Brown R1, Kolodziej I1, Fong C1
1University Of Sydney, , Australia
Biography:
Rebecca has a background in Clinical Research, with extensive experience in developing and managing high-quality research databases. She leverages this expertise in her role as a Data Consultant, collaborating with researchers, faculty, professional staff, and students to promote, enhance, and implement best practices in research data management.
Abstract:
Appropriate User Testing (UT) of REDCap projects prior to “go-live” is a critical step to ensuring the integrity, accuracy, and reliability of the resulting dataset. Effective UT allows researchers to identify issues, improve participant experience, validate system functionality, and ensure project requirements are met. This step is often overlooked or inadequately completed, resulting in frequent post-implementation updates, inconsistencies in data, and negatively impacts data capture.
This presentation will outline the development, documentation, and rollout of a self-guided, modular training program to improve REDCap UT practices. Modules will be presented in the form of a REDCap survey that allows researchers to access information relevant to the features and functions utilised within their project. Our approach focuses on directing researchers to confidently validate their databases and guide testing and troubleshooting for REDCap functions and features.
Particular attention will be given to the challenges in designing training that is both scalable and adaptable across diverse research areas. Researchers want training to be flexible, easily accessible, and available “just-in-time”, reflecting their often unpredictable and busy schedules, with neutral language and worked examples to ensure understanding across the broad domain and skill range.
This training will provide researchers with a structured, adaptable pathway to develop essential skills to assess data integrity, system performance, and overall reliability. By improving UT capability, this initiative aims to enhance research data quality and reduce downstream inefficiencies.
Microsoft Copilot(GPT-5 based) was used to support initial drafting. The authors reviewed and validated all content to ensure accuracy.
