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Opening the ‘Black Box’: An Overview of Methods to Investigate the Decision-Making Process in Choice-Based Surveys

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  • Dan Rigby

    (The University of Manchester)

  • Caroline Vass

    (The University of Manchester)

  • Katherine Payne

    (The University of Manchester)

Abstract

The desire to understand the preferences of patients, healthcare professionals and the public continues to grow. Health valuation studies, often in the form of discrete choice experiments, a choice based survey approach, proliferate as a result. A variety of methods of pre-choice process analysis have been developed to investigate how and why people make their decisions in such experiments and surveys. These techniques have been developed to investigate how people acquire and process information and make choices. These techniques offer the potential to test and improve theories of choice and/or associated empirical models. This paper provides an overview of such methods, with the focus on their use in stated choice-based healthcare studies. The methods reviewed are eye tracking, mouse tracing, brain imaging, deliberation time analysis and think aloud. For each method, we summarise the rationale, implementation, type of results generated and associated challenges, along with a discussion of possible future developments.

Suggested Citation

  • Dan Rigby & Caroline Vass & Katherine Payne, 2020. "Opening the ‘Black Box’: An Overview of Methods to Investigate the Decision-Making Process in Choice-Based Surveys," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 13(1), pages 31-41, February.
    • Handle: RePEc:spr:patien:v:13:y:2020:i:1:d:10.1007_s40271-019-00385-8
    DOI: 10.1007/s40271-019-00385-8
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    1. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part II. Conceptualisation of external validity, sources and explanations of bias and effectiveness of mitigation methods," Journal of choice modelling, Elsevier, vol. 41(C).
    2. 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.
    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. Milad Haghani & Michiel C. J. Bliemer & John M. Rose & Harmen Oppewal & Emily Lancsar, 2021. "Hypothetical bias in stated choice experiments: Part II. Macro-scale analysis of literature and effectiveness of bias mitigation methods," Papers 2102.02945, arXiv.org.
    5. Kaiying Wang & Chris Barr & Richard Norman & Stacey George & Craig Whitehead & Julie Ratcliffe, 2021. "Using Eye-Tracking Technology with Older People in Memory Clinics to Investigate the Impact of Mild Cognitive Impairment on Choices for EQ-5D-5L Health States Preferences," Applied Health Economics and Health Policy, Springer, vol. 19(1), pages 111-121, January.

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