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Table 1 Hallmarks of complex adaptive systems

From: Tool for evaluating research implementation challenges: A sense-making protocol for addressing implementation challenges in complex research settings

Hallmarks of complex adaptive systems Definitions Example from research setting
Large Number of agents Agents are system components. In healthcare settings, agents may be people (e.g., physicians, patients, administrators), processes (e.g., nursing processes), or functional units (e.g., accounting), and organizations (e.g., regulatory agency) [10]. Subjects, healthcare providers, research team members, administrators, regulators, funders
The agents are diverse The more diverse the agents, the greater the likelihood of novel behavior [10]. Diverse training, background, expertise, experience
The agents are connected and interdependent The number and quality of connections among agents. Interdependence ensures that the performance of any one individual is not the additive function of the actions of that agent. Agents interact and use each other’s knowledge and skills, and build on each other’s work products [11]. Frequent interactions for coordinating and implementing the protocol, regular study team meetings
Relationships among agents are non-linear and unpredictable Patterns of the relationships between the agents do not directly reflect the inputs and outputs from the relationships [10]. Relationship between study team and setting administrator may facilitate or hinder protocol implementation
Agents interact with the environment and both co-evolve Agents respond to the environment and/or other agents but the reciprocal environment and/or agent also change from the interaction, influencing how both develop [12]. Study team adapts intervention schedule based on clinical routine at the site. Site implements new routine to facilitate recruitment (e.g., pizza at meeting)
The system’s future is linked to its past because of its history of co-evolution. The history of an agent and its interactions shape its current and future state but does not preclude unpredictable transformation of a complex adaptive system at any given time [13]. Prior experience with research by the site may influence its implementation of current project
Agents self-organize Agents interact and mutually adjust behaviors to meet demands of the environment. Through self-organization, new patterns of behavior emerge [14]. Researchers learn ways to be mobile—moving to locations to do the intervention rather than having staff come to the researchers
System dynamics lead to emergence of new forms or order which are not under centralized control ‘Patterns and processes that occur within the underlying networks play a major role in the emergence of system-wide features;’ (page, 623). These are discernible global patterns over which there is no centralized control [9]. Study subjects may be more or less likely to participate based on what other agents in the system are saying about the study; higher or lower site participation rates result