ArticleBMC public health2022
Providing laypeople with results from dynamic infectious disease modelling studies affects their allocation preference for scarce medical resources-a factorial experiment.
Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundAllocation of scarce medical resources can be based on different principles. It has not yet been investigated which allocation schemes are preferred by medical laypeople in a particular situation of medical scarcity like an emerging infectious disease and how the choices are affected by providing information about expected population-level effects of the allocation scheme based on modelling studies. We investigated the potential benefit of strategic communication of infectious disease modelling results.
methodsIn a two-way factorial experiment (n = 878 participants), we investigated if prognosis of the disease or information about expected effects on mortality at population-level (based on dynamic infectious disease modelling studies) influenced the choice of preferred allocation schemes for prevention and treatment of an unspecified sexually transmitted infection. A qualitative analysis of the reasons for choosing specific allocation schemes supplements our results.
resultsPresence of the factor "information about the population-level effects of the allocation scheme" substantially increased the probability of choosing a resource allocation system that minimized overall harm among the population, while prognosis did not affect allocation choices. The main reasons for choosing an allocation scheme differed among schemes, but did not differ among those who received additional model-based information on expected population-level effects and those who did not.
conclusionsProviding information on the expected population-level effects from dynamic infectious disease modelling studies resulted in a substantially different choice of allocation schemes. This finding supports the importance of incorporating model-based information in decision-making processes and communication strategies.
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