Clinical Epidemiology Interdisciplinary Research Group, Department of Primary Care and Public Health, School of Medicine, Cardiff University, Heath Park, Cardiff, UK.
J Eval Clin Pract. 2011 Aug;17(4):565-74. doi: 10.1111/j.1365-2753.2010.01517.x. Epub 2010 Aug 4.
Although an increasing number of decision support interventions for patients (including decision aids) are produced, few make explicit use of theory. We argue the importance of using theory to guide design. The aim of this work was to address this theory-practice gap and to examine how a range of selected decision-making theories could inform the design and evaluation of decision support interventions.
We reviewed the decision-making literature and selected relevant theories. We assessed their key principles, theoretical pathways and predictions in order to determine how they could inform the design of two core components of decision support interventions, namely, information and deliberation components and to specify theory-based outcome measures.
Eight theories were selected: (1) the expected utility theory; (2) the conflict model of decision making; (3) prospect theory; (4) fuzzy-trace theory; (5) the differentiation and consolidation theory; (6) the ecological rationality theory; (7) the rational-emotional model of decision avoidance; and finally, (8) the Attend, React, Explain, Adapt model of affective forecasting. Some theories have strong relevance to the information design (e.g. prospect theory); some are more relevant to deliberation processes (conflict theory, differentiation theory and ecological validity). None of the theories in isolation was sufficient to inform the design of all the necessary components of decision support interventions. It was also clear that most work in theory-building has focused on explaining or describing how humans think rather than on how tools could be designed to help humans make good decisions. It is not surprising therefore that a large theory-practice gap exists as we consider decision support for patients. There was no relevant theory that integrated all the necessary contributions to the task of making good decisions in collaborative interactions.
Initiatives such as the International Patient Decision Aids Standards Collaboration influence standards for the design of decision support interventions. However, this analysis points to the need to undertake more work in providing theoretical foundations for these interventions.
尽管越来越多的针对患者的决策支持干预措施（包括决策辅助工具）被开发出来，但很少有干预措施明确使用理论。我们认为利用理论来指导设计非常重要。这项工作的目的是解决这一理论与实践之间的差距，并研究一系列选定的决策理论如何为决策支持干预措施的设计和评估提供信息。
我们回顾了决策文献，并选择了相关理论。我们评估了它们的关键原则、理论途径和预测，以确定它们如何为决策支持干预措施的两个核心组成部分（信息和审议部分）的设计提供信息，并指定基于理论的结果测量指标。
选择了 8 种理论：（1）期望效用理论；（2）决策冲突模型；（3）预期理论；（4）模糊痕迹理论；（5）区分和巩固理论；（6）生态理性理论；（7）理性回避决策的理性情绪模型；最后，（8）情感预测的关注、反应、解释、适应模型。有些理论与信息设计密切相关（例如预期理论）；有些理论与审议过程更相关（冲突理论、区分理论和生态有效性）。没有一种理论能够独立地为决策支持干预措施的所有必要组成部分的设计提供充分的信息。因此，当我们考虑为患者提供决策支持时，理论与实践之间存在巨大差距也就不足为奇了。在构建理论方面，大多数工作都集中在解释或描述人类的思维方式，而不是如何设计工具来帮助人类做出明智的决策。因此，在协作交互中做出明智决策的任务中，没有一种综合了所有必要贡献的相关理论，这并不奇怪。
国际患者决策辅助工具标准协作等倡议影响了决策支持干预措施设计的标准。然而，这项分析表明，需要为这些干预措施提供理论基础方面做更多的工作。
