Abstract

The psychometric paradigm has dominated the field of empirical work analysing risk perceptions. In this paper, we use an alternative method, Best-Worst Scaling (BWS), to elicit relative risk perceptions concerning potentially unsafe domestic food behaviours. We analyse heterogeneity in those risk perceptions via estimation of latent class models. We identify 6 latent segments of differing risk perception profiles with the probability of membership of those segments differing between experts and the lay public. The BWS method provides a practical approach to assessing relative risks as the choices made by the participants and subsequent analysis have a strong theoretical basis. It does so without the influence of scale bias, the cognitive burden of ranking a large number of items or issues of aggregation of data, often associated with the more commonly used psychometric paradigm. We contend that BWS, in conjunction with latent class modelling, provides a powerful method for eliciting risk rankings and identifying differences in these rankings in the population.

摘要

心理测量范式主导了分析风险认知的实证工作领域。在本文中，我们使用了另一种方法，即最佳-最差比例 (BWS)，以得出有关潜在不安全家庭食品行为的相对风险认知。我们通过潜在类别模型的估计来分析这些风险感知的异质性。我们确定了 6 个具有不同风险感知概况的潜在部分，这些部分的成员资格在专家和普通公众之间存在差异。BWS 方法提供了一种评估相对风险的实用方法，因为参与者所做的选择和随后的分析具有强大的理论基础。它没有规模偏差的影响，没有对大量项目进行排序的认知负担或数据聚合问题，通常与更常用的心理测量范式相关联。我们认为，BWS 与潜在类别建模相结合，提供了一种强大的方法来引发风险排名并识别这些排名在人群中的差异。