Comparison of Preferences and Data Quality between Discrete Choice Experiments Conducted in Online and Face-to-Face Respondents

Ruixuan Jiang, Eleanor Pullenayegum, James W. Shaw, Axel Mühlbacher, Todd A. Lee, Surrey Walton, Thomas Kohlmann, Richard Norman and A. Simon Pickard
Additional contact information
Ruixuan Jiang: Center for Observational and Real-World Evidence, Merck & Co., Inc, Rahway, NJ, USA
Eleanor Pullenayegum: Child Health Evaluative Sciences, Hospital for Sick Children, Toronto, Canada
James W. Shaw: Patient-reported Outcomes Assessment, Bristol-Myers Squibb, Princeton, NJ, USA
Axel Mühlbacher: Duke Department of Population Health Sciences and Duke Global Health Institute, Duke University, Durham, NC, USA, Germany
Todd A. Lee: Department of Pharmacy Systems, Outcomes, and Policy, University of Illinois at Chicago College of Pharmacy, Chicago, IL, USA
Surrey Walton: Department of Pharmacy Systems, Outcomes, and Policy, University of Illinois at Chicago College of Pharmacy, Chicago, IL, USA
Thomas Kohlmann: Institute for Community Medicine, Medical University Greifswald, Greifswald, Germany
Richard Norman: Curtin University School of Public Health, Perth, Australia
A. Simon Pickard: Department of Pharmacy Systems, Outcomes, and Policy, University of Illinois at Chicago College of Pharmacy, Chicago, IL, USA

Medical Decision Making, 2023, vol. 43, issue 6, 667-679

Abstract: Introduction Discrete choice experiments (DCE) are increasingly being conducted using online panels. However, the comparability of such DCE-based preferences to traditional modes of data collection (e.g., in-person) is not well established. In this study, supervised, face-to-face DCE was compared with its unsupervised, online facsimile on face validity, respondent behavior, and modeled preferences. Methods Data from face-to-face and online EQ-5D-5L health state valuation studies were compared, in which each used the same experimental design and quota sampling procedure. Respondents completed 7 binary DCE tasks comparing 2 EQ-5D-5L health states presented side by side (health states A and B). Data face validity was assessed by comparing preference patterns as a function of the severity difference between 2 health states within a task. The prevalence of potentially suspicious choice patterns (i.e., all As, all Bs, and alternating As/Bs) was compared between studies. Preference data were modeled using multinomial logit regression and compared based on dimensional contribution to overall scale and importance ranking of dimension-levels. Results One thousand five Online respondents and 1,099 face-to-face screened (F2F S ) respondents were included in the main comparison of DCE tasks. Online respondents reported more problems on all EQ-5D dimensions except for Mobility. The face validity of the data was similar between comparators. Online respondents had a greater prevalence of potentially suspicious DCE choice patterns ([Online]: 5.3% [F2F S ] 2.9%, P  = 0.005). When modeled, the relative contribution of each EQ-5D dimension differed between modes of administration. Online respondents weighed Mobility more importantly and Anxiety/Depression less importantly. Discussion Although assessments of face validity were similar between Online and F2F S , modeled preferences differed. Future analyses are needed to clarify whether differences are attributable to preference or data quality variation between modes of data collection.

Keywords: EQ-5D; discrete choice experiment; face-to-face; online (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:43:y:2023:i:6:p:667-679

DOI: 10.1177/0272989X231171912

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