The Complex Landscape of Evidence Synthesis
Navigating the Complex Landscape of Evidence Synthesis
On March 26th, 2025, Evidence Prime hosted a webinar that explored the complexities of evidence synthesis and the role of AI in enhancing research quality and efficiency. The session featured insightful presentations from Dr. Danielle Pollock and Artur Nowak.
Understanding the Challenges in Evidence Synthesis
Dr. Pollock opened the discussion by highlighting the growing complexity of evidence synthesis. With numerous types of reviews available, such as systematic reviews, scoping reviews, and mapping reviews, many researchers struggle with classification and methodology. This lack of organization contributes to research waste, inconsistencies in synthesis, and difficulties for first-time reviewers.
To address these issues, Dr. Pollock emphasized the need for a standardized taxonomy and better guidance for researchers. Clearer distinctions between review types and improved methodologies can enhance transparency and reliability in evidence synthesis.
AI as a Solution: Enhancing Evidence Synthesis
Artur Nowak followed with a discussion on AI-driven solutions for evidence synthesis. While AI presents significant opportunities, he also cautioned against the risks of improper use, stressing the need for methodological expertise when integrating AI into research workflows.
Artur outlined several ways AI can streamline and improve evidence synthesis:
- Protocol Review: AI can assist researchers in structuring their protocols to align with best practices.
- Literature Searching: AI tools help automate and refine search strategies, reducing time spent on manual screening.
- Data Extraction: AI speeds up identifying and extracting data points from studies.
By leveraging AI responsibly, researchers can improve the quality and transparency of their work, ultimately advancing the field of evidence-based decision-making.
Engaging Q&A Session
The webinar concluded with a dynamic Q&A session, where attendees asked about different review methodologies and protocol registration. The discussion reinforced the importance of combining AI-driven efficiencies with methodological rigor to ensure high-quality research outcomes.
Stay Tuned for More Insights
If you missed the webinar, you can watch it by registering here: