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Updated: Dec 27, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Tools and analytic techniques to synthesise community knowledge in CBPR using computer-mediated participatory system
Joshua Hayward1, Saraya Morton1, Michael Johnstone2
11Global Obesity Centre, Institute for Health Transformation, Deakin University, Geelong, 3220 Australia.
Abstract:
Participatory systems thinking methods are often used in community-based participatory research to engage and respond to complexity. Participation in systems thinking activities creates opportunities for participants to gain useful insights about complexity. It is desirable to design activities that extend the benefits of this participation into communities, as these insights are predictive of success in community-based prevention. This study tests an online, computer-mediated participatory system modelling platform (STICKE) and associated methods for collating and analysing its outputs. STICKE was trialled among a group of community members to test a computer-mediated system modelling exercise. The causal diagrams resulting from the exercise were then merged, and network analysis and DEMATEL methods applied to inform the generation of a smaller summary model to communicate insights from the participant group as a whole. Participants successfully completed the online modelling activity, and created causal diagrams consistent with expectations. The DEMATEL analysis was identified as the participant-preferred method for converging individuals causal diagrams into a coherent and useful summary. STICKE is an accessible tool that enabled participants to create causal diagrams online. Methods trialled in this study provide a protocol for combining and summarising individual causal diagrams that was perceived to be useful by the participant group. STICKE supports communities to consider and respond to complex problems at a local level, which is cornerstone of sustainable effective prevention. Understanding how communities perceive their own health challenges will be important to better support and inform locally owned prevention efforts.
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