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理解数字健康产品的采用:使用贝叶斯有效设计的离散选择实验方法学教程。

Understanding Uptake of Digital Health Products: Methodology Tutorial for a Discrete Choice Experiment Using the Bayesian Efficient Design.

机构信息

Behavioural and Implementation Science Group, School of Health Sciences, University of East Anglia, Norwich, United Kingdom.

Norwich Medical School, University of East Anglia, Norwich, United Kingdom.

出版信息

J Med Internet Res. 2021 Oct 11;23(10):e32365. doi: 10.2196/32365.

Abstract

Understanding the preferences of potential users of digital health products is beneficial for digital health policy and planning. Stated preference methods could help elicit individuals' preferences in the absence of observational data. A discrete choice experiment (DCE) is a commonly used stated preference method-a quantitative methodology that argues that individuals make trade-offs when engaging in a decision by choosing an alternative of a product or a service that offers the greatest utility, or benefit. This methodology is widely used in health economics in situations in which revealed preferences are difficult to collect but is much less used in the field of digital health. This paper outlines the stages involved in developing a DCE. As a case study, it uses the application of a DCE to reveal preferences in targeting the uptake of smoking cessation apps. It describes the establishment of attributes, the construction of choice tasks of 2 or more alternatives, and the development of the experimental design. This tutorial offers a guide for researchers with no prior knowledge of this research technique.

摘要

了解数字健康产品潜在用户的偏好对数字健康政策和规划很有帮助。陈述偏好方法可以帮助在没有观察数据的情况下得出个人的偏好。离散选择实验(DCE)是一种常用的陈述偏好方法,即一种定量方法,它认为个人在做出决策时会通过选择提供最大效用或利益的产品或服务的替代方案来进行权衡。这种方法在健康经济学中广泛用于难以收集显示偏好的情况,但在数字健康领域的使用要少得多。本文概述了开发 DCE 所涉及的阶段。作为一个案例研究,它使用 DCE 的应用来揭示针对戒烟应用程序的采用的偏好。它描述了属性的建立、2 个或更多替代方案的选择任务的构建以及实验设计的开发。本教程为没有该研究技术先验知识的研究人员提供了指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce62/8546533/b3dbf084e09a/jmir_v23i10e32365_fig1.jpg

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