A growing body of evidence suggests that causal loop diagrams — a core tool of systems thinking — are transforming how researchers and policymakers understand the interconnected dynamics of health systems, chronic disease, and population health.
Why linear thinking fails in health management
Health systems are complex adaptive systems. Emergency department crowding feeds back into primary care workloads; workforce burnout accelerates staff turnover, which increases the workload on remaining personnel; and childhood obesity prevention programs interact with food industry dynamics, school policies, and community infrastructure simultaneously. Traditional statistical models, designed to isolate the effect of one variable on another while holding everything else constant, systematically miss these feedback loops. Causal loop diagrams (CLDs) address this gap by mapping the circular causality that governs real-world health systems (Littlejohns et al., 2018; Schoenenberger et al., 2016).
A CLD represents variables as nodes and causal relationships as arrows, with each arrow carrying a polarity sign: “+” for same-direction change and “–” for opposite-direction change. Closed loops are classified as reinforcing (R) — driving exponential growth or collapse — or balancing (B) — pulling the system toward equilibrium. This deceptively simple grammar enables the visualization of feedback structures that are otherwise invisible in tabular data or regression output.
Mapping the evidence: 211 articles across two decades
A systematic search of the Web of Science Core Collection using the topic query “causal loop diagram,” restricted to over 30 health-related WoS categories and filtered to retain only original research articles, yielded 211 publications spanning 2007–2026. The dataset excludes retracted publications, editorials, corrections, meeting abstracts, book chapters, proceedings, and review articles.
The growth trajectory is striking. Only 9 articles were published between 2007 and 2014. Annual output reached 15 in 2020, climbed to 22 in 2023, surged to 40 in 2024, and peaked at 45 in 2025. The first quarter of 2026 alone has already produced 13 articles, signaling continued acceleration. This exponential growth likely reflects the heightened demand for complexity-aware methodologies catalyzed by the COVID-19 pandemic (Lekagul et al., 2022).
The 211 articles have collectively received 2,759 citations, with a mean of 13.1 and a median of 4 citations per article. The most-cited article, with 151 citations, mapped the feedback loops of major depressive disorder (Wittenborn et al., 2016). Forty-two articles have not yet received any citations, predominantly because they were published in 2024–2026.
Five thematic clusters shaping the field
Health system strengthening and policy design constitutes the largest thematic cluster. Malakoane et al. (2020) used CLDs to appraise the challenges of the public health system in South Africa’s Free State province, generating 141 citations. Kwamie et al. (2014) applied systems thinking through realist evaluation of a leadership development program for district health managers in Ghana (82 citations). Ozawa et al. (2016) explored pathways for building trust in vaccination and strengthening health system resilience (76 citations). More recently, Botwright et al. (2025) analyzed healthcare demand-supply dynamics through CLDs and system archetypes, drawing policy implications for kidney disease management.
Obesity, nutrition, and physical activity form a robust second cluster. Brennan et al. (2015) examined systems thinking applications related to healthy eating, active living, and childhood obesity across 49 U.S. communities (83 citations). Chavez-Ugalde et al. (2022) used group model building to frame the commercial determinants of adolescent dietary behavior, revealing industry-level feedback loops that conventional research designs typically overlook.
Mental health and psychosocial well-being represent a growing domain. Beyond the foundational work of Wittenborn et al. (2016) on depression, Crielaard et al. (2021) modeled the impact of adverse socioeconomic conditions on chronic stress from a complexity science perspective (78 citations), and Trani et al. (2016) applied community-based system dynamics to global mental health intervention in Afghanistan (47 citations).
Aging and neurodegenerative disease have emerged as an important frontier. Uleman et al. (2021) mapped the multicausality of Alzheimer’s disease through group model building, integrating perspectives from neuroscience, cardiology, nutrition, and sleep science into a single CLD (46 citations). Wang et al. (2023) applied systems thinking to unravel the mechanisms underlying orthostatic hypotension-related fall risk in older adults.
Health equity and social determinants constitute a thematically distinctive cluster. Burrell et al. (2021) depicted how structural racism and disenfranchisement create dynamics in community violence (51 citations). Mills et al. (2023) constructed a CLD of smoking behavior to advance health equity in tobacco control.
Group model building: the methodological signature
An abstract-level content scan reveals that stakeholder participation appears in 79 articles, interviews in 63, and group model building (GMB) in 62. Workshops (57 articles), qualitative methods (58), and expert consultation (45) further underscore the participatory epistemological foundation of CLD research.
GMB is the methodological innovation that distinguishes CLD research from conventional health management studies. It brings diverse stakeholder groups — clinicians, managers, patients, policymakers, community representatives — together in structured workshops to collectively construct a system model. Broekhuizen et al. (2022) used GMB to derive policy lessons from surgical team mentoring in Uganda. Koh et al. (2023) employed GMB with clinicians to model fall reduction strategies for community-dwelling older adults. The core strength of GMB lies in its capacity to integrate divergent mental models into a collective system map, making tacit knowledge explicit and actionable.
While CLDs are inherently qualitative mapping tools, 25 articles extended them into quantitative simulation through stock-and-flow modeling. Leerapan et al. (2021) demonstrated this transition in the context of health workforce planning for Thailand’s Universal Health Coverage scheme, providing a template for how CLDs can evolve from qualitative mapping to quantitative policy simulation.
Geographic and institutional landscape
The Netherlands dominates the field with 171 author affiliations, followed by Australia (126) and the United States (211 address mentions). The United Kingdom (54), China (45), Canada (37), Singapore (34), and Thailand (31) constitute the next tier of contributing nations. The Netherlands’ disproportionate prominence reflects the system dynamics research traditions anchored at Amsterdam and Maastricht universities. ZonMw (the Netherlands Organisation for Health Research and Development) is the most frequent funder (5 articles), followed by the UK Medical Research Council (4) and the Wellcome Trust (3).
Health Research Policy and Systems leads the publication landscape with 12 articles, followed by Social Science & Medicine (9), Frontiers in Public Health (8), BMC Public Health (8), and BMC Medicine (7). The open access rate is remarkably high: 174 of 211 articles (82.5%) are available through some form of open access, facilitating global dissemination.
An open frontier for Turkish health management
Perhaps the most striking finding of this bibliometric analysis is that none of the 211 articles carries a Turkish institutional affiliation. This absence represents both a gap and a strategic opportunity. Turkey’s health system transformation — including the city hospital model, family medicine gatekeeping dynamics, health workforce planning challenges, and the rapidly aging population — presents research questions ideally suited to CLD methodology.
Malakoane et al.’s (2020) public health system appraisal model could be directly adapted for Turkish city hospitals. Xu and Mills’ (2017) gatekeeping analysis in rural China offers a methodological template for studying referral dynamics in Turkish family medicine. Leerapan et al.’s (2021) workforce planning model provides a framework for addressing physician and nurse supply-demand imbalances. Any of these adaptations could yield the first WoS-indexed CLD article from Turkey, published in journals such as Health Research Policy and Systems, BMC Health Services Research, or Social Science & Medicine.
Conclusion
Causal loop diagrams have established themselves as a rapidly growing, interdisciplinary, and high-impact research tool in the health sciences. The 211-article evidence base demonstrates applications spanning health system strengthening, mental health, childhood obesity, geriatric care, health equity, and patient safety. For health management scholars in Turkey and other countries currently absent from this literature, CLD methodology — particularly when combined with group model building — offers a powerful, participatory, and publication-ready approach to understanding the complex dynamics that define contemporary health systems.
References
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