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Causal loop diagrams
A brief introduction
© 2014, Johns Hopkins University. All rights reserved.
Overview of systems thinking analytical
tools
© 2014, Johns Hopkins University. All rights reserved.
Example of applying systems thinking
approach
“Overview of system dynamics modeling approach”,
from: Martinez and Richardson (2013)
© 2014, Johns Hopkins University. All rights reserved.
What are causal loop diagrams and why
are they useful?
• System dynamics method used to develop a
qualitative conceptualization of a system
• Focus on visualizing internal, mental models
• Facilitates consensus-building and brainstorming
• Can help bring together perspectives and data from
different disciplines
• Complements “traditional” data collection and
analysis
© 2014, Johns Hopkins University. All rights reserved.
What are causal loop diagrams and why
are they useful?
• Emphasis on causality and feedback effects
• Causal loop diagrams indicate the sign and direction
of the causality and the type of feedback in the
system
• Communication – NOT simulation
• Whether modeling is appropriate depends on the
question you are trying to solve
© 2014, Johns Hopkins University. All rights reserved.
Paina et al (under review) Dual practice
policy in Uganda
© 2014, Johns Hopkins University. All rights reserved.
Rwashana et al (2008) Immunization System
CLD
© 2014, Johns Hopkins University. All rights reserved.
Causal loop diagram components
• Causality: AB
• Changes in B are caused by changes in A
• Polarity: + or –
• If A and B change in the same direction (either both increase or both
decrease), then polarity is +
• If A and B change in opposite directions, then polarity is –
© 2014, Johns Hopkins University. All rights reserved.
Causal loop diagram components
• Feedback loops – a change in the system catalyzes a
cascade through other variables to either reinforce or
balance the initial change.
• Reinforcing feedback loop (vicious or virtuous) – amplifying effect
• Balancing feedback loops – dampening effect
© 2014, Johns Hopkins University. All rights reserved.
Causal loop diagram components
• Delays
• The effect that A has on B is delayed (||)
• Balancing loops are often self-regulating, experience delays
© 2014, Johns Hopkins University. All rights reserved.
Developing a causal loop diagram
• Qualitative and quantitative data collected using
rigorous methods
• Iterative process for identification of key variables and causal linkages
• E.g. Rwashana’s dynamic systems methodology
• Stage 1 – Problem statement
• Stage 2 – Field studies
• Stage 3 – Model building ***This is where CLDs come in***
• Stage 4 – Case study
• Stage 5&6 – Simulations and Policy analysis
• Participatory modeling and diagram development
• Group model building
• E.g. Peter Hovmand’s work (for example (2012) Hovmand - Group Model-Building
‘Scripts’ as a Collaborative Planning Tool)
© 2014, Johns Hopkins University. All rights reserved.
Thank you

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A 101 (or 100.5) on Systems Approaches to Capacity Building for Community Health _Ligia Paina_5.8.14

  • 1. Causal loop diagrams A brief introduction
  • 2. © 2014, Johns Hopkins University. All rights reserved. Overview of systems thinking analytical tools
  • 3. © 2014, Johns Hopkins University. All rights reserved. Example of applying systems thinking approach “Overview of system dynamics modeling approach”, from: Martinez and Richardson (2013)
  • 4. © 2014, Johns Hopkins University. All rights reserved. What are causal loop diagrams and why are they useful? • System dynamics method used to develop a qualitative conceptualization of a system • Focus on visualizing internal, mental models • Facilitates consensus-building and brainstorming • Can help bring together perspectives and data from different disciplines • Complements “traditional” data collection and analysis
  • 5. © 2014, Johns Hopkins University. All rights reserved. What are causal loop diagrams and why are they useful? • Emphasis on causality and feedback effects • Causal loop diagrams indicate the sign and direction of the causality and the type of feedback in the system • Communication – NOT simulation • Whether modeling is appropriate depends on the question you are trying to solve
  • 6. © 2014, Johns Hopkins University. All rights reserved. Paina et al (under review) Dual practice policy in Uganda
  • 7. © 2014, Johns Hopkins University. All rights reserved. Rwashana et al (2008) Immunization System CLD
  • 8. © 2014, Johns Hopkins University. All rights reserved. Causal loop diagram components • Causality: AB • Changes in B are caused by changes in A • Polarity: + or – • If A and B change in the same direction (either both increase or both decrease), then polarity is + • If A and B change in opposite directions, then polarity is –
  • 9. © 2014, Johns Hopkins University. All rights reserved. Causal loop diagram components • Feedback loops – a change in the system catalyzes a cascade through other variables to either reinforce or balance the initial change. • Reinforcing feedback loop (vicious or virtuous) – amplifying effect • Balancing feedback loops – dampening effect
  • 10. © 2014, Johns Hopkins University. All rights reserved. Causal loop diagram components • Delays • The effect that A has on B is delayed (||) • Balancing loops are often self-regulating, experience delays
  • 11. © 2014, Johns Hopkins University. All rights reserved. Developing a causal loop diagram • Qualitative and quantitative data collected using rigorous methods • Iterative process for identification of key variables and causal linkages • E.g. Rwashana’s dynamic systems methodology • Stage 1 – Problem statement • Stage 2 – Field studies • Stage 3 – Model building ***This is where CLDs come in*** • Stage 4 – Case study • Stage 5&6 – Simulations and Policy analysis • Participatory modeling and diagram development • Group model building • E.g. Peter Hovmand’s work (for example (2012) Hovmand - Group Model-Building ‘Scripts’ as a Collaborative Planning Tool)
  • 12. © 2014, Johns Hopkins University. All rights reserved. Thank you

Hinweis der Redaktion

  1. Learning and management tools – not a focus of this presentation
  2. How to read a CLD
  3. Reinforcing if all polarities in the loop are the sameBalancing if not all polarities in the loop are the same