Modeling Daily Partner Violence and Substance Use Based upon Couple's Reporting.

Abstract

While agent-based models (ABMs) have successfully modeled violence and women's decision-making, they relied upon studies of her daily reports of violence and household environment; these models were not based upon descriptions of his emotions and perceptions. The purpose of this study was to improve our understanding of the triggers of violent events within violent relationships through agent-based modeling by including men's perceptions and emotions. An agent-based model was created of couples with history of violence based upon results of a study involving multiple time series of partner violence, including couples' daily reports of their emotions and perceptions. To explore factors that may alter model results, seven continuous variable parameters were created based upon significant (p ≤ .05) but discrepant (opposite directions) in prior studies. To assess the potential impact that influencing factors such as random stress as well as his and her feelings and behaviors could have on violence and stalking, the impact of these factors was also assessed. Results found that, at baseline, which included no extremes in variable parameters, no violence emerged. One prior-day→same-day relationship (HerConcern→HerConcern) was particularly important in this ABM. Men's and women's drug use and refraining from arguments had little impact on any outcome, but his and her alcohol use, his sense of insult and her violence all had significant effects. In fact, women's alcohol use interacted with other influencing variables and was a source of atypical patterns. In conclusion, incorporating men's perceptions into an ABM of partner violence resulted in important differences compared with ABMs based solely on women's input. Not only were women's daily concerns about the effect of violence on children was critical to results, but this ABM demonstrated the complexity of partner violence in response to influences as illustrated by contextual dependence, interaction effects and synergy.