An Assessment of Public Preferences for Newborn Screening Using Best Worst Scaling
An Assessment of Public Preferences for Newborn Screening Using Best Worst Scaling
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DOI：
10.1016/j.jpeds.2018.05.035
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发表时间：
2018-10-01
影响因子：
5.1
通讯作者：
Prosser, Lisa A.
中科院分区：
文献类型：
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作者：
Tarini, Beth A.;Simon, Norma-Jean;Prosser, Lisa A.
目的确定和量化公众对新生儿筛查条件属性的偏好。研究设计我们进行了一项在线全国调查（n = 502），以评估对候选新生儿筛查条件属性的偏好。受访者被提供了假设的条件配置文件，这些配置文件使用10个属性定义，每个属性有2-6个级别。参与者表明他们是否会建议筛查一种疾病，以及在做出这个决定时，哪些疾病属性最重要，哪些最不重要（最佳-最差缩放）。根据条件推荐（推荐或不推荐筛查）计算差异评分并分层。使用回归分析来评估属性对选择筛选或不筛选的影响。结果诊断出的婴儿数量对于推荐新生儿筛查的人来说是重要的，而开始治疗的年龄对于不推荐新生儿筛查的人来说是重要的。成本被认为是一个关键属性，治疗效果和通过新生儿筛查做出诊断的影响对两组都不太重要。结论通过调查方法确定的公众偏好提供了对新生儿筛查的充分基线了解，可用于为新生儿筛查决策提供信息。
Objective To identify and quantify public preferences for attributes of newborn screening conditions.Study design We conducted an online national survey of the public (n = 502) to evaluate preferences for attributes of candidate newborn screening conditions. Respondents were presented with hypothetical condition profiles that were defined using 10 attributes with 2-6 levels per attribute. Participants indicated whether they would recommend screening for a condition and which condition attributes were most and least important when making this decision (best-worst scaling). Difference scores were calculated and stratified by condition recommendation (recommend or not recommend for screening). Regression analyses were used to evaluate the effect of attributes on choice to screen or not screen.Results The number of babies diagnosed was important to those who would recommend newborn screening for a profile, and age at which the treatment would start was important to those who would not recommend newborn screening. Cost was considered to be a key attribute, and treatment effectiveness and impact of making the diagnosis through newborn screening were of low importance for both groups.Conclusion Public preferences identified through survey methods that provide an adequate baseline understanding of newborn screening can be used to inform newborn screening decisions.