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

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 pr...

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Detalles Bibliográficos
Autores principales: Szinay, Dorothy, Cameron, Rory, Naughton, Felix, Whitty, Jennifer A, Brown, Jamie, Jones, Andy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8546533/
https://www.ncbi.nlm.nih.gov/pubmed/34633290
http://dx.doi.org/10.2196/32365
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author Szinay, Dorothy
Cameron, Rory
Naughton, Felix
Whitty, Jennifer A
Brown, Jamie
Jones, Andy
author_facet Szinay, Dorothy
Cameron, Rory
Naughton, Felix
Whitty, Jennifer A
Brown, Jamie
Jones, Andy
author_sort Szinay, Dorothy
collection PubMed
description 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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spelling pubmed-85465332021-11-10 Understanding Uptake of Digital Health Products: Methodology Tutorial for a Discrete Choice Experiment Using the Bayesian Efficient Design Szinay, Dorothy Cameron, Rory Naughton, Felix Whitty, Jennifer A Brown, Jamie Jones, Andy J Med Internet Res Tutorial 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. JMIR Publications 2021-10-11 /pmc/articles/PMC8546533/ /pubmed/34633290 http://dx.doi.org/10.2196/32365 Text en ©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. https://creativecommons.org/licenses/by/4.0/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.
spellingShingle Tutorial
Szinay, Dorothy
Cameron, Rory
Naughton, Felix
Whitty, Jennifer A
Brown, Jamie
Jones, Andy
Understanding Uptake of Digital Health Products: Methodology Tutorial for a Discrete Choice Experiment Using the Bayesian Efficient Design
title Understanding Uptake of Digital Health Products: Methodology Tutorial for a Discrete Choice Experiment Using the Bayesian Efficient Design
title_full Understanding Uptake of Digital Health Products: Methodology Tutorial for a Discrete Choice Experiment Using the Bayesian Efficient Design
title_fullStr Understanding Uptake of Digital Health Products: Methodology Tutorial for a Discrete Choice Experiment Using the Bayesian Efficient Design
title_full_unstemmed Understanding Uptake of Digital Health Products: Methodology Tutorial for a Discrete Choice Experiment Using the Bayesian Efficient Design
title_short Understanding Uptake of Digital Health Products: Methodology Tutorial for a Discrete Choice Experiment Using the Bayesian Efficient Design
title_sort understanding uptake of digital health products: methodology tutorial for a discrete choice experiment using the bayesian efficient design
topic Tutorial
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8546533/
https://www.ncbi.nlm.nih.gov/pubmed/34633290
http://dx.doi.org/10.2196/32365
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