With our field's strong focus on context for understanding and acting on social problems, community psychologists have frequently elevated the importance of employing systems thinking and methods that help us to understand systems more effectively. As a result, community psychologists have adopted some methods from the interdisciplinary field of systems science. In this virtual special issue, we will compare how several of these approaches have been used in publications in the AJCP in the last 50 years. We identify differences in their popularity, implementation with communities, and how they create generative discussion in the field. We conclude by looking to the future to explore ways community psychology can deepen engagement with methods from systems science.

Networked community change (NCC) efforts focus on building and supporting networks of stakeholders in communities to address complex problems, with a particular focus on tie formation among stakeholders and organizer facilitation of an information-sharing network (Lawlor & Neal, 2016). NCC approaches include, for example, systemic action research (Burns, 2007), Collective Impact (Kania & Kramer, 2011), and network action research (Foth, 2006) and can be understood as community-level interventions supporting change (Bess, 2015). Previous research demonstrates the promising nature of NCC efforts under ideal circumstances for efficient information sharing in community change efforts. However, these efforts frequently operate in non-ideal conditions, needing to adapt to a variety of community challenges. This article extends the agent-based simulation model presented in Lawlor and Neal (2016) to reflect the challenges that arise when stakeholders implement these approaches to community change and identify how they can impact information-sharing networks. First, we review literature to establish common challenges that arise in these efforts. Second, we employ the Lawlor and Neal (2016) model to examine these challenges and report on the resulting structure of the information-sharing networks that emerge from implementing them in the simulation model. We conclude with implications of common networked community change challenges on network formation and future directions for addressing these real-world challenges as communities work on complex problems.

Coalitions have a long history as part of the field of community psychology. While community psychologists often work with coalitions, these entities engage in a widerange of activities and structures that are not well defined within the field. In this paper, we explore the following questions: (1) What are the characteristics of coalitions thatcommunity psychologists study? (2) What are the themes in the way authors define coalitions in their work? To address these questions, we conducted a systematic reviewof articles about coalitions in journals serving community psychologists. Findings suggest coalitions can be characterized by a focus on local level community issuesaround health and wellness and include a diverse group of stakeholders. Coalitions are defined by a focus on three types of coordination: knowledge coordination, negotiatedcoordination, and action coordination. These types of coordination are used to address specific problems coalitions encounter and define the goals and techniquesappropriate for resolving them.

Household food security is influenced by the socio-political environment, resource access, and experiential factors, but the systemic interactions of these drivers are rarely considered in the same study. In collaboration with stakeholders, we built a system dynamics model to examine the drivers of food insecurity in Detroit and how community-led interventions could promote food security. We found that single interventions were not as effective as multiple interventions in combination, due to the complex limits on a households’ ability to purchase healthy foods. The iterative modeling process allowed stakeholders to jointly understand and generate insights into the cross-scale limits that households must navigate in order to achieve food security. Furthermore, our modeling effort demonstrates how time is a fundamental resource stock that limits the efficacy of behavioral and structural interventions.

Acute socio-environmental crises often expose systemic problems that are linked by failures in management, environmental, or social systems. If recovery efforts are to address these systemic problems, these issues and the concerns of those impacted by the crisis need to be clearly articulated, rationally represented, and communicated to those responsible for the recovery. Although participatory approaches to crisis recovery often use environmental modeling, explicit ways in which stakeholders' narratives and experiences can be translated into computer-based models for scenario analysis are not readily available to modelers or decision-makers. We present an approach to translating community narratives about crisis events using a free Fuzzy Cognitive Mapping software called Mental Modeler (www.mentalmodeler.org). We applied this process to the recent water crisis in Flint, Michigan, and demonstrate how participatory modeling can give communities a way to structure their thoughts, develop recovery actions, and communicate with those in charge of crisis recovery efforts.