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arXiv · 2011.01876

The Impact of Individual's Ecological Factors on the Dynamics of Alcohol Drinking among Arizona State University Students: An Application of the Survey Data-driven Agent-based Model

Abstract

College-aged students are one of the most vulnerable populations to high-risk alcohol drinking behaviors that could cause them consequences such as injury or sexual assault. An important factor that may influence college students' decision on alcohol drinking behavior is socializing at certain contexts across university environment. The present study aims to identify and better understand ecological conditions driving the dynamics of distribution of alcohol use among college-aged students. To this end, a pilot study is conducted to evaluate students' movement patterns to different contexts across the Arizona State University (ASU) campus, and to use its results to develop an agent-based simulation model designed for examining the role of environmental factors on development and maintenance of alcohol drinking behavior by a representative sample of ASU students. The proposed model that resembles an approximate reaction-diffusion model accounts for movement of agents to various contexts (i.e. diffusion) and alcohol drinking influences within those contexts (i.e., reaction) via a SIR-type model. Of the four most visited contexts at ASU Tempe campus -- Library, Memorial Union, Fitness Center, and Dorm -- the context with the highest visiting probability, Memorial Union, is the most influential and most sensitive context (around $16$ times higher impact of alcohol related influences than the other contexts) on spreading alcohol drinking behavior. Our findings highlight the crucial role of socialization at local environments on the dynamics of students' alcohol use as well as on the long-term prediction of the college drinking prevalence.

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BibTeXRIS

Asma Azizi, Anamika Mubayi, Anuj Mubayi. 2020-10-31. The Impact of Individual's Ecological Factors on the Dynamics of Alcohol Drinking among Arizona State University Students: An Application of the Survey Data-driven Agent-based Model. https://arxiv.org/abs/2011.01876

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