ArticleHealth policy and planning2022
How to do (or not to do)…using causal loop diagrams for health system research in low and middle-income settings.
Article in Health policy and planning, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
32 citing papers in PubMed.
- Reimagining the Intensive Care Unit as a Complex Adaptive System: A Systems Thinking Perspective.Cureus · 2026Review
- A scoping review and systems thinking synthesis of scale-up frameworks.BMC health services research · 2026Article
- Visualizing stigma and HIV service engagement: a participatory approach using causal loop diagrams.BMC public health · 2026Article
- A systems approach to understanding injury care in LMICs using causal loop diagrams.BMJ global health · 2026Article
- Diagrams-to-Dynamics (D2D): Exploring causal loop diagram leverage points under uncertainty.BMC medicine · 2026Article
- Structural analysis and causal loop modelling: an integrated systems approach to analysing perinatal service delivery in carceral settings in Ontario, Canada.Health research policy and systems · 2026Article
- Applying a gender and equity matrix for a contextualized antimicrobial stewardship intervention in Pakistan.Health policy and planning · 2026Article
- Training-Fuel Coupling (TFC): A Molecular Sports Nutrition Framework for Energy Availability, Chrono-Nutrition, and Performance Optimization.Nutrients · 2026Review
- Integrating systems and implementation science in modeling and evaluating complex health interventions: methodological reflections from service delivery redesign in Kakamega, Kenya.Health policy and planning · 2026Article
- Participatory system dynamics modeling: advancing equity through contextualized implementation science in global health.BMC global and public health · 2026Review
- Implementation pathways of a health services delivery redesign model to improve maternal and newborn outcomes in Kenya.BMJ global health · 2026Article
- A realist review to understand the complexity of effective management of type 2 diabetes and hypertension.Public health reviews · 2026Review
- Towards "Zero by 30", the Kenyan case: a systematic exploration of barriers to rabies policy implementation through systems thinking.Health research policy and systems · 2025Article
- Using causal loop diagrams to explore the maternal and child health system response to payment for performance in Zambia, and it's generalisability across settings.SSM - health systems · 2025Article
- Advancing implementation of shared care for cancer survivors using a systems thinking approach (the SEAMLESS study).Journal of cancer survivorship : research and practice · 2025Article
- Causal Loop Diagrams of Food Systems, Diet, and Obesity: A Scoping Review of Methods, Contextual Factors, and Outcomes.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2025Article
- Identifying the active ingredients in payment for performance programmes using system dynamics modelling.SSM - health systems · 2025Article
- Strategizing towards the future hospital: a systems thinking approach.Health research policy and systems · 2025Article
- Understanding healthcare demand and supply through causal loop diagrams and system archetypes: policy implications for kidney replacement therapy in Thailand.BMC medicine · 2025Article
- A co-designed conceptual model for implementing falls prevention programmes for community-dwelling older adults in Singapore: a systems thinking approach.Age and ageing · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Causal loop diagrams (CLDs) are a systems thinking method that can be used to visualize 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.