Causal Loop Diagrams

Bala, B. K.; Arshad, Fatimah Mohamed; Noh, Kusairi Mohd

doi:10.1007/978-981-10-2045-2_3

Cited by 27 publications

(21 citation statements)

References 4 publications

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“…CLDs visualize the known or assumed causal structure of a system and consist of variables and connections drawn as arrows between the variables. These connections have specific directions, in line with the underlying causal relationships, and typically have positive or negative polarity (Bala et al 2017 ). A positive connection (+) implies that when the causal variable changes in one direction, the variable it connects to changes in the same direction; a negative connection (-) implies that when the causal variable changes in one direction, the variable it connects to changes in the opposite direction.…”

Section: Methodsmentioning

confidence: 99%

Mapping the multicausality of Alzheimer’s disease through group model building

et al. 2020

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Section: Methodsmentioning

confidence: 99%

Mapping the multicausality of Alzheimer’s disease through group model building

et al. 2020

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“…Systems mapping is an umbrella term for various methods to describe a system's structure in the form of a diagram. In the field of system dynamics it typically refers to constructing causal loop diagrams, which show causal connections and feedback loops among variables (Bala et al, 2017). Systems maps such as causal loop diagrams can be generated using qualitative, quantitative or mixed-methods approaches (Coyle, 2000;Dhirasasna & Sahin, 2019;Wolstenholme, 1999).…”

Section: Participatory Approaches To Systems Mappingmentioning

confidence: 99%

Decarbonising Existing Homes in Wales: A Participatory Behavioural Systems Mapping Approach

Hale

Jofeh

Chadwick

2022

Preprint

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Background: To reduce carbon emissions, urgent change is needed to high-carbon human behaviours including home energy use. Previous policy failures point to insufficient use and integration of systemic and behavioural approaches to bring about change. A novel behavioural systems mapping approach was used to inform national policy recommendations for energy-saving retrofit of homes in Wales. Method: Three participatory workshops were held with the independent Welsh residential decarbonisation advisory group (‘the Advisory Group’) to (1) map relationships between actors, behaviours and influences on behaviour within the home retrofit system, (2) provide training in the Behaviour Change Wheel framework (3) use these to develop policy recommendations for interventions. Recommendations were analysed using the COM-B (capability, opportunity, motivation) model of behaviour to assess whether they addressed these factors. Results: Two behavioural systems maps were produced, representing privately rented and owner-occupied housing tenures. The main causal pathways and feedback loops in each map are described. Necessary interventions to achieve national-scale retrofit included: government-led investment, campaigns and awareness-building, financial-sector funding mechanisms, enforcement of regulations, and creating more streamlined and trusted supply chain services. Of 27 final policy recommendations, 6 addressed capability, 22 opportunity, and 12 motivation. Conclusions: Participatory behavioural systems mapping can be used in conjunction with behaviour change frameworks to develop policy recommendations that address the behavioural determinants of complex environmental problems. Research is underway to refine and extend the approach through application to other sustainability challenges and methods of constructing systems maps.

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“…In biological systems, flows can be flows of matter (energy), that constitute the mechanism by which a stock value may change in time, and flows of information, responsible for the control action exerted by stocks on the processes that in turn control the flows. The control flows network is a fundamental aspect in ST diagramming since their action is responsible for feedbacks and causal loop formation at different time scales (Haraldsson, 2004). The pattern of feedbacks is therefore the feature that defines the system dynamics.…”

Section: The Flowsmentioning

confidence: 99%

Using Stock-Flow Diagrams to Visualize Theranostic Approaches to Solid Tumors in Personalized Nanomedicine

Cazzagon

Romano

Gonella

2021

Front. Bioeng. Biotechnol.

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Personalized nanomedicine has rapidly evolved over the past decade to tailor the diagnosis and treatment of several diseases to the individual characteristics of each patient. In oncology, iron oxide nano-biomaterials (NBMs) have become a promising biomedical product in targeted drug delivery as well as in magnetic resonance imaging (MRI) as a contrast agent and magnetic hyperthermia. The combination of diagnosis and therapy in a single nano-enabled product (so-called theranostic agent) in the personalized nanomedicine has been investigated so far mostly in terms of local events, causes-effects, and mutual relationships. However, this approach could fail in capturing the overall complexity of a system, whereas systemic approaches can be used to study the organization of phenomena in terms of dynamic configurations, independent of the nature, type, or spatial and temporal scale of the elements of the system. In medicine, complex descriptions of diseases and their evolution are daily assessed in clinical settings, which can be thus considered as complex systems exhibiting self-organizing and non-linear features, to be investigated through the identification of dynamic feedback-driven behaviors. In this study, a Systems Thinking (ST) approach is proposed to represent the complexity of the theranostic modalities in the context of the personalized nanomedicine through the setting up of a stock-flow diagram. Specifically, the interconnections between the administration of magnetite NBMs for diagnosis and therapy of tumors are fully identified, emphasizing the role of the feedback loops. The presented approach has revealed its suitability for further application in the medical field. In particular, the obtained stock-flow diagram can be adapted for improving the future knowledge of complex systems in personalized nanomedicine as well as in other nanosafety areas.

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Causal Loop Diagrams

Cited by 27 publications

References 4 publications

Mapping the multicausality of Alzheimer’s disease through group model building

Mapping the multicausality of Alzheimer’s disease through group model building

Decarbonising Existing Homes in Wales: A Participatory Behavioural Systems Mapping Approach

Using Stock-Flow Diagrams to Visualize Theranostic Approaches to Solid Tumors in Personalized Nanomedicine

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