Literature DB >> 34798566

Police narrative reports: Do they provide end-users with the data they need to help prevent bicycle crashes?

Dahianna Lopez1, Liam C Malloy2, Kimberly Arcoleo3.   

Abstract

Bicycles gained significant popularity among Americans in 2020. Greater investment in adequate bicycle safety facilities will be needed. Crash data from police will undoubtedly play a role in decision-making. This research evaluated the data quality of text narratives in police reports on bicycle crashes. The aims were to identify situations in which police officers wrote more detail in the narrative text, investigate if longer reports translate to more in-depth crash descriptions, examine the extent to which narrative texts cover details useful for those charged with bicycle safety. This is a 4-year retrospective cohort study of vehicle-vs-bicycle crashes that occurred between January 1, 2009, and December 31, 2012, in Boston, Massachusetts (USA). Police reports were matched with the Pedestrian and Bicycle Crash Analysis Tool (PBCAT) to measure how much information was captured and when reports were more likely to capture more information. Police reports only captured most information in one area of the standardized form (Crash Typing), with average total missingness of over 75%. Longer reports did reduce the amount of missingness, and officers were more likely to write longer reports when they were on the crash site, when there was an injury, when the crash involved an extended car door, and during the day. A 100% increase in the report's words was associated with a four-percentage point reduction in PBCAT missingness. While longer reports result in less missingness when measured against the standardized crash form, the average report still misses most of the information that the form would capture. We recommend that police departments adopt a standardized form to facilitate information capture at the scene of bicycle-vehicle crashes.
Copyright © 2021 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bicycle; Crash: Police Report; Text narrative

Mesh:

Year:  2021        PMID: 34798566     DOI: 10.1016/j.aap.2021.106475

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  1 in total

1.  Prediction of Severe Injury in Bicycle Rider Accidents: A Multicenter Observational Study.

Authors:  Il-Jae Wang; Young Mo Cho; Suck Ju Cho; Seok-Ran Yeom; Sung Wook Park; So Eun Kim; Jae Chol Yoon; Yeaeun Kim; Jongho Park
Journal:  Emerg Med Int       Date:  2022-05-27       Impact factor: 1.621

  1 in total

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