,由于能够立即访问数据,我们能够在数据收集仍在进行时迅速识别并解决这些问题。通过详细阐述我们吸取的经验教训,如迭代测试、定期站点间会议和定制修改的重要性,我们为未来项目提供了一个路线图,以提高生产力、提升数据质量并有效地开展大规模基于人群的研究。我们的建议将对使用电子数据采集进行基于人群数据研究的团队有益。