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May 31, 2026Social Science & Medicine0 citationsOpen Access

Fit for Purpose? Assessing the Robustness of Discrete Choice Experiment Designs in the Context of Evolving Health Technologies

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MGMesfin G. GenieVWVerity WatsonMSMichaël Schwarzinger

Key Points

  • This research aims to understand how changing health technologies affect preferences in discrete choice experiments. It investigates whether simplifications in design alter the interpretation of data.
  • Between-sample discrete choice experiment (DCE) was conducted.
  • Varying attribute and level complexity were tested across different samples.
  • Effects of omitting attributes and simplifying levels on choice consistency were analyzed.
  • Omitting attributes and simplifying levels did not change their relative importance.
  • Higher specification complexity led to reduced choice consistency.
  • Design choices can significantly influence the robustness of DCE data in health contexts.

Abstract

• In fast-changing settings, whether preferences remain robust as knowledge evolves is unclear. • A between-sample DCE assessed effects of varying attribute and level complexity. • Omitting attributes and simplifying levels did not alter relative importance. • Greater specification complexity was associated with reduced choice consistency. • Design choices in evolving health technologies can affect DCE data robustness.

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Cite This Study

Genie et al. (2026) studied this question.

synapsesocial.com/papers/6a1bd2375783ba022b6fdacehttps://doi.org/10.1016/j.socscimed.2026.119463
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