Complex Systems Sciences
Study of how the parts of a system give rise to the collective behaviors of the system and how the system interacts with its environment (Koithan, Bell, Niemeyer, & Pincus, 2012)
Complexity
The result of patterns of interactions resulting from ever-changing demands on the system, as well as attempts to derive and test partial solutions to problems (Marshall & Broome, 2017).
Principles of Complexity
Wholes are not just the sum of their parts.
All healthcare is local.
Value is now the centerpiece of service delivery.
Simple systems aggregate to complex systems.
Diversity is essential to life.
Error is essential to success.
Systems thrive when all thei
Complex Adaptive System (CAS)
Characterized by a number of elements interacting locally in a dynamic, non-linear manner. Interactions in the system are intricate, system activities are a function of what has previously occurred and are open to energy and information from the environme
Properties of a CAS (Chaffee and McNeill, 2007):
- Adaptable elements.
- Attractors.
- Co-evolution.
- Context and embeddedness.
- Emergent behavior.
- Inherent order.
- Nonlinearity.
- Porous boundaries.
- Self-organization.
- Simple rules.
- Unpredictability.
System
A complex of elements in mutual interaction (VonBertalanffy, 1968).
Open System
Exchanges energy with its environment; evolves in complexity over time (Bell & Koithan, n.d.).
Closed System
Does not exchange energy with its environment; runs down over time (Bell & Koithan, n.d.).
System Inputs
Energy, resources, people, raw materials that are introduced into a system.
Elements that are processed in the system.
Throughput
Process that happens in the system.
Output
Outcomes; the result of the processing that occurred.
Network
A series of points or nodes interconnected by communication paths (Bell & Koithan, n.d.). Have connectivity, exchange, and locality.
Connectivity
Each discrete entity or agent (node) has a finite number of defined connections (links) to other nodes (generally dynamic).
Exchange
Links exist for exchange of significant resources between nodes (bidirectionality).
Locality
Delivery of the exchanged resource occurs only in local interactions from node to link or link to node, governed by local behavioral rules (game theory).
Node
A point of connection or junction in a network.
Hub
A center or distribution point in a network.
Weak Link
Links between network elements (modules) with a low intensity connection. Occurs when its addition or removal does not change the mean value of a target measure in a statistically discernible way.
Phase Transition
Sudden transition from a state of disorder to order (or one state into another).
Interaction
The relationships among the parts of the system or network.
Adaptable Elements
Elements in a CAS can evolve (Chaffee & McNeill, 2007).
Attractors
Values or behaviors people are drawn towards, exhibit influence in a CAS (Chaffee & McNeill, 2007). Catalysts in a CAS that allow new behaviors to emerge.
Types of Attractors:
Fixed, Limit-Cycle, Strange.
Fixed Point Attractor
An attractor within a system that is regular, terminating in a single point in phase space (Bell & Koithan, n.d.).
Limit Cycle Attractor
An attractor within a system that is periodic in time, that is, that cycle periodically through an ordered sequence of states (Bell & Koithan, n.d.).
Bifurcation
Points of criticality or instability providing increases in complexity or new attractors arising and resulting in a change in behavioral patterns. Represent abrupt and enduring change or availability of new dynamics (Koithan, Bell, Niemeyer, & Pincus, 201
Catastrophes
Sudden change in events. Involve combinations of attractors and bifurcations, and are operating in some self-organizing events (Bell & Koithan, n.d.).
Co-evolution
Progress in the CAS occurs with constant tension and balance (Chaffee & McNeill, 2007).
Context and Embeddedness
CAS are embedded in other CAS. A nurse is a CAS, and is also an agent within the CAS of nursing, etc (Chaffee & McNeill, 2007). Each system is NESTED within other systems, all evolving and interacting, a single entity cannot be understood without consider
Emergence
New behaviors arise from the co-evolution resulting from the relationship between the CAS and the environment, where change is constantly in evidence as the two co-exist and influence one another (Chaffee & McNeill, 2007). Driven by self-organization (Koi
Inherent Order
Order is maintained in a CAS even without central control (Chaffee & McNeill, 2007).
Non-linearity
One action does not cause a single expected result, but the effect can spread in unpredictable ways (Chaffee & McNeill, 2007). A small change may have an extensive effect and a large change may have a small effect (Chaffee & McNeill, 2007).
Dynamics
Moving, changing, adapting over time towards increased complexity. Transformation of behavior in relations to attractors and emergence (Koithan, Bell, Niemeyer, & Pincus, 2012)
Porous Boundaries
Boundaries between different elements of the system and between the CAS and it's environment (Chaffee & McNeill, 2007). This promotes exchange of information, matter, and energy, and interaction between the components of the elements (Chaffee & McNeill, 2
Self-organization
When order is created through patterns of organization that follow simple rules, such as schools of fish (Chaffee & McNeill, 2007).
There is no single leader; the patterns of movement are non-linear and dynamic. Often seen in crisis where individuals have
Downward Causation
Occurs when a higher level property in a system experiences emergence, and effects on the lower level properties are found (Capra & Luisi, 2015; Tabaczek, 2013).
Simple Rules
Allow for existing behaviors and innovations because there is not a burdensome and stifling compendium of directives that must be followed (Chaffee & McNeill, 2007).
The CAS learns and, as a whole, provides multiple and creative paths for action.
Local ap
Unpredictability
Forecasting is inexact in a CAS because elements change, behavior is emerging and activities are nonlinear; the trajectory of a system is unknowable (Chaffee & McNeill, 2007).
Chaos or Edge of Chaos or Butterfly Effect
A particular nonlinear dynamic wherein seemingly random events are actually predictable from simple deterministic equations. Arises from conflict between systems and elements within a system (O'Grady & Malloch, 2018). The presence of conflicting forces in
Sensitivity to Initial Conditions
Chaos theory proposes that systems outcomes are sensitively dependent on the precise value of prior inputs. Small changes in these initial condition parameters can drastically alter subsequent behaviors of the system. Because of the complexity of these sy
Equilibrium
There is a constant and permanent tension between equilibrium (stabilizers) and disequilibrium (challenges) (O'Grady & Malloch, 2018).
This tension is essential to life and reflects the fact that disequilibrium is the universe's natural state (O'Grady & M
Revolution
Otherwise termed hyper-evolution, occurs when the many local changes are aggregated to inexorably alter the prevailing reality (called the paradigmatic moment) (O'Grady & Malloch, 2018).
A revolution occurs in a system when the external environment or int
Evolution
The adaptive response of a group of organisms that occur over many generations (Bell & Koithan, n.d.).
Reflect the response of the collection of organisms to their environment.
Indirect Causality
One of the most powerful ways of probing how the behavior of a complex system is observing how it responds to a force applied to it, especially indirect effects that take place at different places or times than the force (Bell & Koithan, n.d.).
Fitness Landscape
Fitness is the adaptation of the system to the environment. Represented by a landscape model of self-organization
Systems Perspective
Systems thinking states that parts are best understood, and problems are best solved, as they relate to the whole system. Systems thinkers understand that systems are about relationships, matrices of connections, community, and culture (Marshall & Broome,
Entropy
Disorder.
Underlyed by the second law of thermodynamics which states that an isolated system, in essence a system closed to its environment, if left to itself will tend to increase it's disorganization, it's randomness (Putts, 1978).
The process of entrop
Interdependence
The mutual dependence of all life processes on one another.
All members of an ecological community are interconnected in a vast and intricate network of relationships (Capra & Luisi, 2015).
Equifinality
Implies that an end or characteristic state can be reached in all open systems independent of the starting point. Indicates the sameness of the end derived from varying approaches and varying previous existing states (Putts, 1978).
Multifinality
The end has state has various possibilities; a multifinal situation occurs when the means selected affect the outcome so that the choice of means must rest upon reason to ensure the desired outcome (Putts, 1978).
Feedback Loop or Feedback
A circular arrangement of causally connected elements, in which an initial cause propagates around the links of the loop, so that each element has an effect on the next, until the last "feeds back" the effect into the first element of the cycle.
Can be po
Control of Subsystems
Through increasing centralization, one part of the system must emerge as the controlling unit capable of integrating the actions of the subparts of the system.
This process allows for integration of the total organism and the possibility of unified action