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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
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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8940588/ https://www.ncbi.nlm.nih.gov/pubmed/35321669 http://dx.doi.org/10.1186/s12889-022-13000-7 |
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author | Rübsamen, Nicole Garcia Voges, Benno Castell, Stefanie Klett-Tammen, Carolina Judith Oppliger, Jérôme Krütli, Pius Smieszek, Timo Mikolajczyk, Rafael Karch, André |
author_facet | Rübsamen, Nicole Garcia Voges, Benno Castell, Stefanie Klett-Tammen, Carolina Judith Oppliger, Jérôme Krütli, Pius Smieszek, Timo Mikolajczyk, Rafael Karch, André |
author_sort | Rübsamen, Nicole |
collection | PubMed |
description | 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-13000-7. |
format | Online Article Text |
id | pubmed-8940588 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-89405882022-03-23 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 BMC Public Health Research 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-13000-7. BioMed Central 2022-03-23 /pmc/articles/PMC8940588/ /pubmed/35321669 http://dx.doi.org/10.1186/s12889-022-13000-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Rübsamen, Nicole Garcia Voges, Benno Castell, Stefanie Klett-Tammen, Carolina Judith Oppliger, Jérôme Krütli, Pius Smieszek, Timo Mikolajczyk, Rafael Karch, André Providing laypeople with results from dynamic infectious disease modelling studies affects their allocation preference for scarce medical resources—a factorial experiment |
title | Providing laypeople with results from dynamic infectious disease modelling studies affects their allocation preference for scarce medical resources—a factorial experiment |
title_full | Providing laypeople with results from dynamic infectious disease modelling studies affects their allocation preference for scarce medical resources—a factorial experiment |
title_fullStr | Providing laypeople with results from dynamic infectious disease modelling studies affects their allocation preference for scarce medical resources—a factorial experiment |
title_full_unstemmed | Providing laypeople with results from dynamic infectious disease modelling studies affects their allocation preference for scarce medical resources—a factorial experiment |
title_short | Providing laypeople with results from dynamic infectious disease modelling studies affects their allocation preference for scarce medical resources—a factorial experiment |
title_sort | providing laypeople with results from dynamic infectious disease modelling studies affects their allocation preference for scarce medical resources—a factorial experiment |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8940588/ https://www.ncbi.nlm.nih.gov/pubmed/35321669 http://dx.doi.org/10.1186/s12889-022-13000-7 |
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