Agent-Based Modeling of Ecological Niche Theory and Assortative Drinking

Fitzpatrick, Ben; Martinez, Jason

doi:10.18564/jasss.1926

Cited by 14 publications

(25 citation statements)

References 31 publications

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“…The connecting theory needed to specify relationships between drinking agents and alcohol markets has begun to be developed in agent-based computational models [1][8]. Yet there has been little empirical consideration of the plausible impacts of macro-ecological features of drinking environments on individual drinking behaviors.…”

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confidence: 99%

Testing a social ecological model of alcohol use: the California 50-city study

2014

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Background and aims Social ecological theories suggest that greater community alcohol availability and individual drinker characteristics should jointly affect drinking patterns and the use of drinking contexts. We assessed relationships of demographic and personality characteristics of individual drinkers and environmental characteristics at the city-level to measures of drinking patterns and use of drinking contexts. Design Multilevel statistical analyses of archival and survey data from 50 cities in California, USA. Settings An ecological sample of 50 geographically distinct cities with populations from 50,000 to 500,000 persons. Participants General population telephone survey of 8,553 adults 18 years of age and older stratified by cities. Measurements Archival data on city-level alcohol outlet densities were combined with individual survey data identifying community conditions, individual demographic and psychosocial characteristics, frequencies of use of drinking contexts and drinking patterns. Findings Greater on-premise outlet densities were related to greater drinking frequencies (b=2.967, z=4.688, p<0.001) and volumes (b=0.627, z=3.394, p<0.001), and use of on-premises drinking places (bars, b=0.334, z=2.645, p<0.006, and restaurants, b=0.171, z=2.770, p=0.005). Individual demographic and personality characteristics were related to drinking and use of drinking contexts. For example, greater impulsivity was related to greater drinking frequencies (b=0.200, z=2.088, p=0.023) and logged quantities (b=0.015, z=2.009, p=0.026), and proportionately more drinking at bars (b=0.033, z=2.016, p=0.026) and parties (b=0.171, z=2.770, p=0.004). Conclusion Community availability of alcohol and individual drinker characteristics appear to act jointly to affect drinking levels and use of drinking contexts in California, USA. These effects may increase risks related to drinking in some contexts (e.g., bars) much more than others (e.g., at friends’ or relatives’ homes).

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confidence: 99%

Testing a social ecological model of alcohol use: the California 50-city study

2014

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“…Although conceptual models and theory have long guided social science in general (Lewin, 1951;Kuhn, 1974) and alcohol studies specifically (Denzin, 1987;Gusfield, 1996), models for drinking events rarely build on previous work, transcend theoretical streams, or acknowledge dynamics and complexity (e.g., nonlinearity, random effects, and feedback loops). Although there is a small body of system dynamic alcohol studies at the community level (Gorman et al, 2001;Gruenewald, 2006;Holder, 2006;Scribner et al, 2009) and some recent notable exceptions employing agent-based modelling (Gorman et al, 2006;Fitzpatrick and Martinez, 2012) at the population and event levels, dynamical modelling in alcohol research is still largely underdeveloped. At the event level, this may well be an artefact of the difficultly of measuring drinking events (Clapp et al, 2007;Kuntsche et al, 2014).…”

Section: What Is a Drinking Event? Toward A System Dynamics Modelmentioning

confidence: 99%

A System Dynamic Model of Drinking Events: Multi‐Level Ecological Approach

et al. 2018

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Drinking events are dynamic. The interactions of individuals, groups, and the environment as they relate to drinking behaviour are overwhelmingly complex. This paper presents an empirically grounded dynamic conceptual model to better understand drinking events. Using a collaborative mixed‐methods approach, we developed an aggregated system dynamic model of drinking events. The process began with identification of system elements and boundaries. Once the first aspects of the model were completed, we constructed a causal loop diagram, an aggregated causal loop diagram, and stock and flow diagrams. Finally, we developed and ran computer simulations of the dynamical models. The model presented here can be used to guide future agent‐based, system dynamics, or differential equation‐based models. Such models can help inform future empirical work and modelling to increase the understanding of drinking events and provide solutions to the problems that happen proximal to these events. Copyright © 2018 John Wiley & Sons, Ltd.

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“…Internationally, the Sheffield Alcohol Policy Model (SAPM) delves into the consequences of alcohol consumption in Great Britain . Additionally, agent‐based modeling has been employed to examine how environmental and social dynamics influence general population and college drinking , as well as spatial dynamics and social processes of college drinking events . There are even fewer instances of system dynamics modeling approaches .…”

Section: A Paradigm Shift In Alcohol Prevention Researchmentioning

confidence: 99%