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Understanding the extent to which an intervention ‘works’ can provide compelling evidence to decision makers, although without an accompanying explanation of how an intervention works, this evidence can be difficult to apply in other settings, ultimately impeding its usefulness in making judicious and evidence-informed decisions. In this paper, we describe logic models as a tool for outlining graphically a hypothesis of how an intervention leads to a change in an outcome through depicting a causal chain of events. However, it is the nature of these connecting relationships and their basis in causality which is of interest here, and we focus on complex causal relationships and the way in which contextual factors reflecting the intervention setting or population may moderate these. Evidence synthesis techniques are considered, and their usefulness in analysing different parts of the causal chain or different types of relationship. The approaches outlined in this paper aim to assist systematic reviewers in producing findings that are useful to decision makers and practitioners, and in turn help to confirm existing theories or develop entirely new ways of understanding how interventions effect change
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Kneale et al. (2018) studied this question.
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