ArticleInjury epidemiology2020
Re-prioritizing traffic stops to reduce motor vehicle crash outcomes and racial disparities.
Article in Injury epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Informing traffic enforcement leniency and discretion: Crash culpability and the effectiveness of written warnings versus citations.Accident; analysis and prevention · 2023Article
- Public health critical race praxis at the intersection of traffic stops and injury epidemiology.Injury epidemiology · 2022Article
- The color of risk protection orders: gun violence, gun laws, and racial justice.Injury epidemiology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLaw enforcement traffic stops are one of the most common entryways to the US justice system. Conventional frameworks suggest traffic stops promote public safety by reducing dangerous driving practices and non-vehicular crime. Law enforcement agencies have wide latitude in enforcement, including prioritization of stop types: (1) safety (e.g. moving violation) stops, (2) investigatory stops, or (3) economic (regulatory and equipment) stops. In order to prevent traffic crash fatalities and reduce racial disparities, the police department of Fayetteville, North Carolina significantly re-prioritized safety stops.
methodsAnnual traffic stop, motor vehicle crash, and crime data from 2002 to 2016 were combined to examine intervention (2013-2016) effects. Fayetteville was compared against synthetic control agencies built from 8 similar North Carolina agencies by weighted matching on pre-intervention period trends and comparison against post-intervention trends.
resultsOn average over the intervention period as compared to synthetic controls, Fayetteville increased both the number of safety stops + 121% (95% confidence interval + 17%, + 318%) and the relative proportion of safety stops (+ 47%). Traffic crash and injury outcomes were reduced, including traffic fatalities - 28% (- 64%, + 43%), injurious crashes - 23% (- 49%, + 16%), and total crashes - 13% (- 48%, + 21%). Disparity measures were reduced, including Black percent of traffic stops - 7% (- 9%, - 5%) and Black vs. White traffic stop rate ratio - 21% (- 29%, - 13%). In contrast to the Ferguson Effect hypothesis, the relative de-prioritization of investigatory stops was not associated with an increase in non-traffic crime outcomes, which were reduced or unchanged, including index crimes - 10% (- 25%, + 8%) and violent crimes - 2% (- 33%, + 43%). Confidence intervals were estimated using a different technique and, given small samples, may be asymmetrical.
conclusionsThe re-prioritization of traffic stop types by law enforcement agencies may have positive public health consequences both for motor vehicle injury and racial disparity outcomes while having little impact on non-traffic crime.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.