Date:
This was an experiment designed to evaluate the effectiveness of hot spots policing in urban and suburban areas. The program is rated Ineffective. There were no statistically significant differences between treatment and control hot spots in part 1 crimes, part 2 crimes, and crime-related calls for service. However, results showed a statistically significant reduction in crime-related calls for service in urban locations relative to suburban locations.
An Ineffective rating implies that implementing the program is unlikely to result in the intended outcome(s).
This program's rating is based on evidence that includes at least one high-quality randomized controlled trial.
An Ineffective rating implies that implementing the program is unlikely to result in the intended outcome(s).
This program's rating is based on evidence that includes at least one high-quality randomized controlled trial.
Program Goals
Hot spots policing strategies involve increasing police presence in small geographic areas or places (usually in urban settings) where crime is concentrated (Braga, Papachristos, and Hureau 2012). In 2014, the Louisville (Ky.) Metropolitan Police Department (LMPD), working with university researchers, implemented an experiment to evaluate whether hot spots policing tactics would reduce crime in traditional urban hot spots as well as in “cooler” suburban hot spot areas. Although different tactics may be used in hot spots policing, this experiment tested the effects of directed patrol (Schaefer, Hughes, and Stelzig 2019).
Target Sites
Hot spots were selected by identifying microgeographic locations in Louisville with the highest levels of crime. Specifically, crime data and crime-related calls for service were collected for each of the participating patrol divisions for a 2-year period prior to the implementation of the experiment. Once all crime data were geocoded and categorized, the top 80 street segments with the total volume of crime and crime-related calls for service in each division were considered for inclusion.
Program Activities
Officers were assigned to one or two hot spot locations that were geographically close to their assigned patrol beats. They were directed to visit the locations every 2–3 hours, at random times, staying 12–15 minutes at each location. The officers were not given specific instructions on what to do while at the hot spots. They were given the discretion to engage in proactive activities as needed
Program Theory
Hot spots policing is based on deterrence theory as well as three related opportunity theories (Braga et al. 2019). Deterrence theory suggests that individuals will refrain from engaging in crime if they fear the certainty, swiftness, and severity of punishment (Paternoster and Bachman 2001). In general, increasing police presence in crime hot spots elevates people’s perceived risk of apprehension, thereby discouraging crime (Weisburd and Majmundar 2017). Hot spots policing is also heavily influenced by opportunity theories such as rational choice theory, routine activities theory, and environmental criminology theory (Braga et al. 2019).
Study 1
Part 1 Crimes
Schaefer and colleagues (2019) found that there were no statistically significant differences between the treatment and control hot spots in part 1 crimes during the 90-day intervention period.
Part 2 Crimes
There were no statistically significant differences between the treatment and control hot spots in part 2 crimes during the 90-day intervention period.
Crime-Related Calls for Service
There were no statistically significant differences between the treatment and control hot spots in crime-related calls for service during the 90-day intervention period.
Study
To assess the impact of hot spots policing in Louisville (Ky.) on crime and disorder, Schaefer and colleagues (2019) used block randomization to ensure an equal balance of urban and suburban hot spots across the treatment and control groups. The experiment was designed to examine the effectiveness of directed patrol as a crime-reduction strategy in both urban and suburban locations in Louisville.
When the experiment was implemented, the Louisville Metropolitan Police Department (LMPD) oversaw eight geographically based patrol divisions. Out of the eight patrol divisions, seven participated in the experiment. To identify hot spots, crime data and crime-related calls for service were collected for each of the seven participating divisions for a 2-year period prior to the implementation of the experiment (January 2012–December 2013). Data from this period were geocoded to street segments and categorized as part 1 crimes, part 2 crimes, and crime-related calls for service. Part 1 crimes correspond to those included in Part 1 of the Uniform Crime Report (UCR) data; these are often referred to as “index” crimes. Part 2 crimes are less serious and comprise other forms of criminal activity; the present study refers to these as “soft” crimes. Once all the crime data were geocoded and categorized, 80 street segments with the greatest volume of crime and crime-related calls for service were selected from each division for possible inclusion in the study.
After identifying an initial pool of potential street segments, the study authors used Sherman and Weisburd’s (1995) inclusion criteria to determine eligible hot spots. To be eligible for inclusion in the experiment:
- No hot spot [could be] larger than one standard linear street block.
- No hot spot [could] extend for more than one-half block form either side of an intersection.
- No hot spot [could be] within one standard linear block of another hot spot.
After the removal of ineligible hot spots, each division commander selected 10–24 hot spots from their division for inclusion in the experiment. These selected hot spots were then randomly assigned to either the treatment or control group. In total, across the seven patrol divisions, 94 hot spots were selected, including 47 in the treatment group and 47 in the control group.
To determine whether the hot spot was in an urban or suburban location, the study authors relied on classifications established by the National Center for Education Statistics (NCES) Education Demographic and Geographic Estimates (EDGE) program. This process resulted in 24 urban hot spots and 23 suburban hot spots in each group. To ensure that the treatment and control hot spot pairs were equivalent on the three outcome variables of interest (part 1 crimes, part 2 crimes, and crime-related calls for service), an independent samples t-test was conducted using crime data from January 2012–December 2013. The results revealed that there were no statistically significant differences between the treatment and control groups on any of the outcome measures at baseline.
The experiment lasted 90 days, beginning on June 2, 2014, and ending on August 30, 2014. To determine the impact of the hot spots strategy, the study author used ordinary least squares (OLS) regression models with a difference-in-differences (DID) approach. DID measures were used to estimate the effects of the intervention on the three outcomes between the treatment and control conditions during the 90-day intervention period.
Subgroup Analysis
The primary goal of the study by Schaefer and colleagues (2019) was to determine whether hot spots policing tactics (specifically directed patrol) were effective at reducing crime (as measured by calls for service, part 1 crimes, and part 2 crimes) in both urban and suburban communities. The results showed a statistically significant reduction in crime-related calls for service in urban locations relative to suburban locations. However, there were no statistically significant differences between urban and suburban hot spot locations for part 1 and part 2 crimes.
These sources were used in the development of the program profile:
Study
Schaefer, Brian P., Thomas Hughes, and W. Cameron Stelzig. 2019. “Hot Spots Across the Metropolis: Evaluating Hot Spots Directed Patrol at City and Suburban Locations.” Justice Quarterly, available online first.
These sources were used in the development of the program profile:
Braga, Anthony, Andrew Papachristos, and David Hureau. 2012. “Hot Spots Policing Effects on Crime.” Campbell Systematic Reviews 1.
Braga, Anthony A., Brandon S. Turchan, Andrew V. Papachristos, and David M. Hureau. 2019. “Hot Spots Policing and Crime Reduction: An Update of an Ongoing Systematic Review and Meta-Analysis.” Journal of Experimental Criminology 15(3):289–311.
Paternoster, R., and R. Bachman. 2001. Explaining Criminals and Crime. Los Angeles, Calif.: Roxbury.
Sherman, Lawrence W., and David Weisburd. 1995. “General Deterrent Effects of Police Patrol in Crime ‘Hot Spots’: A Randomized, Controlled Trial.” Justice Quarterly 12(4):625–48.
Weisburd, D., and M.K. Majmundar. (eds.). 2018. Proactive Policing: Effects on Crime and Communities. Committee on Proactive Policing: Effects on Crime, Communities, and Civil Liberties. Washington, D.C.: The National Academies 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
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Crime & Delinquency - Multiple crime/offense types |
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Crime & Delinquency - Violent offenses |
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Crime & Delinquency - Property offenses |
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Crime & Delinquency - Public order offenses |
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Crime & Delinquency - Drug and alcohol offenses |
Geography: Suburban Urban
Setting (Delivery): High Crime Neighborhoods/Hot Spots
Program Type: Community-Oriented Policing, Hot Spots Policing, Violence Prevention
Current Program Status: Not Active