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Respondent Understanding in Discrete Choice Experiments: A Scoping Review

Author

Listed:
  • Alison Pearce

    (University of Sydney)

  • Mark Harrison

    (University of British Columbia)

  • Verity Watson

    (University of Aberdeen)

  • Deborah J. Street

    (University of Technology Sydney)

  • Kirsten Howard

    (University of Sydney)

  • Nick Bansback

    (University of British Columbia)

  • Stirling Bryan

    (University of British Columbia)

Abstract

Introduction Despite the recognised importance of participant understanding for valid and reliable discrete choice experiment (DCE) results, there has been limited assessment of whether, and how, people understand DCEs, and how ‘understanding’ is conceptualised in DCEs applied to a health context. Objectives Our aim was to identify how participant understanding is conceptualised in the DCE literature in a health context. Our research questions addressed how participant understanding is defined, measured, and used. Methods Searches were conducted (June 2019) in the MEDLINE, EMBASE, PsychINFO and Econlit databases, as well as hand searching. Search terms were based on previous DCE systematic reviews, with additional understanding keywords used in a proximity-based search strategy. Eligible studies were peer-reviewed journal articles in the field of health, related to DCE or best-worst scaling type 3 (BWS3) studies, and reporting some consideration or assessment of participant understanding. A descriptive analytical approach was used to chart relevant data from each study, including publication year, country, clinical area, subject group, sample size, study design, numbers of attributes, levels and choice sets, definition of understanding, how understanding was tested, results of the understanding tests, and how the information about understanding was used. Each study was categorised based on how understanding was conceptualised and used within the study. Results Of 306 potentially eligible articles identified, 31 were excluded based on titles and abstracts, and 200 were excluded on full-text review, resulting in 75 included studies. Three categories of study were identified: applied DCEs (n = 52), pretesting studies (n = 7) and studies of understanding (n = 16). Typically, understanding was defined in relation to either the choice context, such as attribute terminology, or the concept of choosing. Very few studies considered respondents’ engagement as a component of understanding. Understanding was measured primarily through qualitative pretesting, rationality or validity tests included in the survey, and participant self-report, however reporting and use of the results of these methods was inconsistent. Conclusions Those conducting or using health DCEs should carefully select, justify, and report the measurement and potential impact of participant understanding in their specific choice context. There remains scope for research into the different components of participant understanding, particularly related to engagement, the impact of participant understanding on DCE validity and reliability, the best measures of understanding, and methods to maximise participant understanding.

Suggested Citation

  • Alison Pearce & Mark Harrison & Verity Watson & Deborah J. Street & Kirsten Howard & Nick Bansback & Stirling Bryan, 2021. "Respondent Understanding in Discrete Choice Experiments: A Scoping Review," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 14(1), pages 17-53, January.
  • Handle: RePEc:spr:patien:v:14:y:2021:i:1:d:10.1007_s40271-020-00467-y
    DOI: 10.1007/s40271-020-00467-y
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    References listed on IDEAS

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    1. Jennifer A Whitty & Simon Stewart & Melinda J Carrington & Alicia Calderone & Thomas Marwick & John D Horowitz & Henry Krum & Patricia M Davidson & Peter S Macdonald & Christopher Reid & Paul A Scuffh, 2013. "Patient Preferences and Willingness-To-Pay for a Home or Clinic Based Program of Chronic Heart Failure Management: Findings from the Which? Trial," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-8, March.
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    5. Mark Harrison & Dan Rigby & Caroline Vass & Terry Flynn & Jordan Louviere & Katherine Payne, 2014. "Risk as an Attribute in Discrete Choice Experiments: A Systematic Review of the Literature," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 7(2), pages 151-170, June.
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    Cited by:

    1. Jemimah Ride & Ilias Goranitis & Yan Meng & Christine LaBond & Emily Lancsar, 2024. "A Reporting Checklist for Discrete Choice Experiments in Health: The DIRECT Checklist," PharmacoEconomics, Springer, vol. 42(10), pages 1161-1175, October.
    2. Pestana, Joana & Frutuoso, João & Costa, Eduardo & Fonseca, Filipa, 2024. "Heterogeneity in physician's job preferences in a dual practice context – Evidence from a DCE," Social Science & Medicine, Elsevier, vol. 343(C).
    3. Christine Michaels-Igbokwe & Gillian R. Currie & Bryanne L. Kennedy & Karen V. MacDonald & Deborah A. Marshall, 2021. "Methods for Conducting Stated Preference Research with Children and Adolescents in Health: A Scoping Review of the Application of Discrete Choice Experiments," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 14(6), pages 741-758, November.
    4. Nicolet, Anna & Perraudin, Clémence & Krucien, Nicolas & Wagner, Joël & Peytremann-Bridevaux, Isabelle & Marti, Joachim, 2023. "Preferences of older adults for healthcare models designed to improve care coordination: Evidence from Western Switzerland," Health Policy, Elsevier, vol. 132(C).
    5. Rowen, Donna & Powell, Philip A. & Hole, Arne Risa & Aragon, Maria-Jose & Castelli, Adriana & Jacobs, Rowena, 2022. "Valuing quality in mental healthcare: A discrete choice experiment eliciting preferences from mental healthcare service users, mental healthcare professionals and the general population," Social Science & Medicine, Elsevier, vol. 301(C).

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