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Providing laypeople with results from dynamic infectious disease modelling studies affects their allocation preference for scarce medical resources-a factorial experiment.
Rübsamen, Nicole; Garcia Voges, Benno; Castell, Stefanie; Klett-Tammen, Carolina Judith; Oppliger, Jérôme; Krütli, Pius; Smieszek, Timo; Mikolajczyk, Rafael; Karch, André.
Afiliação
  • Rübsamen N; Institute of Epidemiology and Social Medicine, University of Münster, Albert-Schweitzer-Campus 1, 48149, Münster, Germany. ruebsame@uni-muenster.de.
  • Garcia Voges B; Department of Epidemiology, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany. ruebsame@uni-muenster.de.
  • Castell S; Department of Epidemiology, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany.
  • Klett-Tammen CJ; Department of Epidemiology, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany.
  • Oppliger J; Department of Epidemiology, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany.
  • Krütli P; Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland.
  • Smieszek T; Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland.
  • Mikolajczyk R; MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College School of Public Health, London, UK.
  • Karch A; Modelling and Economics Unit, Statistics, Modelling, and Economics Department, Public Health England, London, UK.
BMC Public Health ; 22(1): 572, 2022 03 23.
Article em En | MEDLINE | ID: mdl-35321669
ABSTRACT

BACKGROUND:

Allocation 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.

METHODS:

In 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.

RESULTS:

Presence 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.

CONCLUSIONS:

Providing 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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças Transmissíveis / Alocação de Recursos Tipo de estudo: Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças Transmissíveis / Alocação de Recursos Tipo de estudo: Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article