Online Program

326453
Conjoint analysis: What can it do for public health?


Wednesday, November 4, 2015 : 1:10 p.m. - 1:30 p.m.

Lauren Wallar, Department of Population Medicine, University of Guelph, Guelph, ON, Canada
Andrew Papadopoulos, BASc, MBA, PhD, Department of Population Medicine, University of Guelph, Guelph, ON, Canada
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.

Learning Areas:

Biostatistics, economics
Implementation of health education strategies, interventions and programs
Planning of health education strategies, interventions, and programs
Program planning
Public health or related research

Learning Objectives:
Describe conjoint analysis as a method for predicting and measuring health-related choices and behaviours

Keyword(s): Public Health Research, Decision-Making

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am a PhD candidate in Epidemiology. My doctoral dissertation focuses on the application of a conjoint analysis method termed maximum difference scaling to quantify preferences for local community wellness, provincial environmental health education, and provincial environmental health information technology.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.