Leveraging group model building to operationalize implementation strategies across implementation phases: an exemplar related to child maltreatment intervention selection.

Background: Implementation strategies can help support the adoption and implementation of health interventions that are appropriate for a local context and acceptable to decision makers and community members. Implementation strategies should be designed to handle the complexity of the multi-level, dynamic contexts in which interventions are implemented. Systems science theories and methods explicitly attend to complexity and can be valuable for specifying implementation strategies. Group Model Building (GMB) combines research partner engagement strategies with systems science to support researchers' and partners' learning about complex problems and to identify solutions through consensus. This paper specifies how GMB can operationalize implementation strategies - methods for supporting evidence implementation in real-world practice - and describes how GMB can aid in selecting and tailoring both health interventions and implementation strategies. A case study in child maltreatment prevention planning is provided to illustrate how GMB was used to specify the "actions" - strategy activities - for three implementation strategies (conduct local consensus discussions; build a coalition; model and simulate change) during the earliest implementation phases, with the goal of supporting intervention selection decisions. Examples are provided of generalizable research products that can be produced concurrently through GMB, in addition to contextually-driven implementation support.

Methods: Participants (n = 8) were engaged over four sessions using tailored GMB activities. Participants generated a qualitative system dynamics model that described their theory of change for how to prevent child maltreatment in their communities. This theory of change reflected a dynamic understanding of the interconnected determinants of child maltreatment.

Results: GMB was acceptable to participants and resulted in products that could be used for implementation planning (e.g., to model and simulate change) and future research. GMB fostered trust and idea sharing between participants.

Conclusion: GMB can facilitate learning about which outcomes are (or are not) impacted by interventions, which resources and approaches are required for quality implementation (e.g., implementation strategies), and tradeoffs in outcomes and resources between interventions. GMB also provides a structured, effective process to generate a shared implementation vision amongst participants. Lessons learned include methods for developing trust with and between participants, and the need for researchers to tailor GMB actions for participant and project needs.