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Longitudinal risk factors for intimate partner violence among men in treatment for alcohol use disorders
Casey T Taft1, Timothy J O'Farrell, Susan Doron-LaMarca
1National Center for PTSD, VA Boston Healthcare System, and Department of Psychiatry, Boston University School of Medicine, Boston, MA 02130, USA. casey.taft@va.gov
Objective:
This study examined static and time-varying risk factors for perpetration of intimate partner violence (IPV) among men in treatment for alcohol use disorders.
Method:
Participants were 178 men diagnosed with alcohol abuse or dependence and their partners. Most (85%) of the men were European American; their average age was 41.0 years. Participants completed measures assessing initial alcohol problem severity, baseline beliefs related to alcohol use, antisocial personality characteristics, alcohol and drug use, relationship adjustment, and IPV.
Results:
According to couples' reconciled reports, 42% of participants perpetrated IPV at baseline. Among this group, the IPV recurrence rate was 43% at 6-month follow-up and 36% at 12-month follow-up. For participants without IPV perpetration at baseline, new incidence of IPV was 15% and 7% at the 6-month and 12-month follow-up points, respectively. Fixed marker predictors of IPV rates included baseline alcohol problem severity variables, baseline beliefs related to alcohol use, and antisocial personality characteristics. Variable risk factor predictors included alcohol and drug use variables, relationship adjustment factors, and anger. Alcohol use variables and anger were associated with new incidents of IPV among those without reported IPV at baseline only.
Conclusions:
Findings suggest that assessing and monitoring IPV occurrence by both partners is important for men in treatment for alcohol use disorders. Results indicate vulnerability factors that may identify individuals at risk for IPV and provide targets for IPV prevention among those with alcohol use disorders. These findings can aid in the development of more comprehensive models that more precisely predict IPV.
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