Lifestyle-related diseases such as obesity are highly multifactorial/multiclausal. The full set of factors that both predict and explain a particular behavior we term the "Conductome". Although psychological variables can play an important role in the Conductome, they should be compared and contrasted with other variable types, associated with other disciplines, to evaluate their ability to predict and explain those behaviors that lead to such diseases, as well as aid in the search for interventions to mitigate them. In this talk I will introduce the Conductome and show the necessity of using "Hybrid Intelligence" - an optimal combination of Artificial and Human Intelligence - to construct it. I will use several highly multifactorial data sets that combine information from a set of well-known psychological constructs with demographic, epidemiologic, social, economic and physiological information in order to better understand the etiology of unhealthy behaviors and their consequences, such as obesity, as well as to understand the role and relative importance of psychological factors when compared to other variable types.