Domestic violence is the leading cause of injuries to women aged 15-44 years. Mandated treatment of intimate partner violence (IPV), or batterer treatment, is (a) very costly, (b) generally focused on men, and (c) relatively ineffective; furthermore, men also are victims of IPV, and women’s IPV is little addressed. There is evidence that women’s physical aggression toward a partner makes them more likely to sustain an injury in retaliation. Recent studies suggest the importance of individual psychopathology as a predictor of aggression for women. Substance use is associated with IPV and frequently has been considered a contributing factor for men, but this issue has been little examined in women. The purpose of this study was to examine the association of substance use, including nicotine, alcohol, marijuana, and other illicit drugs, and IPV for a sample of 160 generally lower socioeconomic status women studied over a number of years with the same male partner in the OYS-Couples study. We collected new data to provide additional diagnostic information on both the women and their partners’ current and lifetime substance use. We tested the validity of different explanations of the observed associations between substance use and IPV. The findings have important implications regarding the possible efficacy of substance abuse prevention and treatment programs as indirect prevention and treatment for women’s IPV.Year Project Began: 2009
Funder: ARRA Challenge Grant (National Institute on Drug Abuse)
Alan Feingold, Ph.D.
Oregon Social Learning Center
Active Research Projects
Primary Research and Clinical Interests
Dr. Feingold came to OSLC after having worked for nearly a decade as a biostatistician in the Division of Substance Abuse at the Department of Psychiatry at the Yale University School of Medicine. His main current interest at OSLC is in developing and validating new methods of effect sizes (and confidence intervals for these new effect sizes) to convey the practical significance of findings from latent growth, multilevel, and mixture modeling of continuous and categorical outcomes in the alcohol field. Developing and validating effect sizes for the indirect effects from mediation analysis with different kinds of variable distributions is a key aim of his NIAAA-funded work.