Tanenbaum, Hilary (2017). An agent-based modeling approach to explore personality traits and obesity development.
The numerous, interacting factors involved in the etiological web of obesity development warrant examination with modeling methods that can adeptly reflect these dynamics. Improvements in computer processing speed, combined with the development of user-friendly software, have afforded an opportunity for exploration with Agent-Based Models (ABMs), a complex systems approach that uses computer-generated algorithms to simulate the behavior of individual real-world entities. This method readily incorporates heterogeneous populations, stochasticity and non-linear variables, making it well-suited for obesity research. In addition, ABMs provide a blank canvas on which to experiment with potential interventions or investigate counterfactuals to support existing theories of causality. Although personality traits and obesity development have been linked, an ABM has not yet been employed to evaluate these relationships. Using data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) and AnyLogic software (v. 7.6), this dissertation introduces a novel methodological approach for designing an ABM to evaluate links between personality and obesity, creating the agent population directly as a one-to-one representation of the real-world study participants. After verifying and validating the baseline model, theoretical personality trait interventions are simulated to assess the impact of these changes on obesity development. The effects of a single trait alteration are first examined, followed by an exploration of combined trait changes. The findings from the experimental simulations reveal information about potential interventions, highlighting important differences between sexes, identifying specific subsets of the population that would benefit most from a particular approach, and uncovering possible adverse outcomes which might otherwise remain hidden. Collectively, the results of the studies support ABMs as a valuable tool for gaining insight into the dynamic factors at play in obesity development, as well as for determining the most effective strategies for prevention.
Applied sciences Psychology Health and environmental sciences Agent-based model Obesity Personality Information Technology Public health Behavioral Sciences 0489:Information Technology 0602:Behavioral Sciences 0573:Public health
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Health Promotion Sciences
Xie, Bin Hilton Brian
Claremont Graduate University
City of Publication