ACT-CTU Clinical Trial Rounds - Dr. Isabelle Fortier and Rita Wissa

Value of the Information & Strength of the Argument

The value of the information is high, as it provides practical, actionable advice based on extensive experience in managing clinical trial data. The speakers illustrate common pitfalls with concrete examples, such as the change from long to short IPAQ forms, which led to incompatible data, and the issue of overlapping categories in survey questions. Their argumentation is solid, grounded in real-world cases, and they emphasize the importance of rigorous validation and documentation. The presentation is persuasive, urging researchers to invest time and resources in data management from the outset to avoid costly errors later.

Scientific Rigor, Source Quality, Title Accuracy

The scientific rigor is evident in the speakers’ expertise and the systematic approach they advocate. They reference the FAIR principles and mention resources like the Maelstrom Research website for further guidance. However, they do not cite specific scientific literature, relying instead on anecdotal evidence from their projects. The title accurately reflects the content, which is a focused discussion on data quality in clinical trials. The presentation is well-structured, with clear examples and practical recommendations, though it lacks formal citations to external sources.

The title accurately reflects the content, which focuses on optimizing data quality in clinical trials, presented by the two named experts.

8/10

The presentation is given by two experts in data management and harmonization, with extensive experience in clinical research. They provide practical, real-world examples and emphasize rigorous validation and documentation. The content aligns with established best practices in clinical data management, though it is primarily based on anecdotal experience rather than formal citations.

Markers derived by PSI from the transcript: the creator did not define chapters.

• 02:00Introduction of speakers and topic.
• 05:00Discussion on the complexity of clinical research data and the need for FAIR principles.
• 10:00Importance of data management plans and budgeting.
• 15:00Examples of questionnaire design pitfalls, including changing questions mid-study.
• 20:00Discussion on variable format anticipation and date variable issues.
• 25:00Case study of cancer type question changes across waves.
• 30:00Importance of testing and piloting data collection tools.
• 35:00Data monitoring and release processes.
• 40:00Examples of data inconsistencies and cross-checking.
• 45:00Documentation and versioning best practices.

• Maelstrom Research — Mentioned as a resource for data harmonization and management tools.

• FAIR Principles — The speakers emphasize the need for data to be findable, accessible, interoperable, and reusable, aligning with the FAIR principles.