IntroductionApplication of system thinking to the development, implementation and evaluation of childhood obesity prevention efforts represents the cutting edge of community-based prevention. We report on an approach to developing a system oriented community perspective on the causes of obesity.MethodsGroup model building sessions were conducted in a rural Australian community to address increasing childhood obesity. Stakeholders (n = 12) built a community model that progressed from connection circles to causal loop diagrams using scripts from the system dynamics literature. Participants began this work in identifying change over time in causes and effects of childhood obesity within their community. The initial causal loop diagram was then reviewed and elaborated by 50 community leaders over a full day session.ResultsThe process created a causal loop diagram representing community perceptions of determinants and causes of obesity. The causal loop diagram can be broken down into four separate domains; social influences; fast food and junk food; participation in sport; and general physical activity.DiscussionThis causal loop diagram can provide the basis for community led planning of a prevention response that engages with multiple levels of existing settings and systems.

Introduction: Applying systems science in public health trials is a recent innovation in childhood obesity prevention. This paper aims to use systems science conventions to propose a theory of change for community-based interventions aiming to build capacity and use exemplars from systems science for obesity prevention to describe how this approach works.Methods: Participants were community-based researchers. A dynamic hypothesis was created in workshops conducted in 2020 and 2021 by identifying variables critical to building community capacity for systems thinking. These were used to develop stock and flow diagrams representing individual causal relationships, feedback loops, and the overall theory of change.Results: The resultant model identified 9 stocks and 4 pairs of central balancing and reinforcing feedback loops. These represented building commitment through relationships, mutual learning, strengthening collaboration, and embedding capacity. The model is described using examples from 3 trials involving 25 communities across Victoria, Australia. Conclusions:This nonlinear and practice-based model illustrates the process of community-based obesity prevention. The model integrates >20 years of community-based intervention implementation experience, providing an overarching theory of how such interventions work to create change and prevent obesity.

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Background Coalitions are a popular mechanism for delivering community-based health promotion. The aim of this systematic review was to synthesize research that has quantitatively analyzed the association between coalition characteristics and outcomes in community-based initiatives targeting the social determinants of health. Coalition characteristics described elements of their structure or functioning, and outcomes referred to both proximal and distal community changes. Methods Authors searched six electronic databases to identify peer reviewed, published studies that analyzed the relationship between coalition characteristics and outcomes in community-based initiatives between 1980 and 2021. Studies were included if they were published in English and quantitatively analyzed the link between coalition characteristics and outcomes. Included studies were assessed for quality using the Joanna Briggs Institute analytical cross-sectional studies assessment tool. Results The search returned 10,030 unique records. After screening, 26 studies were included from six countries. Initiatives targeted drug use, health equity, nutrition, physical activity, child and youth development, crime, domestic violence, and neighbourhood improvement. Community outcomes measured included perceived effectiveness (n=10), policy, systems or environment change (n=9), and community readiness or capacity (n=7). Analyses included regression or correlation analysis (n=16) and structural equation or pathway modelling (n=10). Studies varied in quality, with a lack of data collection tool validation presenting the most prominent limitation to study quality. Statistically significant associations were noted between community outcomes and wide range of coalition characteristics, including community context, resourcing, coalition structure, member characteristics, engagement, satisfaction, group facilitation, communication, group dynamics, relationships, community partnership, and health promotion planning and implementation. Conclusion Existing literature demonstrates that coalition characteristics, including best practice health promotion planning and evaluation, influence community outcomes. The field of coalition research would benefit from more consistent description and measurement of coalition characteristics and outcomes, and efforts to evaluate coalitions in a wider range of countries around the world. Further research using empirical community outcome indicators, and methods that consider the interrelationship of variables, is warranted. Trial registration A protocol for this review was registered with PROSPERO (CRD42020205988).

Systems thinking approaches are increasingly being used to help communities understand and develop responses to preventing complex health problems. Less is known about how success is characterized and what influences success in these approaches. We present a systematic review of how concepts of success are understood and evaluated in the peer reviewed literature of studies using systems thinking in community prevention. We searched five databases for peer-reviewed literature published between 2000 and 2022, with search terms related to systems thinking, prevention and community. Studies were included if they; reported using community-based systems thinking to prevent a public health problem; described the engagement and empowerment of community members to address a public health issue; and, were published in English. Thirty-four articles were identified from 10 countries. Twenty-one aimed to prevent a chronic disease (e.g., obesity) and 16 measured success using specific tools, 10 of which used semi-structured interviews or surveys. Measures of success included implementation processes, cultural appropriateness, the number or type of actions implemented, effectiveness of community action, and changes in individual thinking or mental models, population health outcomes, data collected, or systems level measures. Implementation factors influencing success included the capacity to engage participants, composition and experience of facilitators, strength of coordination teams, allocation of resources, adaptation to participant feedback, use of multiple systems approaches, workshop process providing time and methods to allow new insights, flexible delivery, and diversity of perspectives. Findings from each of the articles indicated that approaches increased a range of outcomes including community action, strategic thinking, future planning and evaluation, community buy-in, community voice, contribution and leadership, in addition to developing shared visions and goals and creating new, ongoing collaborations, among many others. Measures of success varied, suggesting more empirical reporting of proposed outcomes of system science in communities would be valuable. While the measurement of success in the use of systems thinking in community-based prevention efforts is limited, there are helpful examples we can look to for future measurement of success.