More NCJRS Abstracts, August 16, 2007

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NCJ 219163
Jacquelyn C. Campbell; Nancy Glass; Phyllis W. Sharps; Kathryn Laughon; Tina Bloom
Intimate Partner Homicide: Review and Implications of Research and Policy
Trauma, Violence, & Abuse Volume:8 Issue:3 Dated:July 2007 Pages:246 to 269

This literature review presents and critiques the research evidence pertinent to major risk factors for intimate-partner homicide (IPH) in general and for intimate-partner homicide of women (femicide) in particular. The number-one risk factor for IPH, whether the victim is a male or female, is at least one previous incident of domestic violence. Other major risk factors for IPH are access to a gun, estrangement of the partners, threats to kill and threats with a weapon, and nonfatal strangulation. Research shows that women are nine times more likely to be killed by an intimate partner (husband, boyfriend, same-sex partner, or ex-partner) than by a stranger. IPH has decreased significantly during the past 30 years for both male and female victims, with the decrease being greatest for male victims. The increase in domestic violence resources and policy changes regarding domestic violence and gun access are partly responsible for this decrease. Unemployment is the primary demographic risk factor for IP femicide, when compared to race, income, and education. Risk factors for IP homicide-suicide, which is almost always a female victim and male perpetrator, include prior mental health problems in the perpetrator and other risk factors for IPH without suicide. More research is needed on same-sex IPHs, attempted IPHs, and on policies and practices that prevent IPHs. The literature review presents research related to IPH during the past 10 years with implications for the health care, advocacy, and criminal justice systems. Critiques of individual studies are mentioned as reviewed, with an overall critique of the studies in the field, gaps in knowledge, and recommendations for policy and future research presented at the conclusion of the article. 1 table, 1 figure, and 104 references

NCJ 219211
Grace M. Barnes; Joseph H. Hoffman; John W. Welte; Michael P. Farrell; Barbara A. Dintcheff
Adolescents' Time Use: Effects on Substance Use, Delinquency and Sexual Activity
Journal of Youth and Adolescence Volume:36 Issue:5 Dated:July 2007 Pages:697 to 710

This study analyzed the effects of adolescent time use on heavy alcohol use, cigarette smoking, illicit drug use, delinquency, and sexual activity. Results indicated that the two factors most predictive of adolescent problem behaviors were family time and peer time. Specifically, family time emerged as a protective factor against all five problem behaviors under analysis while peer time emerged as a significant risk factor for all five problem behaviors. Family time, however, did not appear to buffer the relationship between unsupervised peer time and problem behaviors. These findings are consistent with both social control theory and the routine activity perspective. The results suggest that social policies that encourage parents and adolescents to spent social time together in the company of other adults and adolescents may facilitate the prevention of substance abuse, delinquency, and risky sexual behavior in older adolescents. Future research is needed to understand why higher levels of deviance seem to be associated with time spent alone/relaxing. Data were drawn from the responses of 606 adolescents to wave 3 of a 6-wave longitudinal study that focused on the development of alcohol misuse and related problem behaviors. Participants were recruited from western New York using random-digit-dialing telephone sampling procedures. Participants completed face-to-face interviews regarding their alcohol use patterns, engagement in delinquency, sexual activity, sociodemographic characteristics, and time spent on a variety of activities, including homework, extracurricular activities, sports time, alone time, paid work, housework, television watching, and variables measuring family time and peer time. Hierarchical regression models were used to analyze the data. Tables, references