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Enhancing implementation science by applying best principles of systems science

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Figure

Fig. 1 Stages of the modelling process. The modelling process depicted as an iterative sequence of steps beginning with problem definition andconcluding with policy analysis
Fig. 3 Example of causal mapping from qualitative data. A reinforcingloop reflecting the essence of a comment (qualitative data) from afocus group participant regarding the importance of a peer network inrecommending healthcare providers
Fig. 5 Simulation modelling in context. The practice of simulationmodelling is situated amidst an ongoing process of observing thereal world, formulating mental models of how it works, settingdecision rules to guide behaviour, and from these heuristics, makingdecisions that in turn affect the state of the real world
Table 1 Summary of best principles from systems science for informing the modelling process, recommendations for action byimplementation scientists and contributing thought leaders and key references

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