Background: Medication nonadherence is a global problem that requires urgent attention. Roughly half of all drugs that are prescribed for chronic treatments are not taken by the patients in question. Initiatives designed to support patients and help them modify their behavior are enhanced by personalization, and a number of profiling tools exist to help customize such interventions. Most of these tools were originally designed as paper-based questionnaires, but the growth of digital adherence technologies (DATs) illuminate the need for the development of digital profiling systems that can interact with fully automated patient interfaces.
Objective: The objective of this study was to examine existing frameworks from medicine, psychology, sociology, consumer behavior, and economics to elaborate a comprehensive, quantitative profiling approach that can be used to drive the customization of patient support initiatives.
Results: Building primarily on Icek Ajzen’s Theory of Planned Behavior (TPB), the Health Belief Model (HBM) was used to inform the beliefs about behavior posited in the TPB, while incorporating established factors regarding self-efficacy in the “control” elements of the TPB and selected social and psychological factors in the other constituents of the model. The resulting SPUR (Social, Psychological, Usage, Rational) framework represents a holistic, profiling tool with detailed, quantitative outputs that describe a patient’s behavioral risks and the drivers of that risk.
Conclusion: An interactive, digital questionnaire built around SPUR represents a potentially useful tool for those desirous of building interactive digital support programs for patients with chronic diseases.



中文翻译：

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SPUR 模型：考虑患者行为的框架。


背景：药物依从性是一个需要紧急关注的全球性问题。大约一半用于慢性治疗的药物并未被相关患者服用。个性化增强了旨在支持患者并帮助他们改变行为的举措，并且存在许多分析工具来帮助定制此类干预措施。这些工具大多数最初设计为纸质问卷，但数字依从性技术 (DAT) 的发展表明需要开发可与全自动患者界面交互的数字分析系统。

目的：本研究的目的是检查医学、心理学、社会学、消费者行为和经济学的现有框架，以制定一种全面的定量分析方法，可用于推动患者支持计划的定制。

结果：主要以 Icek Ajzen 的计划行为理论 (TPB) 为基础，健康信念模型 (HBM) 用于告知 TPB 中设定的有关行为的信念，同时将有关自我效能的既定因素纳入“控制”要素中。 TPB 以及模型其他组成部分中选定的社会和心理因素。由此产生的 SPUR（社会、心理、使用、理性）框架代表了一个整体的分析工具，具有详细的定量输出，可以描述患者的行为风险和该风险的驱动因素。

结论：围绕 SPUR 构建的交互式数字问卷对于那些希望为慢性病患者建立交互式数字支持项目的人来说是一个潜在有用的工具。