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dc.contributor.authorChang, Hsin-Lien_US
dc.contributor.authorShih, Chang-Kuen_US
dc.date.accessioned2014-12-08T15:24:07Z-
dc.date.available2014-12-08T15:24:07Z-
dc.date.issued2012-09-01en_US
dc.identifier.issn0001-4575en_US
dc.identifier.urihttp://hdl.handle.net/11536/16776-
dc.description.abstract"This study developed a scale to measure 502 Taiwan traffic police officers' perceived ability to detect, detain, and intercept those vehicles whose drivers are driving while intoxicated (DWI) when conducting sobriety checkpoints. Through factor analysis, the officers' enforcement ability was found to consist of two component latent traits: detecting ability (DA) and detaining and intercepting ability (DIA). A multidimensional approach of Rasch models was then applied to measure the police officers' perceived abilities and particular difficulties in conducting sobriety checkpoints. The study results indicated that the majority of police officers performed well in detecting DWI vehicles, but half of the study participants lacked confidence in detaining DWI vehicles and intercepting escaping DWI vehicles. DWI with weaving was found to be the most aggressive and threatening behavior to traffic police when conducting sobriety checkpoints. Police officers over age 46 were found to have significantly lower DA and DIA, while branch captains were found to have significantly higher DA than their colleagues. Several strategies and programs are suggested based on the study findings to improve the enforcement ability of police officers. (C) 2012 Elsevier Ltd. All rights reserved."en_US
dc.language.isoen_USen_US
dc.title"Using a multidimensional Rasch model approach to measure the police's perceived ability to detect, detain and intercept DWI vehicles when conducting sobriety checkpoints"en_US
dc.typeArticleen_US
dc.identifier.journalACCIDENT ANALYSIS AND PREVENTIONen_US
dc.citation.volume48en_US
dc.citation.issueen_US
dc.citation.spageen_US
dc.citation.epage505en_US
dc.contributor.department運輸與物流管理系 註:原交通所+運管所zh_TW
dc.contributor.departmentDepartment of Transportation and Logistics Managementen_US
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