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Developing a Discrete Choice Experiment to Understand Patient Preferences in Resource-Limited Settings: a Six-Step Guide

Authors :
Ann R. Akiteng
Mari Armstrong-Hough
Jeremy I. Schwartz
Rachel Nugent
Isaac Ssinabulya
Sarah E Moor
Christine Ngaruiya
Tracy L. Rabin
Nicola L. Hawley
Evelyn Hsieh
Christine K. Nalwadda
Robert Kalyesubula
Andrew K. Tusubira
Publication Year :
2020
Publisher :
Cold Spring Harbor Laboratory, 2020.

Abstract

A discrete choice experiment (DCE) is a method to quantify preferences for goods and services in a population. Participants are asked to choose between sets of 2 hypothetical scenarios that differ in terms of particular characteristics. Their selections reveal the relative importance of each “attribute”, or characteristic, and the extent to which people consider trade-offs between characteristics. DCEs are increasingly used in healthcare and public health settings as they can inform the design of health-related interventions to achieve maximum impact. Specific efforts must be made in the development process to ensure relevance of DCEs to the communities in which they are administered. Herein, we build upon gaps in the prior literature by offering researchers a step-by-step process to guide DCE development for resource-limited settings, including detailed methodological considerations for each step and a specific actionable approach that we hope will simplify the process for other researchers. We present the 6 steps we followed to develop a DCE to evaluate patient preferences for management of hypertension and diabetes in rural Uganda. These steps are: 1) formative work; 2) attribute selection; 3) attribute level selection; 4) DCE design selection; 5) determination of attribute level combinations; and 6) assessment and enhancement of tool comprehensibility. We describe each of these steps in detail to ease the development process for researchers looking to develop locally contextualized, end-user-centric health interventions.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........107d23494fd0a2780d5a1cd9f709e0f2
Full Text :
https://doi.org/10.1101/2020.10.05.20206557