Evidence Rating: No Effects | One study
Date:
This crime prevention strategy applied hot spots policing techniques to bus stops in London, England. The program is rated No Effects. Generally, there was no statistically significant difference in bus driver reports of crime for treatment bus stops relative to control bus stops. The program also had a reverse effect on victim reports of crime, which increased in treatment bus stops, compared with control bus stops. This finding was statistically significant.
A No Effects rating implies that implementing the program is unlikely to result in the intended outcome(s) and may result in a negative outcome(s).
This program's rating is based on evidence that includes at least one high-quality randomized controlled trial.
Program Goals/Target Sites
The Hot Spots Policing intervention was designed to deter crime from bus stops in London experiencing high crime rates. Bus stops were chosen as target sites of the intervention because they had a disproportionately higher count of incidents reported by bus drivers to the police relative to other bus stops in London (specifically, there had been at least three incidents associated with the bus stop in the past six months).
Program Components
The program was carried out and delivered by teams of two uniformed Metropolitan Police Service (MPS) officers who were assigned to “be visible” and to deter crime and antisocial behavior at the bus stops. The officers were provided with a patrol plan that contained maps of the designated bus stops and the bus lines associated with them that would take them to the next bus stop. Officers were instructed to follow the rigid patrol plan without deviation and therefore police presence in the hot spots coincided with actual bus arrivals (as the officers also arrived at the bus stops by bus). The officers arrived at the bus stops during the “hot hours”—meaning that they were physically present at the bus stop at its peak moment in terms of crime opportunities—when passengers embarked or disembarked from the bus.
Patrol teams of two MPS officers visited the stops three times per shift (12:00–6:00 p.m.), five times per week for 15 minutes, over a 6-month period. The officers were in charge of monitoring their bus stops and thereby deterring crime with their presence.
Program Theory
Hot spots policing techniques are grounded in deterrence theory. In this program, officers were thought to serve as crime deterrents due to their presence at the bus stops. The logic was that people who may be tempted to commit a crime would perceive an increased risk of detection and punishment and therefore be deterred from committing crimes (Sherman and Rogan 1995; McGarrell et al. 2001). The police, therefore, acted as guardians to reduce opportunities for committing a crime (Nagin et al. 2015).
The program is also grounded in rational choice theory (Clarke and Cornish 1985), which asserts that people often weigh the relative costs and benefits when deciding whether or not to commit a crime. Further decisions, including where and when to commit a crime and the selection of targets or victims are also influenced by rational decision-making processes (La Vigne 2015). People who may have been tempted to commit a crime were assumed to perceive the high risk of being caught committing a crime with a police officer in close proximity. This police presence was thought to have a deterrent effect.
The preponderance of evidence suggested that Hot Spots Policing at Bus Stops in London did not have the intended effects on crime, and in some cases caused a “backfiring effect,” wherein the control bus stops experienced fewer instances of crime than the treatment bus stops.
Study 1
DIR, Out of Hours, 50-100m Buffer
The number of DIRs outside of peak times in the 50- to 100-meter buffer zone was higher for treatment bus stops than for control bus stops, which was statistically significant (also suggesting a “backfiring effect” of the program).
Victim-Generated Crimes, 50-100m Radius
The number of victim-generated crime reports was higher in the treatment bus stops, compared with the control bus stops. This was a statistically significant finding, suggesting there was “backfiring effect,” wherein the effect favored the control group.
Victim-Generated Crimes, 100-150m Radius
The number of victim-generated crime reports was statistically significantly higher in the treatment bus stops than in the control bus stops (also suggesting a “backfiring effect” of the program).
DIR, Peak Hours, 50-100m Buffer
The program resulted in fewer DIRs during the timeframe (between 12:00 and 6:00 p.m., from Monday to Friday) in the 50- to 100-meter buffer zone of treatment bus stops, compared with control bus stops. This finding was statistically significant.
DIR, Out of Hours, 100-150m Buffer
There was no statistically significant difference in the number of DIRs outside of peak times in the 100- to 150-meter buffer zone for treatment and control bus stops.
DIR, Out of Hours, 50m Radius
The program found no statistically significant differences between the treatment bus stops and control bus stops in the number of DIRs outside of peak times in the 50-meter buffer zone.
DIR, Peak Hours, 50m Radius
Ariel and Partridge (2017) found no statistically significant differences in the number of bus driver incident reports (DIRS) at the peak times for criminal activity (between 12:00 and 6:00 p.m.) from Monday to Friday between treatment bus stops and control bus stops.
DIR, Peak Hours, 100-150m Buffer
The program found no statistically significant difference between treatment and control bus stops in the number of DIRs during the peak hours timeframe in the 100- to 150-meter buffer zone.
Victim-Generated Crimes, 50m Radius
The program found no statistically significant difference between treatment and control bus stops in the number of victim-generated crime reports within the 50-meter buffer zone.
Study 1
Ariel and Partridge (2017) conducted a randomized controlled trial to measure the effects of hot spots policing at bus stops in London on crime, measured through victim-generated crime reports and bus driver incident reports. The experiment took place in London, the UK’s most populous urban metropolitan city, with 8.63 million residents in nearly 607 square miles. Overall, per 1,000 residents, London had 8.3 violence with injury offenses, 1.7 sexual assaults, 2.6 robberies, and 8.8 residential burglaries in 2014–2015. In terms of the bus network, London hosts one of the largest systems in the world, with over 9,000 buses, 675 bus routes, and 19,000 bus stops. The bus network attracts over two billion commuter trips per year. The MPS recorded 7.2 crimes per million passenger journeys during 2014–2015.
The study authors identified the hottest bus stops (i.e., bus stops that had a disproportionately higher count of driver incident reports relative to the other 19,000 bus stops in London) in the Greater London area, and randomly assigned them to the treatment or control conditions. None of the pretreatment between-group differences were statistically significant, therefore suggesting that the two groups were approximately equivalent prior to the launch of the intervention. The study authors drew a concentric series of buffers to test for the treatment effects in the area surrounding the bus stop at less than 50 meters, 50 to 100 meters, and 100 to 150 meters. Buffer zones were drawn to detect any possible displacement effects or diffusion of benefits and to ensure that no two hot spots and their surrounding areas overlapped, which could cause a treatment effect spillover.
The experiment involved 102 bus stops. Metropolitan Police Service officers were not instructed to patrol beyond the bus stop vicinity and were tracked using GPS. Outcomes were measured in terms of victim-generated crime reports to the police and bus driver incident reports (DIRs), within targeted and catchment areas. Victim-generated crime reports capture any instance in which an individual called on the police to report a crime, whereas DIRs are instances of criminal damage, fare evasion, and passenger disturbance on London’s bus network. At any given moment during the duration of the experiment (6 months), there were about 32 officers conducting patrols during hot hours. Each patrol unit had ownership of about two to four hot spots, depending on the travel distance between the bus stops.
Changes in the two outcome types, DIRs and victim-generated crime reports, were compared between the 6-month period before the trial and after the beginning of the trial, and then were compared with the differences between the treatment and control conditions. The data were also organized based on the time of the intervention (Monday–Friday, between 12:00 and 6:00 p.m.), and outside these hours. No subgroup analyses were conducted.
Police officer teams were equipped with a hand-held GPS tracker that could track the movement of the officer at any given moment. The GPS trackers were used to measure how much time officers spent in particular areas (duration), and how many visits were made (frequency). Every tracker was set to transmit a timestamp every five minutes, which indicated the latitude and longitude of the tracker, to ensure that the police officers were patrolling within their designated areas (Ariel and Partridge 2017).
These sources were used in the development of the program profile:
Study 1
Barack, Ariel, and Henry Partridge. 2017. “Predictable Policing: Measuring the Crime Control Benefits of Hot Spots Policing at Bus Stops.” Journal of Quantitative Criminology 33:809–33.
These sources were used in the development of the program profile:
Clarke, Ronald V., and Derek B. Cornish. 1985. “Modeling Offenders’ Decisions: A Framework for Research and Policy.” Crime and Justice 6: 147–85.
La Vigne, Nancy. 2015. “Crime In and Around Metro Transit Stations: Exploring the Utility of Opportunity Theories of Crime.” In Safety and Security in Transit Environments.. London, UK: Palgrave Macmillan, 251–69.
McGarrell, Edmund F., Steve Chernak, Alexander Weiss, and Jeremy Wilson.2001. “Reducing Firearms Violence Through Directed Police Patrol.” Criminology and Public Policy 1(1):119–48.
Nagin, Daniel S., Robert M. Solow, and Cynthia Lum. 2015. “Deterrence, Criminal Opportunities and Police.”Criminology 53(1):74–100.
Sherman, Lawrence W., and Dennis P. Rogan. 1995. “Effects of Gun Seizures on Gun Violence: ‘Hot Spots’ Patrol in Kansas City.” Justice Quarterly 12(4):673–93.
Skogan, Wesley G., and Susan M. Hartnett.1997. “Community Policing, Chicago Style” In Studies in Crime and Public Policy. New York: Oxford University Press.
Following are CrimeSolutions-rated programs that are related to this practice:
Hot spots policing strategies focus on small geographic areas or places, usually in urban settings, where crime is concentrated. Through hot spots policing strategies, law enforcement agencies can focus limited resources in areas where crime is most likely to occur. This practice is rated Effective for reducing overall crime and rated Promising for reducing violent, property, public order, and drug and alcohol offenses.
Evidence Ratings for Outcomes
Crime & Delinquency - Multiple crime/offense types | |
Crime & Delinquency - Violent offenses | |
Crime & Delinquency - Property offenses | |
Crime & Delinquency - Public order offenses | |
Crime & Delinquency - Drug and alcohol offenses |
Geography: Urban
Setting (Delivery): High Crime Neighborhoods/Hot Spots
Program Type: Community and Problem Oriented Policing, Hot Spots Policing, Situational Crime Prevention
Current Program Status: Not Active