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为非专业人士提供来自动态传染病建模研究的结果会影响他们对稀缺医疗资源分配偏好的事实——一项析因实验。

Providing laypeople with results from dynamic infectious disease modelling studies affects their allocation preference for scarce medical resources-a factorial experiment.

机构信息

Institute of Epidemiology and Social Medicine, University of Münster, Albert-Schweitzer-Campus 1, 48149, Münster, Germany.

Department of Epidemiology, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany.

出版信息

BMC Public Health. 2022 Mar 23;22(1):572. doi: 10.1186/s12889-022-13000-7.

DOI:10.1186/s12889-022-13000-7
PMID:35321669
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8940588/
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.

摘要

背景

稀缺医疗资源的分配可以基于不同的原则。在像新发传染病这样的医疗资源短缺的特定情况下,尚未研究医学外行更倾向于哪种分配方案,以及提供基于模型研究的分配方案对预期人群水平效果的信息如何影响这些选择。我们调查了传染病模型结果的战略沟通的潜在益处。

方法

在一项双向析因实验(n=878 名参与者)中,我们调查了疾病的预后或基于动态传染病模型研究的预期对死亡率的人群水平影响的信息是否会影响对未指定性传播感染的预防和治疗的首选分配方案的选择。对选择特定分配方案的原因的定性分析补充了我们的结果。

结果

“分配方案的人群水平效果信息”这一因素的存在大大增加了选择使人群总体伤害最小化的资源分配系统的概率,而预后则不会影响分配选择。选择分配方案的主要原因因方案而异,但在接受和未接受基于模型的预期人群水平效果信息的人群中没有差异。

结论

提供来自动态传染病模型研究的预期人群水平效果的信息导致分配方案的选择有了很大的不同。这一发现支持了在决策过程和沟通策略中纳入基于模型的信息的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3451/8941733/49d285d136b7/12889_2022_13000_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3451/8941733/c8595539eed8/12889_2022_13000_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3451/8941733/6cba16c7b2d5/12889_2022_13000_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3451/8941733/49d285d136b7/12889_2022_13000_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3451/8941733/c8595539eed8/12889_2022_13000_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3451/8941733/6cba16c7b2d5/12889_2022_13000_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3451/8941733/49d285d136b7/12889_2022_13000_Fig3_HTML.jpg

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