Discrete choice experiments (DCEs) are used to quantify the preferences of specified sample populations for different aspects of a good or service and are increasingly used to value interventions and services related to healthcare. Systematic reviews of healthcare DCEs have focussed on the trends over time of specific design issues and changes in the approach to analysis, with a more recent move towards consideration of a specific type of variation in preferences within the sample population, called taste heterogeneity, noting rises in the popularity of mixed logit and latent class models. Another type of variation, called scale heterogeneity, which relates to differences in the randomness of choice behaviour, may also account for some of the observed 'differences' in preference weights. The issue of scale heterogeneity becomes particularly important when comparing preferences across subgroups of the sample population as apparent differences in preferences could be due to taste and/or choice consistency. This primer aims to define and describe the relevance of scale heterogeneity in a healthcare context, and illustrate key points, with a simulated data set provided to readers in the Online appendix.