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An Exploratory Application of Eye-Tracking Methods in a Discrete Choice Experiment

Author

Listed:
  • Caroline Vass

    (Manchester Centre for Health Economics, University of Manchester, Manchester, UK)

  • Dan Rigby

    (Department of Economics, University of Manchester, Manchester, UK)

  • Kelly Tate

    (Division of Neuroscience and Experimental Psychology, School of Biological Sciences, University of Manchester, Manchester, UK)

  • Andrew Stewart

    (Division of Neuroscience and Experimental Psychology, School of Biological Sciences, University of Manchester, Manchester, UK)

  • Katherine Payne

    (Manchester Centre for Health Economics, University of Manchester, Manchester, UK)

Abstract

Background. Discrete choice experiments (DCEs) are increasingly used to elicit preferences for benefit-risk tradeoffs. The primary aim of this study was to explore how eye-tracking methods can be used to understand DCE respondents’ decision-making strategies. A secondary aim was to explore if the presentation and communication of risk affected respondents’ choices. Method. Two versions of a DCE were designed to understand the preferences of female members of the public for breast screening that varied in how risk attributes were presented. Risk was communicated as either 1) percentages or 2) icon arrays and percentages. Eye-tracking equipment recorded eye movements 1000 times a second. A debriefing survey collected sociodemographics and self-reported attribute nonattendance (ANA) data. A heteroskedastic conditional logit model analyzed DCE data. Eye-tracking data on pupil size, direction of motion, and total visual attention (dwell time) to predefined areas of interest were analyzed using ordinary least squares regressions. Results. Forty women completed the DCE with eye-tracking. There was no statistically significant difference in attention (fixations) to attributes between the risk communication formats. Respondents completing either version of the DCE with the alternatives presented in columns made more horizontal (left-right) saccades than vertical (up-down). Eye-tracking data confirmed self-reported ANA to the risk attributes with a 40% reduction in mean dwell time to the “probability of detecting a cancer†( P = 0.001) and a 25% reduction to the “risk of unnecessary follow-up†( P = 0.008). Conclusion. This study is one of the first to show how eye-tracking can be used to understand responses to a health care DCE and highlighted the potential impact of risk communication on respondents’ decision-making strategies. The results suggested self-reported ANA to cost attributes may not be reliable.

Suggested Citation

  • Caroline Vass & Dan Rigby & Kelly Tate & Andrew Stewart & Katherine Payne, 2018. "An Exploratory Application of Eye-Tracking Methods in a Discrete Choice Experiment," Medical Decision Making, , vol. 38(6), pages 658-672, August.
    • Handle: RePEc:sae:medema:v:38:y:2018:i:6:p:658-672
    DOI: 10.1177/0272989X18782197
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    References listed on IDEAS

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    1. Mandy Ryan & Nicolas Krucien & Frouke Hermens, 2018. "The eyes have it: Using eye tracking to inform information processing strategies in multi‐attributes choices," Health Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 709-721, April.
    2. Esther W. de Bekker‐Grob & Mandy Ryan & Karen Gerard, 2012. "Discrete choice experiments in health economics: a review of the literature," Health Economics, John Wiley & Sons, Ltd., vol. 21(2), pages 145-172, February.
    3. Stuart J. Wright & Caroline M. Vass & Gene Sim & Michael Burton & Denzil G. Fiebig & Katherine Payne, 2018. "Accounting for Scale Heterogeneity in Healthcare-Related Discrete Choice Experiments when Comparing Stated Preferences: A Systematic Review," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 11(5), pages 475-488, October.
    4. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74(2), pages 132-132.
    5. Kelvin Balcombe & Iain Fraser & Eugene McSorley, 2015. "Visual Attention and Attribute Attendance in Multi‐Attribute Choice Experiments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(3), pages 447-467, April.
    6. Ryan, Mandy, 1999. "Using conjoint analysis to take account of patient preferences and go beyond health outcomes: an application to in vitro fertilisation," Social Science & Medicine, Elsevier, vol. 48(4), pages 535-546, February.
    7. Jennifer A Whitty & Ruth Walker & Xanthe Golenko & Julie Ratcliffe, 2014. "A Think Aloud Study Comparing the Validity and Acceptability of Discrete Choice and Best Worst Scaling Methods," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-9, April.
    8. A. Brett Hauber & Angelyn Fairchild & F. Reed Johnson, 2013. "Quantifying Benefit–Risk Preferences for Medical Interventions: An Overview of a Growing Empirical Literature," Applied Health Economics and Health Policy, Springer, vol. 11(4), pages 319-329, August.
    9. Christina Kreuzmair & Michael Siegrist & Carmen Keller, 2017. "Does Iconicity in Pictographs Matter? The Influence of Iconicity and Numeracy on Information Processing, Decision Making, and Liking in an Eye‐Tracking Study," Risk Analysis, John Wiley & Sons, vol. 37(3), pages 546-556, March.
    10. Louviere, Jordan J. & Lancsar, Emily, 2009. "Choice experiments in health: the good, the bad, the ugly and toward a brighter future," Health Economics, Policy and Law, Cambridge University Press, vol. 4(4), pages 527-546, October.
    11. repec:cup:judgdm:v:9:y:2014:i:5:p:420-432 is not listed on IDEAS
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    2. Bansal, Prateek & Kim, Eui-Jin & Ozdemir, Semra, 2024. "Discrete choice experiments with eye-tracking: How far we have come and ways forward," Journal of choice modelling, Elsevier, vol. 51(C).

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