Conjoint analysis: What can it do for public health?

Delivery of programs and services is one of the primary functions of any public health system that aims to enhance population health and wellness. Although much is known about what contributes to a healthy lifestyle, the public continues to make choices and engage in behaviours that lead to poor health outcomes. Public health programs and services seek to alter these choices and behaviours but sometimes with limited success.

Applied market research methods have been successfully used in the business world for decades to predict and affect consumer choices and behaviours. One of these market research methods is termed conjoint analysis. Conjoint analysis quantifies consumer preference by statistically analyzing the choices that individuals make when presented with different products or services. Multinomial logit, latent class and Hierarchical Bayes are statistical methods used to analyze choice at the population-, sub-population- and individual-level, respectively.

In this presentation, the presenter will introduce conjoint analysis as an applied method for determining preference for public health programs and services using a case study of community wellness. By having a better understanding of what the public prefers with respect to the design and delivery of programs and services, public health practitioners are better positioned to positively influence health choices and behaviours and maximize population health outcomes.