Understanding Uptake of Digital Health Products: Methodology Tutorial for a Discrete Choice Experiment Using the Bayesian Efficient Design
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Cameron, Rory
Naughton, Felix
Whitty, Jennifer A
Brown, Jamie
Jones, Andy
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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.
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Journal of Medical Internet Research
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23
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10
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© Dorothy Szinay, Rory Cameron, Felix Naughton, Jennifer A Whitty, Jamie Brown, Andy Jones. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 11.10.2021. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
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Information and computing sciences
Public health
Bayesian
design
digital health
discrete choice experiment
engagement
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Szinay, D; Cameron, R; Naughton, F; Whitty, JA; Brown, J; Jones, A, Understanding Uptake of Digital Health Products: Methodology Tutorial for a Discrete Choice Experiment Using the Bayesian Efficient Design, Journal of Medical Internet Research, 2021, 23 (10), pp. e32365