Examines methods for tailoring health messages to users based on mathematical models employed in online marketing of commercial goods. Public health campaigns that seek to change behavior are successful in large part when the messages deployed are themselves effective by being attuned to the target audience and -- when possible -- the target individual. Conventional approaches to the design of effective messages in health behavior change -- primarily experimental and factorial in approach -- have moved too slowly both empirically and theoretically leaving message design unprincipled and intuitive. The research proposed radically alters the approach to message design and selection by developing empirically based “recommendation algorithms” based on a model of commercial product recommendation and applied and tested on a large archive of smoking cessation messages.
Constructing Recommender Systems for Effective Health Messages: Smoking Cessation
National Institute of Health
23 Sep 2011 to 31 Jul 2015