Improving Study Design and Reporting for Stated Choice Experiments [Methods Study], Australia, 2013-2020

Researchers can use experiments to learn about what patients prefer. Discrete choice experiments, or DCEs, describe treatments with different features, such as out-of-pocket costs or wait times. Patients fill out surveys about which treatments they prefer. From their choices, researchers learn what is most important to patients and how they think about the different features.
DCEs can be hard to design and analyze. When surveys are complex, patients may ignore information or take shortcuts, which leads to inaccurate results.
To make DCE results more accurate, researchers can

Change the design of the DCE
Apply statistical methods

But current knowledge of how to do this is limited. In this project, the research team looked at improving methods to design and analyze DCEs.

研究人员可借助实验了解患者的偏好选择。离散选择实验（Discrete Choice Experiments, DCEs）通过不同特征对治疗方案进行描述，例如自付费用或候诊时长。患者需填写关于自身偏好治疗方案的调查问卷，研究人员可通过患者的选择结果，明确患者最为重视的因素，以及其对各类特征的考量逻辑。
离散选择实验的设计与分析往往存在较高难度。若调查问卷过于复杂，患者可能会忽略部分信息或采取简化作答策略，进而导致研究结果不够准确。
为提升离散选择实验结果的准确性，研究人员可通过两种途径优化：一是调整实验设计方案，二是运用统计学分析方法。但目前学界关于此类优化方法的认知仍较为有限。本项目中，科研团队针对离散选择实验的设计与分析方法展开了优化探索。