Table 1 Summary of best principles from systems science for informing the modelling process, recommendations for action by implementation scientists and contributing thought leaders and key references

1. Model the problem, not the system

Conduct formative research; construct models collaboratively in interdisciplinary teams

Sterman [34]

2. Pay attention to what is important, not just what is quantifiable

Use qualitative data to derive causal relationships; be guided by deep thinking and multiple perspectives

Meadows [36]

3. Leverage the utility of models as boundary objects

Create modifiable and readily perceptible representations of models; build trust and agreement by representing local knowledge

Black [43]

4. Adopt a portfolio approach to model building

Work in parallel to develop separate but related models in diverse ways; encourage exploration with ‘flawed’ models rather than aiming for perfection

Metcalf [6]