How to do (or not to do)…using causal loop diagrams for health system research in low and middle-income settings

Abstract

Causal loop diagrams (CLDs) are a systems thinking method that can be used to visualise and unpack complex health system behaviour. They can be employed prospectively or retrospectively to identify the mechanisms and consequences of policies or interventions designed to strengthen health systems and inform discussion with policymakers and stakeholders on actions that may alleviate sub-optimal outcomes. Whilst the use of CLDs in health systems research has generally increased, there is still limited use in low- and middle-income settings. In addition to their suitability for evaluating complex systems, CLDs can be developed where opportunities for primary data collection may be limited (such as in humanitarian or conflict settings) and instead be formulated using secondary data, published or grey literature, health surveys/reports and policy documents. The purpose of this paper is to provide a step-by-step guide for designing a health system research study that uses CLDs as their chosen research method, with particular attention to issues of relevance to research in low- and middle-income countries (LMICs). The guidance draws on examples from the LMIC literature and authors’ own experience of using CLDs in this research area. This paper guides researchers in addressing the following four questions in the study design process; (1) What is the scope of this research? (2) What data do I need to collect or source? (3) What is my chosen method for CLD development? (4) How will I validate the CLD? In providing supporting information to readers on avenues for addressing these key design questions, authors hope to promote CLDs for wider use by health system researchers working in LMICs.

Sexual risk-taking behavior amongst emerging adults in a tertiary institution of learning in Coastal Kenya: A qualitative study of stakeholders’ perspectives using causal loop mapping

“…The interview numbers used in presenting the verbatim were not known to the study participants or any other person outside the study team. To develop the CLD, first a causal structure diagram (CSD) (S2 File) was prepared based on the data (ex-post development) [23] to identify the causal relationships between the correlates of SRTB. The information from the CSD was then used to develop the CLD using Vensim software version 9.3.4 (Ventana systems Inc 2015).…”

“…Systems thinking enables understanding of inter-relationships and interactions within a system [22]. Causal loop diagrams (CLDs) are a systems thinking method that can be used to unpack complex health system behaviour [23]. The current study utilizes CLD to map the system surrounding SRTB.…”

Leveraging global investments for polio eradication to strengthen health systems’ resilience through transition

“…To this end, we used causal loop diagrams (CLDs) that help to map relationships between variables in a system and provide a visual representation of the system structure ( De Savigny et al. , 2017 ; Cassidy et al. , 2022 ).…”

Constructing causal loop diagrams from large interview data sets

“…Various approaches for constructing CLDs from text have been proposed (Eker and Zimmermann, 2016;Kim and Andersen, 2012;Turner et al, 2013a) with some applied specifically in a public health context (e.g. Cassidy et al, 2022) as discussed in the previous section. This study is concerned with trialling and developing manual and semiautomated variations on a method with the aim of deciding how best to proceed in analysing a large qualitative data set.…”