Diverse Approaches to Creating and Using Causal Loop Diagrams in Public Health Research: Recommendations From a Scoping Review

Abstract

Objectives: Complex systems thinking methods are increasingly called for and used as analytical lenses in public health research. The use of qualitative system mapping and in particular, causal loop diagrams (CLDs) is described as one promising method or tool. To our knowledge there are no published literature reviews that synthesize public health research regarding how CLDs are created and used.Methods: We conducted a scoping review to address this gap in the public health literature. Inclusion criteria included: 1) focused on public health research, 2) peer reviewed journal article, 3) described and/or created a CLD, and 4) published in English from January 2018 to March 2021. Twenty-three articles were selected from the search strategy.Results: CLDs were described as a new tool and were based upon primary and secondary data, researcher driven and group processes, and numerous data analysis methods and frameworks. Intended uses of CLDs ranged from illustrating complexity to informing policy and practice.Conclusion: From our learnings we propose nine recommendations for building knowledge and skill in creating and using CLDs for future public health research.

Using systems-mapping to address Adverse Childhood Experiences (ACEs) and trauma: A qualitative study of stakeholder experiences

“…Third, there has been a call for systems-thinking projects to provide evidence of “real-world” benefits [ 58 ]. Systems-mapping projects pertaining to trauma and ACEs often do not report on the next steps, i.e., the programs and initiatives that come out of the project [ 26 , 27 , 29 ]. Participants in our study felt that diverse representation and inclusion in the SMP created community investment in the process and outcomes of the effort to foster tangible, coordinated, and community-led actions addressing ACEs.…”

“…For example, participants expressed that the act of mapping the loops allowed them to see the formerly invisible forces more explicitly, thereby helping to remove individual blame and a punitive mindset in understanding their own trauma and ACEs. A scoping review of how causal-loop diagramming has been used in public health found that the majority of studies used causal-loop diagramming to inform policy and practice, identify intervention points, and illustrate system complexity [ 29 ]. While the review found that there is a wide scope of public health issues represented, such as obesity, community violence, and infectious diseases, only three of the 23 studies captured by the review intended to use systems-mapping to help improve participants’ understanding of the public health issue [ 29 ].…”

“…In practice, systems-mapping usually happens in an academic setting where the participants doing the mapping are often professional and privileged individuals, such as professors, funders, and researchers [ 28 , 29 ]. Systems thinking projects are rarely developed through co-creation with local community leaders and community members, especially in contexts such as the rural southern United States [ 30 ].…”

Utilizing Causal Loop Diagramming to Explore a Research and Evaluation Capacity Building Partnership

“…In public health, many causal loop diagram studies are created only by the researcher team, without input from stakeholders ( 96 ). Collaborative model building processes can help stakeholders overcome difficulties with interpretation ( 97 ), develop a shared understanding of how systems variables and relationships drive change ( 21 ) and create consensus on how to address the issue illustrated by the diagram ( 97 ).…”

“…Refining diagrams after data collection has ceased has been used in previous studies and aligns with good model building practice ( 106 ). Furthermore, developing “reader friendly” casual loop diagrams requires considering how the diagram functions as an effective tool for communicating findings ( 96 ). However, changes were not checked with original participants, which may have reduced the trustworthiness of the diagrams.…”