Please use this identifier to cite or link to this item:
http://dx.doi.org/10.25673/101546
Title: | Providing laypeople with results from dynamic infectious disease modelling studies affects their allocation preference for scarce medical resources-a factorial experiment |
Author(s): | Rübsamen, Nicole Garcia Voges, Benno Castell, Stefanie Klett-Tammen, Carolina Judith Oppliger, Jérôme Krütli, Pius Smieszek, Timo Mikolajczyk, Rafael Karch, André |
Issue Date: | 2022 |
Type: | Article |
Language: | English |
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. |
URI: | https://opendata.uni-halle.de//handle/1981185920/103504 http://dx.doi.org/10.25673/101546 |
Open Access: | Open access publication |
License: | (CC BY 4.0) Creative Commons Attribution 4.0 |
Journal Title: | BMC public health |
Publisher: | BioMed Central |
Publisher Place: | London |
Volume: | 22 |
Original Publication: | 10.1186/s12889-022-13000-7 |
Appears in Collections: | Open Access Publikationen der MLU |
Files in This Item:
File | Description | Size | Format | |
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s12889-022-13000-7.pdf | 1.63 MB | Adobe PDF | View/Open |