Causal loop diagrams developed by groups capture a shared understanding of complex problems and provide a visual tool to guide interventions. This paper explores the application of network analytic methods as a new way to gain quantitative insight into the structure of an obesity causal loop diagram to inform intervention design. Identification of the structural features of causal loop diagrams is likely to provide new insights into the emergent properties of complex systems and analysing central drivers has the potential to identify leverage points. The results found the structure of the obesity causal loop diagram to resemble commonly observed empirical networks known for efficient spread of information. Known drivers of obesity were found to be the most central variables along with others unique to obesity prevention in the community. While causal loop diagrams are often specific to single communities, the analytic methods provide means to contrast and compare multiple causal loop diagrams for complex problems.

A randomized trial of routine circumcision in children using the Plastibell device is described and compared to a dissection suturing technique. One hundred children were studied with a mean age of 4.7 years. The device was applicable to all boys up to the age of 8, and a few older. General discomfort was carefully assessed and slightly less common after plastibell circumcision, but dysuria more so. No serious complication was encountered with either method; infection was slightly more common after the conventional procedure. Cosmetic results were similar for both methods. It is concluded that the Plastibell device is a satisfactory method for circumcising children of this age.

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.npj Digital Medicine (2020) 3:22 ; https://doi.

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SummaryIntroductionThe Foresight obesity map represents an expert‐developed systems map describing the complex drivers of obesity. Recently, community‐led causal loop diagrams have been developed to support community‐based obesity prevention interventions. This paper presents a quantitative comparison between the Foresight obesity systems map and a community‐developed map of the drivers of obesity.MethodsVariables from a community‐developed map were coded against the thematic clusters defined in the Foresight map to allow comparison of their sizes and strength of adjoining causal relationships. Central variables were identified using techniques from network analysis. These properties were compared to understand the similarities and differences between the systems as defined by the two groups.ResultsThe community map focused on environmental influences, such as built physical activity environment (18% of variables) and social psychology (38%). The Foresight map's largest cluster was physiology (23%), a minimal focus in the community map (2%). Network analysis highlighted media and available time within both maps, but variables related to school and sporting club environments were unique to the community map.ConclusionCommunity stakeholders focus on modifiable social and environmental drivers of obesity. Capturing local perspectives is critical when using systems maps to guide community‐based obesity prevention.