ABSTRACT

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

摘要

了解干预措施“有效”的程度可以为决策者提供令人信服的证据，尽管没有附带说明干预措施的工作原理，但该证据可能难以在其他情况下应用，最终阻碍了其在做出明智和证据方面的有用性，明智的决定。在本文中，我们将逻辑模型描述为一种工具，通过描绘事件的因果链，以图形方式概述干预如何导致结果变化的假设。但是，这里需要关注的是这些联系关系的性质及其因果关系的基础，我们关注于复杂的因果关系以及反映干预环境或人群的情境因素可以缓和这些关系的方式。考虑了证据综合技术，以及它们在分析因果链的不同部分或不同类型的关系中的有用性。本文概述的方法旨在帮助系统的审阅者得出对决策者和从业人员有用的发现，进而有助于确认现有理论或开发全新的方式来理解干预措施如何改变变化