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Calculating Preference Weights for the Labor and Delivery Index: A Discrete Choice Experiment on Women's Birth Experiences

机译:计算分娩指数的偏好权重:关于女性分娩经历的离散选择实验

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Objective: The aim of this study was to calculate preference weights for the Labor and Delivery Index (LADY-X) to make it suitable as a utility measure for perinatal care studies. Methods: In an online discrete choice experiment, 18 pairs of hypothetical scenarios were presented to respondents, from which they had to choose a preferred option. The scenarios describe the birth experience in terms of the seven LADY-X attributes. A D-efficient discrete choice experiment design with priors based on a small sample (N = 110) was applied. Two samples were gathered, women who had recently given birth and subjects from the general population. Both samples were analyzed separately using a panel mixed logit (MMNL) model. Using the panel mixed multinomial logit (MMNL) model results and accounting for preference heterogeneity, we calculated the average preference weights for LADY-X attribute levels. These were transformed to represent a utility score between 0 and 1, with 0 representing the worst and 1 representing the best birth experience. Results: In total, 1097 women who had recently given birth and 367 subjects from the general population participated. Greater value was placed on differences between bottom and middle attribute levels than on differences between middle and top levels. The atisibutes that resulted in larger utility increases than the other attributes were "feeling of safety" in the sample of women who had recently given birth and "feeling of safety" and "availability of professionals" in the general population sample. Conclusions: By using the derived preference weights, LADY-X has the potential to be used as a utility measure for perinatal (cost-) effectiveness studies.
机译:目的:本研究的目的是计算分娩指数 (LADY-X) 的偏好权重,使其适合作为围产期护理研究的效用衡量标准。方法:在一项在线离散选择实验中,向受访者展示了 18 对假设场景,他们必须从中选择一个首选选项。这些场景根据七个 LADY-X 属性来描述分娩体验。采用基于小样本(N = 110)的先验D高效离散选择实验设计。收集了两个样本,即最近分娩的妇女和普通人群的受试者。使用面板混合对数 (MMNL) 模型分别分析了两个样品。使用面板混合多项式logit(MMNL)模型结果并考虑偏好异质性,我们计算了LADY-X属性水平的平均偏好权重。这些被转换为表示介于 0 和 1 之间的效用分数,其中 0 表示最差,1 表示最佳分娩体验。结果:共有 1097 名近期分娩的妇女和 367 名普通人群受试者参加。与中层和上层之间的差异相比,对底层和中层属性级别之间的差异给予了更大的重视。导致效用增加幅度大于其他属性的因素是最近分娩妇女样本中的“安全感”和一般人群样本中的“安全感”和“专业人员的可用性”。结论:通过使用衍生的偏好权重,LADY-X 有可能用作围产期(成本)有效性研究的效用测量。

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