Investigating heterogeneity in food risk perceptions using best-worst scaling

Caroline Millman, Dan Rigby, Davey L. Jones

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)1288-1303
Number of pages16
JournalJournal of Risk Research
Issue number10
Early online date23 Nov 2020
Publication statusPublished - 2021


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