开发一种针对家庭暴力事件的实用预测筛查工具。

Developing a practical forecasting screener for domestic violence incidents.

作者信息

Berk Richard A, He Yan, Sorenson Susan B

机构信息

Statistics, University of California, Los Angeles, USA.

出版信息

Eval Rev. 2005 Aug;29(4):358-83. doi: 10.1177/0193841X05275333.

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.

摘要

在本文中,作者报告了一种简短筛查工具的开发情况,洛杉矶县警局的副警长们可在现场使用该工具,以帮助预测特定家庭中的家庭暴力事件。数据来自2003年秋季警局副警长被派往的500多个家庭。在现场收集了有关潜在预测因素的信息。在3个月的随访期间对结果进行了测量。使用评估真实预测的现代数据挖掘程序对数据进行了分析。基于所收集信息的一小部分开发了一种筛查工具。使筛查工具更复杂并不能提高预测能力。考虑到误报和漏报的相对成本,该工具正确预测未来服务需求的时间约为60%。涉及家庭暴力轻罪和重罪的未来呼叫被正确预测的时间约为50%。50%这个数字很重要,因为此类呼叫需要执法响应,但在所有家庭暴力服务呼叫中所占比例相对较小。

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