Abstract
BACKGROUND: Process evaluations are increasingly integrated into randomised controlled trials (RCTs) of complex interventions to document their delivery and interactions with local systems and dynamics, helping understand observed health outcomes. Yet process evaluations often struggle to assess relevant contextual determinants, leaving much of the important role of "context" in shaping an intervention's mechanisms opaque in many studies. A lack of easily adapted data collection methods to help define and operationalise indicators of context likely contributes to this. METHODS: We present a method to help structure measures of context in process evaluations and describe its use in two very different settings. The "Context Tracker" is an innovative tool for use within trials and quasi-experiments to more systematically capture and understand key dimensions of context. It was developed in Zimbabwe as part of a cluster randomised controlled trial and then adapted for a quasi-experimental evaluation in the UK. Both studies provided harm reduction and health services for marginalised and hard-to-reach populations. RESULTS: We developed the Context Tracker to be both standardised (i.e. formatted and applied in the same way across study sites) and flexible enough to allow unique features to be explored in greater detail. Drawing on the Context and Implementation of Complex Interventions (CICI) and Risk Environments frameworks, we mapped 5 domains across micro, meso and macro levels in a simple table and used existing evidence and experience to predict factors likely to affect delivery of and participation in intervention components. We tracked these over time across study sites using routine programme statistics, observation and qualitative methods. The Context Tracker enables identification and comparison of facilitators and barriers to implementation, variations in engagement with interventions, and how mechanisms of action are (or are not) triggered in different settings. CONCLUSIONS: The Context Tracker is one example of how evidence-based contextual determinants can be used to guide data collection and analysis within process evaluations. It is relevant in low- and high-income settings and applicable to both qualitative and quantitative analyses. While perhaps most useful to process evaluations of complex interventions targeting marginalised communities, the broader approach would benefit a more general research audience.