Developing a Practical Forecasting Screener for Domestic Violence Incidents

Richard A. Berk, Yan He and Susan B. Sorenson
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Richard A. Berk: University of California, Los Angeles
Yan He: University of California, Los Angeles
Susan B. Sorenson: University of California, Los Angeles

Evaluation Review, 2005, vol. 29, issue 4, 358-383

Abstract: In this article, the authors report on the development of a short screening tool that deputies in the Los Angeles Sheriff’s Department could use in the field to help forecast domestic violence incidents in particular households. The data come from more than 500 households to which sheriff’s deputies were dispatched in fall 2003. Information on potential predictors was collected at the scene. Outcomes were measured during a 3-month follow-up. Data were analyzed with modern data-mining procedures in which true forecasts were evaluated. A screening instrument was developed based on a small fraction of the information collected. Making the screening instrument more complicated did not improve forecasting skill. Taking the relative costs of false positives and false negatives into account, the instrument correctly forecasted future calls for service about 60% of the time. Future calls involving domestic violence misdemeanors and felonies were correctly forecast about 50% of the time. The 50% figure is important because such calls require a law enforcement response and yet are a relatively small fraction of all domestic violence calls for service.

Keywords: domestic violence; data mining; police; spousal assault; family violence (search for similar items in EconPapers)
Date: 2005
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Persistent link: https://EconPapers.repec.org/RePEc:sae:evarev:v:29:y:2005:i:4:p:358-383

DOI: 10.1177/0193841X05275333

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