Abstract
This Campbell systematic review examines the effects of focusing police crime prevention efforts on crime ‘hot spots’, and whether focused police actions at specific locations result in crime displacement (i.e. crime moving around the corner) or diffusion (i.e. crime reduction in surrounding areas) of crime control benefits. The review includes 19 studies covering 25 cases. Seventeen of the studies were conducted in the USA.
Investing police agencies' limited resources on hot spot policing in a small number of high-activity crime places will prevent crime in these and surrounding areas, reducing total crime. Problem oriented policing approach allows for developing tailored responses to specific recurring problems in high activity crime spots. Implementing situational prevention strategies that reduce police reliance on aggressive enforcement strategies may also have positive benefits for police-community relations. The reactions of local communities to hot spot policing must be considered. Residents may welcome efforts to reduce crime. But if policing programmes are seen as heavy-handed, or focus too much on particular population groups, they may end up driving a wedge between the police and those they are trying to help.
Abstract
BACKGROUND
In recent years, crime scholars and practitioners have pointed to the potential benefits of focusing crime prevention efforts on crime places. A number of studies suggest that there is significant clustering of crime in small places, or “hot spots,” that generate half of all criminal events. A number of researchers have argued that many crime problems can be reduced more efficiently if police officers focused their attention to these deviant places. The appeal of focusing limited resources on a small number of high-activity crime places is straightforward. If we can prevent crime at these hot spots, then we might be able to reduce total crime.
OBJECTIVES
To assess the effects of focused police crime prevention interventions at crime hot spots. The review also examined whether focused police actions at specific locations result in crime displacement (i.e., crime moving around the corner) or diffusion (i.e., crime reduction in surrounding areas) of crime control benefits.
SEARCH STRATEGY
A keyword search was performed on 15 online abstract databases. Bibliographies of past narrative and empirical reviews of literature that examined the effectiveness of police crime control programs were reviewed and forward searches for works that cited seminal hot spots policing studies were performed. Bibliographies of past completed Campbell systematic reviews of police crime prevention efforts and hand searches of leading journals in the field were performed. Experts in the field were consulted and relevant citations were obtained.
SELECTION CRITERIA
To be eligible for this review, interventions used to control crime hot spots were limited to police enforcement efforts. Suitable police enforcement efforts included traditional tactics such as directed patrol and heightened levels of traffic enforcement as well as alternative strategies such as aggressive disorder enforcement and problem-oriented policing. Studies that used randomized controlled experimental or quasi-experimental designs were selected. The units of analysis were limited to crime hot spots or high-activity crime “places” rather than larger areas such as neighborhoods. The control group in each study received routine levels of traditional police enforcement tactics.
DATA COLLECTION AND ANALYSIS
19 studies containing 25 tests of hot spots policing interventions were identified and full narratives of these studies were reported. Ten of the selected studies used randomized experimental designs and nine used quasi-experimental designs. A formal meta-analysis was conducted to determine the crime prevention effects in the eligible studies. Random effects models were used to calculate mean effect sizes.
RESULTS
20 of 25 tests of hot spots policing interventions reported noteworthy crime and disorder reductions. The meta-analysis of key reported outcome measures revealed a small statistically significant mean effect size favoring the effects of hot spots policing in reducing citizen calls for service in treatment places relative to control places. The effect was smaller for randomized designs but still statistically significant and positive. When displacement and diffusion effects were measured, unintended crime prevention benefits were associated with the hot spots
AUTHORS' CONCLUSIONS
The extant evaluation research provides fairly robust evidence that hot spots policing is an effective crime prevention strategy. The research also suggests that focusing police efforts on high-activity crime places does not inevitably lead to crime displacement and crime control benefits may diffuse into the areas immediately surrounding the targeted locations.
1 Background
In recent years, crime scholars and practitioners have pointed to the potential benefits of focusing crime prevention efforts on crime places. A number of studies suggest that crime is not spread evenly across city landscapes. Rather, there is significant clustering of crime in small places, or “hot spots,” that generate half of all criminal events (Pierce et al. 1988; Sherman, Gartin, and Buerger 1989; Weisburd et al. 1992). Even within the most crime-ridden neighborhoods, crime clusters at a few discrete locations and other areas are relatively crime free (Sherman, Gartin, and Buerger 1989). A number of researchers have argued that many crime problems can be reduced more efficiently if police officers focused their attention to these deviant places (Sherman and Weisburd 1995; Weisburd and Green 1995a). The appeal of focusing limited resources on a small number of high-activity crime places is straightforward. If we can prevent crime at these hot spots, then we might be able to reduce total crime.
Hot spots policing has become a very popular way for police departments to prevent crime. A recent Police Foundation report found that 7 in 10 departments with more than 100 sworn officers reported using crime mapping to identify crime hot spots (Weisburd et al. 2003). Many police departments reported having the capability to manage and analyze crime data in sophisticated ways and, through management innovations such as Compstat, hold officers accountable for implementing problem-solving strategies to control hot spot locations (Weisburd et al. 2003). The Police Executive Research Forum (2008) surveyed 176 U.S. police departments and reported that nearly 9 out of 10 agencies used hot spots policing strategies to deal with violent crime in their jurisdictions and that problem-solving techniques were often deployed to address violent crime hot spots.
A growing body of research evidence suggests that focused police interventions, such as directed patrols, proactive arrests, and problem-oriented policing, can produce significant crime prevention gains at high-crime “hot spots” (see, e.g. Braga 2008; Eck 1997, 2002; Weisburd and Eck 2004). Indeed, the National Research Council's Committee to Review Research on Police Policy and Practices concluded “…studies that focused police resources on crime hot spots provided the strongest collective evidence of police effectiveness that is now available” (Skogan and Frydl, 2004: 250). However, critics of place-based interventions charge that such policing strategies result in displacement — that is, criminals move to places not protected by police intervention (e.g. Reppetto 1976). The available evidence suggests that hot spots policing interventions are more likely to be associated with the diffusion of crime control benefits into surrounding areas rather than crime displacement (e.g. Braga and Weisburd 2010; Weisburd et al. 2006).
Unlike most innovations in policing, which are normally based on increasing operational and management efficiency, the emergence of hot spots policing can be traced directly to emerging theoretical perspectives in criminology that suggest the importance of places in understanding crime (Weisburd and Braga 2003). The consideration of such place-oriented strategies in crime control policy arose from research suggesting that micro-level variation in crime existed within communities. The observation that the distribution of crime varied within neighborhoods has existed for some time (see Hawley 1944, 1950; Shaw and McKay 1942; Werthman and Piliavin 1967); however, until recently, little research examined this variance beyond the community level of analysis. With the advent of powerful computer systems and software packages, several studies revealed that over half of all crimes in a city are committed at a few criminogenic places within communities (Pierce et al. 1988; Sherman, Gartin, and Buerger 1989). Further, research by Taylor and Gottfredson (1986) suggests that conclusive evidence links this variation to physical and social characteristics of particular blocks and multiple dwellings within a neighborhood. This uneven distribution of crime within specific neighborhoods has been reported in studies of a variety of crime types including drug selling (Weisburd and Green 1994), burglary (Pease 1991), robbery (Hunter and Jeffrey 1992), and auto theft (Clarke and Harris 1992).
Beyond studies observing the clustering of criminal events, in their review of the research literature, Eck and Weisburd (1995) identified four other theoretical concepts that illuminate the role of place in crime. Facilities, such as bars, churches, and apartment buildings have been found to affect crime rates in their immediate environment depending on the type of people attracted, the way the space is managed, or the possible crime controllers present such as owners, security, or police. Site features such as easy access, a lack of guardians, inept or improper management, and the presence of valuable items have been suggested to influence the decisions offenders make about the place they choose to commit their crimes. Studies of offender mobility suggest that offenders' target searching behavior is influenced by personal characteristics (such as gender, age, race, experience, and crime types) and the distribution of crime targets. A direct outgrowth of offender mobility patterns, research on target selection posits that offenders seek places with cues that indicate acceptable risks and gains, such as homes on the outskirts of affluent neighborhoods; these places are found during intentional target searches and during their daily legitimate routines.
The study of crime events at places is influenced and supported by three complementary theoretical perspectives: rational choice, routine activities, and environmental criminology. The rational choice perspective assumes that “offenders seek to benefit themselves by their criminal behavior; that this involves the making of decisions and choices, however rudimentary on occasion these choices may be; and that these processes, constrained as they are by time, the offender's cognitive abilities, and by the availability of relevant information, exhibited limited rather than normative rationality” (Cornish and Clarke 1987: 933). This perspective is often combined with routine activity theory to explain criminal behavior during the crime event (Clarke and Felson 1993). Routine activities theory posits that a criminal act occurs when a likely offender converges in space and time with a suitable target (e.g., victim or property) in the absence of a capable guardian (Cohen and Felson 1979). Rational offenders come across criminal opportunities as they go about their daily routines and make decisions whether to take action. The assumption is that, if victims and offenders are prevented from converging in space and time through the effective manipulation of the situations and settings that give rise to criminal opportunities, police can reduce crime.
Environmental criminology explores the distribution and interaction of targets, offenders, and opportunities across time and space; understanding the characteristics of places, such as facilities, is important as these attributes give rise to the opportunities that rational offenders will encounter during their routine activities (Brantingham and Brantingham 1991). Although this perspective is primarily concerned with applied crime prevention, Weisburd and his colleagues (1992: 48) suggest “environmental criminology's basic contribution lay in its call for a change in the unit of analysis from persons to places.” The attributes of a place are viewed as key in explaining clusters of criminal events. For example, a poorly lit street corner with an abandoned building, located near a major thoroughfare, provides an ideal location for a drug market. The lack of proper lighting, an abundance of “stash” locations around the derelict property, a steady flow of potential customers on the thoroughfare, and a lack of informal social control (termed defensive ownership) at the place generates an attractive opportunity for drug sellers. In many such cases, the police spend considerable time and effort arresting sellers without noticeably impacting the drug trade. The compelling criminal opportunities at the place attract sellers and buyers, and thus sustain the market. If the police want to be more efficient at disrupting the market, this suggests they should focus on the features of the place which cause the drug dealing to cluster at that particular location (see, e.g. Green 1996). This perspective is considered a radical departure from traditional criminological theories that focused prevention efforts on the individual and ignored the importance of place (Weisburd 1997; Sherman, Gartin, and Buerger 1989).
Indeed, police officers have long recognized the importance of place in crime problems. Police officers know the locations within their beats that tend to be trouble spots and are often very sensitive to signs of potential crimes across the places that comprise their beats. As Bittner (1970: 90) suggests in his classic study of police work, some officers know “the shops, stores, warehouses, restaurants, hotels, schools, playgrounds, and other public places in such a way that they can recognize at a glance whether what is going on within them is within the range of normalcy.” The traditional response to such trouble spots typically included heightened levels of patrol and increased opportunistic arrests and investigations. Until recently, police crime prevention strategies did not focus systematically on crime hot spots and did not seek to address the underlying conditions that give rise to high-activity crime places.
The widespread use of hot spots policing to prevent crime warrants ongoing careful reviews of the available empirical evidence on the crime control benefits of the approach. This document provides an updated version of a previously completed Campbell Collaboration systematic review of the effects of hot spots policing on crime (Braga 2001, 2005, 2007).
2 Objectives
This review will synthesize the existing published and non-published empirical evidence on the effects of focused police crime prevention interventions at high-activity crime places and will provide a systematic assessment of the preventive value of focused police crime prevention efforts at crime hot spots. The review also examined whether focused police actions at specific locations result in crime displacement or a diffusion of crime control benefits.
3 Methods
This review synthesizes existing published and non-published empirical evidence on the effects of focused police crime prevention interventions at crime hot spots and provides a systematic assessment of the preventive value of these programs. In keeping with the conventions established by the systematic reviews methods literature, the stages of this review and the criteria used to select eligible studies are described below.
3.1 INCLUSION AND EXCLUSION CRITERIA
3.1.1 Types of studies
In eligible studies, crime places that received the hot spots policing intervention were compared to places that experienced routine levels of traditional police service (i.e., regular levels of patrol, ad-hoc investigations, etc.). The comparison group study had to be either experimental or quasi-experimental (nonrandomized) (Campbell and Stanley 1966; Cook and Campbell 1979).
3.1.2 Type of areas
The units of analysis were crime hot spots or high-activity crime “places.” As Eck (1997: 7-1) suggests, “a place is a very small area reserved for a narrow range of functions, often controlled by a single owner, and separated from the surrounding area… examples of places include stores, homes, apartment buildings, street corners, subway stations, and airports.” All studies using units of analysis smaller than a neighborhood or community were considered. This constraint was placed on the review process to ensure that identified studies were evaluating police strategies focused on the small number of locations that generate a disproportionate amount of crime in urban areas.
As described earlier, hot spots policing was a natural outgrowth of theoretical perspectives that suggested specific places where crime concentrates were an important focus for strategic crime prevention efforts. Police interventions implemented at the community or neighborhood level would not be specifically focused on small places, often encompassing only one or a few city blocks, that would be considered hot spots of crime. However, this review does include quasi-experimental designs that compare changes at larger areal units, such as policing districts or census tracts, if the implemented hot spots policing program was clearly focused at specific places within the larger areal unit. For instance, The Kansas City Gun Project quasi-experiment evaluated the effects of increased gun seizures focused at gun hot spots within an 8 by 10 block police beat on gun crime relative to traditional policing services in comparison police beats (Sherman and Rogan 1995a).
The methodological approaches used to identify hot spots in the eligible studies were also reviewed. Diverse types of hot spots may respond to treatment in different ways. As such, the review needed to be sensitive to varying hot spot identification methods that could influence whether or not the treatment generated crime prevention gains.
3.1.3 Types of interventions
To be eligible for this review, interventions used to control crime hot spots were limited to police-led crime control efforts. Suitable police enforcement efforts included traditional tactics such as directed patrol and heightened levels of traffic enforcement as well as alternative strategies such as aggressive disorder enforcement and problem-oriented policing (Goldstein 1990). Studies of police crackdown programs were also considered (see, e.g. Sherman 1990). However, to be included in the review, crackdown programs had to be focused on very specific places. Some ongoing attention to crime hot spots must be a characteristic of the program whether it was a series of subsequent crackdowns or simple maintenance of the targeted area through other means (e.g. additional follow-up directed patrol). This inclusion criterion ensured that only crackdown programs that were similar to more formal hot spots policing programs were considered.
3.1.4 Types of outcome measures
Eligible studies had to measure the effects of police intervention on officially recorded levels of crime at places such as crime incident reports, citizen emergency calls for service, and arrest data. Other outcomes measures such as survey, interview, systematic observations of social disorder (such as loitering, public drinking, and the solicitation of prostitution), systematic observations of physical disorder (such as trash, broken windows, graffiti, abandoned homes, and vacant lots), and victimization measures used by eligible studies to measure program effectiveness were also coded and analyzed.
Particular attention was paid to studies that measured crime displacement effects and diffusion of crime control benefit effects. As mentioned earlier, policing strategies focused on specific locations have been criticized as resulting in displacement (see Reppetto 1976). More recently, academics have observed that crime prevention programs may result in the complete opposite of displacement--- that crime control benefits were greater than expected and “spill over” into places beyond the target areas (Clarke and Weisburd 1994). The quality of the methodologies used to measure displacement and diffusion effects, as well as the types of displacement (spatial, temporal, target, modus operandi) examined, was assessed. Based on our a priori knowledge of several hot spots policing experiments (e.g. Weisburd and Green 1995; Braga et al. 1999), we expected most analyses of displacement and diffusion effects to compare pre-test and post-test counts of official crime data in catchment areas surrounding treatment and control hot spots.
3.2 SEARCH STRATEGY
Several strategies were used to perform an exhaustive search for literature fitting the eligibility criteria. First, a keyword search was performed on an array of online abstract databases (see lists of keywords and databases below). Second, the bibliographies of past narrative and empirical reviews of literature that examined the effectiveness of police crime control programs were reviewed (Braga 2008; Eck and Maguire 2000; Sherman 1997, 2002; Skogan and Frydl, 2004; Weisburd and Eck 2004). Third, forward searches for works that cited seminal hot spots policing studies were performed (Braga et al. 1999; Sherman et al. 1989; Sherman and Weisburd 1995; Sherman and Rogan 1995a; Weisburd and Green 1995a). Fourth, bibliographies of past completed Campbell systematic reviews of police crime prevention efforts were searched (Mazerolle et al. 2007; Weisburd et al. 2008; Bowers et al. 2010). Fifth, hand searches of leading journals in the field were performed.1
The searches were all completed between October 2010 and January 2011. Thus, the review only covers studies published in 2010 and earlier. Sixth, after finishing the above searches and reviewing the studies as described later, the list of studies meeting our eligibility criteria was emailed in June 2011 to leading criminology and criminal justice scholars knowledgeable in the area of hot spots policing strategies. These 83 scholars were defined as those who authored at least one study which appeared on our inclusion list, anyone involved with the National Academy of Sciences review of police research and other leading scholars (see Appendix 1). This helped to identify studies the above searches left out as these experts were able to make referrals to studies that were missed, particularly unpublished studies. Finally, an information specialist was engaged at the outset of our review and at points along the way in order to ensure that appropriate search strategies were used to identify the studies meeting the criteria of this review.2
The following fifteen databases were searched: Criminal Justice Periodical Index Sociological Abstracts Social Science Abstracts (SocialSciAbs) Social Science Citation Index Arts and Humanities Search (AHSearch) Criminal Justice Abstracts National Criminal Justice Reference Service (NCJRS) Abstracts Educational Resources Information Clearinghouse (ERIC) Legal Resource Index Dissertation Abstracts Government Publications Office, Monthly Catalog (GPO Monthly) Google Scholar Online Computer Library Center (OCLC) SearchFirst CINCH data search C2 SPECTR (Campbell Collaboration Social, Psychological, Educational and Criminological Trials Register)
The following terms were used to search the fifteen databases listed above: Hot spot AND police Crime place AND police Crime clusters AND police Crime displacement Place-oriented interventions High crime areas AND police High crime locations AND police Targeted policing Directed patrol Crackdowns Enforcement swamping
3.3 DETAILS OF STUDY CODING CATEGORIES
All eligible studies were coded (see coding protocol attached in Appendix 2) on a variety of criteria including: Reference information (title, authors, publication etc.) Nature of description of selection of site, problems etc. Nature and description of selection of comparison group or period The unit of analysis The sample size Methodological type (randomized experiment or quasi-experiment) A description of the hot spots policing intervention Dosage intensity and type Implementation difficulties The statistical test(s) used Reports of statistical significance (if any) Effect size/power (if any) The conclusions drawn by the authors
The three authors independently coded each eligible study. Where there were discrepancies, the authors jointly reviewed the study and determined the final coding decision.
3.4 STATISTICAL PROCEDURES AND CONVENTIONS
Analysis of outcome measures across studies were carried out in a uniform manner and, when appropriate and possible, involved quantitative analytical methods. We used meta-analyses of program effects to determine the size and direction of the effects and to weight effect sizes based on the variance of the effect size and the study sample size (Lipsey and Wilson 2001). In this systematic review, the standardized mean difference effect size (also known as Cohen's d; see Rosenthal 1994) was used. The Effect Size Calculator, developed by David B. Wilson and available on the Campbell Collaboration's web site, was used to calculate standardized mean difference effect sizes for reported outcomes in each study.3 Biostat's Comprehensive Meta Analysis Version 2.2 was then used to conduct the meta-analysis of effect sizes. The specific approaches used to calculate effect sizes for each outcome in the eligible studies are described in the meta-analysis section.
3.4.1 Determination of independent findings
One problem in conducting meta-analyses in crime and justice is that investigators often did not prioritize outcomes examined. This is common in studies in the social sciences in which authors view good practice as demanding that all relevant outcomes be reported. For example, the Jersey City Drug Market Analysis Program experiment presents an array of outcome measures including violence, property, disorder, and narcotics calls for service (Weisburd and Green 1995a). However, the lack of prioritization of outcomes in a study raises the question of how to derive an overall effect of treatment. For example, the reporting of one significant result may reflect a type of “creaming” in which the authors focus on one significant finding and ignore the less positive results of other outcomes. But authors commonly view the presentation of multiple findings as a method for identifying the specific contexts in which the treatment is effective. When the number of such comparisons is small and therefore unlikely to affect the error rates for specific comparisons such an approach is often valid.
The studies were analyzed using three approaches. The first approach is conservative; we calculated an overall mean effect size for each study that combined reported outcomes in each study. The second represents the largest effect reported in the studies and gives an upper bound to the review findings. It is important to note that in some of the studies with more than one outcome reported, the largest outcome reflected what authors thought would be the most direct program effect. This was true for the Jersey City Drug Market Analysis Program experiment, which examined a wider range of crime outcome measures, but suggested that the largest program effects would be found in the case of disorder calls of service given the program's focus on street-level drug markets (Weisburd and Green 1995a). Finally, the smallest effect size for each study was analyzed. This approach is the most conservative and likely underestimates the effect of hot spots policing programs on crime. It was used here primarily to provide a lower bound to the review findings.
3.5 TREATMENT OF QUALITATIVE RESEARCH
Qualitative research on crime and disorder outcomes was not included in this systematic review. The authors hope that a qualitative researcher will assist in future updates to this review with a synthesis of qualitative evaluation measures.
4 Findings
4.1 SELECTION OF STUDIES
Search strategies in the systematic review process generate a large number of citations and abstracts for potentially relevant studies that must be closely screened to determine whether the studies meet the eligibility criteria (Farrington and Petrosino 2001). The screening process yields a much smaller pool of eligible studies for inclusion in the review. The search strategies produced 4,315 distinct abstracts using the 11 keywords and 15 databases. The contents of the 4,315 abstracts were reviewed for any suggestion of an experimental or quasi-experimental evaluation of hot spots policing interventions. 131 distinct abstracts were selected for closer review and the full-text reports, journal articles, and books for these abstracts were acquired and carefully assessed to determine whether the interventions involved focused police enforcement efforts at crime hot spots and whether the studies used randomized controlled trial designs or nonrandomized quasi-experimental designs. 19 eligible studies were identified and included in this review: Minneapolis Repeat Call Address Policing (RECAP) Program (Sherman, Buerger, and Gartin 1989) New York Tactical Narcotics Teams (Sviridoff, Sadd, Curtis, and Grinc 1992) St. Louis Problem-Oriented Policing in Three Drug Market Locations Study (Hope 1994) Minneapolis Hot Spots Patrol Program (Sherman and Weisburd 1995) Jersey City Drug Markets Analysis Program (DMAP) (Weisburd and Green 1995a) Kansas City Gun Project (Sherman and Rogan 1995a) Kansas City Crack House Police Raids Program (Sherman and Rogan 1995b) Beenleigh Calls for Service Project (Criminal Justice Commission 1998) Jersey City Problem-Oriented Policing at Violent Places Project (Braga, Weisburd, Waring, Green Mazerolle, Spelman, and Gajewski 1999) Houston Targeted Beat Program (Caeti 1999) Oakland Beat Health Program (Mazerolle, Price, and Roehl 2000) Pittsburgh Police Raids at Nuisance Bars Program (Cohen, Gorr, and Singh 2003) Buenos Aires Police Presence after Terror Attack Initiative (DiTella and Schargrodsky 2004) Philadelphia Drug Corners Crackdowns Program (Lawton, Taylor, and Luongo 2005) Jersey City Displacement and Diffusion Study (Weisburd, Wyckoff, Ready, Eck, Hinkle, and Gajewski 2006) Lowell Policing Crime and Disorder Hot Spots Project (Braga and Bond 2008) Jacksonville Policing Violent Crime Hot Spots Project (Taylor, Koper, and Woods 2011) Philadelphia Foot Patrol Program (Ratcliffe, Taniguchi, Groff, and Wood 2011) Boston Safe Street Teams Program (Braga, Hureau, and Papachristos 2011)
4.2 CHARACTERISTICS OF SELECTED STUDIES
Table 1 presents the basic characteristics of the 19 eligible hot spots policing studies. 17 of the 19 (89.5%) identified studies were conducted in the United States. One hot spots policing evaluation was conducted in Australia (Criminal Justice Commission 1998) and another was conducted in Argentina (DiTella and Schargrodsky 2004). Ten studies (52.6%) were completed in medium-sized cities with between 200,000 and 500,000 residents, seven studies (36.8%) were completed in large cities with more than 500,000 residents, and two studies were completed in smaller cities with less than 200,000 residents. Four cities were the research sites for multiple hot spots policing evaluations. Jersey City (NJ) was the site for three studies (Braga et al. 1999; Weisburd and Green 1995; Weisburd et al. 2006); while Minneapolis (MN) (Sherman, Buerger, and Gartin 1989; Sherman and Weisburd 1995), Kansas City (MO) (Sherman and Rogan 1995a, 1995b), and Philadelphia (Lawton et al. 2005; Ratcliffe et al. 2011) were the sites for two studies each. Fourteen of the eligible hot spots policing studies were published in peer-reviewed journals (73.7%), three were available as unpublished reports (15.8%), and two were available as published reports (10.5%).
Ten eligible studies used randomized controlled trials (52.6%) and nine eligible studies used quasi-experimental research designs (47.4%) to evaluate the effects of hot spots policing on crime. Five of the 19 eligible studies evaluated more than one hot spots policing intervention. In sum, the 19 eligible studies provided 25 distinct experimental and quasi-experimental tests of hot spots policing on crime. The Minneapolis RECAP experiment separately evaluated problem-oriented policing interventions at residential and commercial addresses (Sherman, Buerger, and Gartin 1989). The Vera Institute of Justice separately evaluated the Tactical Narcotics Team intervention at hot spots areas via quasi-experimental analyses in two separate New York Police Department precincts (Sviridoff et al. 1992). The Houston Targeted Beat Program quasi-experimental evaluation separately tested the effects of problem-oriented policing, high-visibility patrol, and zero-tolerance policing on hot spots in targeted high-crime beats (Caeti 1999). The Jersey City Displacement and Diffusion study examined the impact of problem-oriented policing interventions on a prostitution hot spot and a drug crime hot spot in separate quasi-experiments (Weisburd et al. 2006). Finally, the Jacksonville Policing Violent Crime Hot Spots experiment separately tested the effects of direct-saturation patrol and problem-oriented policing on violent street crime (Taylor et al. 2011).
Across the 25 tests in the 19 eligible hot spots policing studies, problem-oriented policing was the evaluated in 13 of the tests (52%). Increased patrol strategies and drug enforcement operations were evaluated in five tests (20%) each. Zero-tolerance policing 4 was evaluated in one test in the Houston Targeted Beat Program quasi-experiment (Caeti 1999) and an intervention designed to increase gun searches and seizures was tested in the Kansas City Gun quasi-experimental evaluation (Sherman and Rogan 1995a). 17 of the 25 hot spots policing tests also included analyses to determine whether the hot spots policing intervention generated any immediate spatial crime displacement or diffusion of crime control benefits effects.
4.3 NARRATIVE REVIEW OF THE EFFECTS OF HOT SPOTS POLICING ON CRIME
This section provides a brief narrative review of the effects of the eligible hot spots policing interventions on crime. Table 2 summarizes the treatments, hot spot definitions, and research designs. Table 3 summarizes the main effects of the intervention on crime and disorder measures, treatment effects as measured by other non-official data sources, and, if measured, the immediate spatial displacement and diffusion of crime control benefits effects. A more detailed narrative review of the 19 hot spots policing studies and the 25 tests contained in the eligible studies is provided in Appendix 3.
4.3.1 Main Effects of Hot Spots Policing on Crime
A noteworthy majority of the hot spots policing evaluations concluded that hot spots policing programs generated significant crime control benefits in the treatment areas relative to the control areas. Only 5 of the 25 tests of hot spots policing interventions did not report noteworthy crime control gains associated with the approach. These five tests were the Minneapolis RECAP treatment at commercial addresses (Sherman, Buerger, and Gartin 1989), the New York Tactical Narcotics Team in the 70th Precinct (Sviridoff et al. 1992), the Beenleigh Calls for Service Project (Criminal Justice Commission 1998), the Houston Targeted Beat Program's problem-oriented policing intervention (Caeti 1999), and the Jacksonville direct-saturation patrol intervention (Taylor et al. 2011).
The largest crime control effects were reported by three quasi-experiments: the Buenos Aires Police Presence after Terror Attack study (75% reduction in motor vehicle theft at protected blocks; DiTella and Schargrodsky 2004), the Jersey City Displacement and Diffusion Study (58% reduction in drug crime events at targeted drug hot spot and 45% reduction in prostitution events at the targeted prostitution hot spot; Weisburd et al. 2006), and the Kansas City Gun Project (49% reduction in gun crime in the targeted area; Sherman and Rogan 1995a). Randomized controlled trials generally reported smaller crime control effects. The Kansas City Crack House Raids experiment reported the smallest crime control effect; treatment blocks experienced a statistically significant reduction in total calls for service that rapidly decayed over a two week period when compared to control blocks (Sherman and Rogan 1995b).
To test the statistical significance of the observed distribution of crime reduction effects reported by the 25 tests, we used an application of the binomial distribution known as the sign test (Blalock 1979). This simple test examines the probabilities of getting an observed proportion of successes from a population of equal proportions of successes and failures. 20 of the 25 tests (80%) of hot spots policing interventions in the 19 eligible studies reported noteworthy crime control gains. According to the sign test, this result was statistically significant (exact binomial two tailed probability = .0041).
4.3.2 Crime Displacement and Diffusion Effects of Hot Spots Policing
17 of the 25 tests (68.0%) examined whether focused police efforts were associated with crime displacement or diffusion of crime control benefits (see Table 3). Prior to a discussion of the research findings, it must be noted that it is very difficult to detect displacement effects, because the potential manifestations of displacement are quite diverse. As Barr and Pease (1990) suggest, “if, in truth, displacement is complete, some displaced crime will fall outside the areas and types of crime being studied or be so dispersed as to be masked by background variation… no research study, however massive, is likely to resolve the issue” (293). Diffusion effects are likely to be as difficult to assess. All 17 tests were limited to examining immediate spatial displacement and diffusion effects; that is, whether focused police efforts in targeted areas resulted in crime “moving around the corner” or whether these proximate areas experienced unintended crime control benefits.
Our review suggests that diffusion of crime control benefits effects were more likely to be observed than crime displacement. Only 3 of the 17 studies reported substantial immediate spatial displacement of crime into areas surrounding the targeted locations. The tests that reported statistically significant crime displacement effects were in the St. Louis Problem-Oriented Policing in Three Drug Market Locations Study (Hope 1994), Jacksonville Problem-Oriented Policing at Violent Crime Hot Spots experiment (Taylor et al. 2011), and Philadelphia Foot Patrol experiment (Ratcliffe et al. 2011). However, eight tests suggested possible diffusion effects associated with the focused police interventions. The tests that reported statistically significant diffusion of crime control benefits effects were in the Jersey City DMAP experiment (Weisburd and Green 1995), Kansas City Gun Project (Sherman and Rogan 1995a), Houston Targeted Beat Program (two tests: areas surrounding the zero-tolerance beats and problem-oriented policing beats; Caeti, 1999), Oakland Beat Health study (Mazerolle et al. 2000), Philadelphia Drug Corners Crackdowns Project (Lawton et al. 2005), and the Jersey City Displacement and Diffusion Study (two tests: buffer zones surrounding the targeted prostitution hot spot and the targeted drug hot spots; Weisburd et al. 2006).
As with our simple assessment of main effects, we used the sign test to determine whether hot spots policing interventions generated statistically significant immediate spatial crime displacement. 14 of the 17 tests (82.4%) of spatial crime displacement did not report statistically significant movement of crime from targeted hot spots into surrounding areas. According to the sign test, this result was statistically significant (exact binomial two tailed probability = .0127).
4.3.3 Study Implementation
The majority of the eligible hot spots policing studies seemed to implement the desired treatment successfully. Seven studies (36.8% of 19), however, did report potential threats to the integrity of the treatment. The Minneapolis RECAP experiment showed no statistically significant differences in the prevalence of citizen calls for service at commercial addresses that received the problem-oriented policing treatment as compared to control commercial addresses (Sherman, Buerger, and Gartin 1989). These results were probably due to the assignment of too many cases to the RECAP unit, thus outstripping the amount of resources and attention the police officers provided to each address (Buerger 1993). Moreover, the simple randomization procedure led to the placing of some of the highest event addresses into the treatment group; this led to high variability between the treatment and control groups and low statistical power. Although the overall findings suggest that the RECAP program was not effective in preventing crime, a case study analysis revealed that several addresses experienced dramatic reductions in total calls for service (Buerger 1992: 1-6, 133-139, 327-331).
The Vera Institute of Justice evaluation of the Tactical Narcotics Teams noted that the intervention was not implemented as planned in one of the two treatment precincts (Sviridoff et al. 1992). In the 67th Precinct, 20% of the staffing of the Tactical Narcotics Team was re-assigned to another department initiative. As a result, the treatment in the 67th Precinct yielded fewer arrests and the maintenance of targeted drug hot spots by uniform patrol was shortened when compared to the treatment in the 70th Precinct.
The patrol treatment in the Minneapolis Hot Spots experiment (Sherman and Weisburd 1995: 638-639) was disrupted during summer months due to a peak in the overall calls for service received by the Minneapolis Police Department and a shortage of officers due to vacations; this situation was further complicated by changes in the computerized calls for service system implemented in the fall. The changes in the calls for service system and the disappearance of differences in patrol dosage between treatment and control hot spots during summer months were addressed by conducting separate outcome analyses using different intervention time periods; there were no substantive differences in the outcomes of the experiment across the different time periods.
The Jersey City DMAP experiment (Weisburd and Green 1995: 721) and Jersey City POP at Violent Places experiment (Braga 1997: 107-142) reported instances where the treatments were threatened by subversion by the participants. The officers charged with preventing crime at the treatment hot spots were resistant to participating in the programs and this resulted in low levels of treatment during the early months of both experiments. In the Jersey City DMAP experiment, this situation was remedied by providing a detailed crackdown schedule to the Narcotics Squad commander and extending the experiment from 12 months to 15 months. This problem was remedied in the Jersey City POP experiment by changing the leadership of the POP unit, developing an implementation accountability system, providing additional training in the problem-oriented policing approach, and through other smaller adjustments.
The Houston Beat Patrol Program reported that the three “high visibility” patrol beats managed by one substation experienced police resistance to the program (Caeti 1999). However, the evaluation suggested that the treatment was applied with enough integrity to measure possible impacts on reported crime outcomes. In the Jersey City Displacement and Diffusion Study, focused police attention was originally applied to three crime hot spots; unfortunately, the Police Foundation research team detected that the intervention was not being applied with an adequate dosage in the burglary hot spot and, as such, dropped the location from the evaluation (Weisburd et al. 2006).
Of course, these implementation problems are not unique to these hot spots policing experiments and quasi-experiments; many well-known criminal justice field experiments have experienced and successfully dealt with methodological difficulties.5 It is also important to note here that none of the eligible studies noted problems with attrition. Since the units-of-analysis were places, this may have diminished common attrition issues commonly found in evaluations involving people as the units-of-analysis.
4.4 META-ANALYSIS OF THE EFFECTS OF HOT SPOTS POLICING ON CRIME
Our meta-analyses of the effects of hot spots policing programs on crime were limited to 16 of the 19 eligible studies. Two studies, the St. Louis Problem-Oriented Policing in Three Drug Market Locations Study (Hope 1994) and the Beenleigh (Australia) Calls for Service Project (Criminal Justice Commission 1998), did not report the necessary information to calculate program effect sizes. As described in Appendix 3, the Houston (TX) Targeted Beat Program (Caeti 1999) did not use appropriate statistical methods to estimate program effects and, unfortunately, accurate effect sizes could not be calculated. We were able to calculate effect sizes for 20 main effects tests and 13 displacement and diffusion tests in these 16 eligible studies.
Computation of effect sizes in the studies was not always direct. The goal was to convert all observed effects into a standardized mean difference effect size metric. None of the studies we examined calculated standardized effect sizes, and indeed, it was sometimes difficult to develop precise effect size metrics from published materials. This reflects a more general problem in crime and justice with “reporting validity” (Farrington, 2006; Lösel and Köferl, 1989), and has been documented in recent reviews of reporting validity in crime and justice studies (see Perry and Johnson, 2008; Perry et al., 2010).
As described earlier, David B. Wilson's Effect Size Calculator was used to calculate the standardized mean difference effect sizes for all outcomes in the eligible studies. For Minneapolis RECAP, we used the chi-square values comparing the difference in calls for service at RECAP and control targets before and after the intervention. We calculated effect sizes from exact p-values from the F tests used in the two-way analysis of variance calculations for calls for service data in the Jersey City DMAP experiment and the cutoff p-values from the OLS parameter estimates of enforcement months 1 — 6 effects on drug calls in the Pittsburgh Police Raids at Nuisance Bars quasi-experiment. For the Kansas City Gun Project, Philadelphia Drug Corners Crackdowns, Jersey City Displacement and Diffusion Study, and the Buenos Aires Terror Attack Study, we calculated standardized mean effect sizes based on the t-test results reported for the intervention variables' effects on the outcome variables.6 For the remaining studies, we calculated odds ratios based on reported pre-test and post-test (or intervention period) crime outcome counts for treatment and control groups; we calculated the variance of the odds ratios following the method outlined in the Appendix of Farrington et al. (2007). In Appendix 4, we provide effect sizes for each outcome for the 20 tests. In Appendix 5, we provide effect sizes for each outcome for the 13 displacement and diffusion tests.
Using the overall mean effect size from each study for 20 main effects tests, the forest plots in Figure 1 show the standardized difference in means between the treatment and control or comparison conditions (effect size) with a 95 percent confidence interval plotted around them for all tests. Points plotted to the right of 0 indicate a treatment effect; in this case, the test showed a reduction in crime or disorder. Points to the left of 0 indicate a backfire effect where control conditions improved relative to treatment conditions. Since the Q statistic which was significant at the p < .05 level (Q = 184.021, df = 19, p < 0.000), we used a random effects model to estimate the overall mean effect size based on a heterogeneous distribution of effect sizes. The meta-analysis of effect sizes suggests an effect in favor of hot spots policing strategies (p<.001). However, the overall effect size for these studies is .184; this would be considered a small mean effect size (see Cohen, 1988).
Seventeen tests reported effect sizes that favor treatment conditions over control conditions. The Kansas City Gun quasi-experiment (.866), Philadelphia Drug Corners Crackdown quasi-experiment (.855), and Buenos Aires Police Presence after Terror Attack quasi-experiment (.617) tests reported the largest statistically significant effect sizes while the Minneapolis Hot Spots Patrol experiment (.061) reported the smallest statistically significant effect size. The forest plots in Figures 2 and 3 present the meta-analyses of the largest and smallest effect sizes for each study, respectively.7 For the largest effect size meta-analysis, the overall standardize mean difference effect size was moderate (.278) and statistically significant at the p < .05 level. For the smallest effect size meta-analysis, the overall standardize mean difference effect size was small (.155) and statistically significant at the p < .05 level. Table 4 presents mean effect sizes for the effects of hot spots policing programs on violent crime, property crime, drug offense, and disorder offense outcomes. Hot spots policing programs produced statistically-significant (p <.05) positive mean effect sizes for drug offense outcomes (.249), violent crime outcomes (.175), and disorder offense outcomes (.151). Hot spots policing programs also produced a positive but smaller mean effect size for property crime outcomes (.084) that was statistically significant at a less restrictive level (p <.10).
Given the important distinction in methodological quality between the randomized controlled trials and quasi-experimental evaluation studies, we also examined research design as a moderator variable. Figure 4 presents a random effects model examining the two different classes of evaluation designs included in this review.8 Consistent with prior research suggesting that weaker designs are more likely to report stronger effects in crime and justice studies (Weisburd et al. 2001; Welsh et al. 2011), the quasi-experimental designs were associated with a much larger within-group effect size (.325, p <.05) relative to the randomized controlled trial designs (.116, p <.05).
4.4.1 Meta-Analysis of Displacement and Diffusion Effects
In this analysis, we analyzed crime displacement and diffusion effects jointly as two sides of a single distribution that ranged from harmful to beneficial effects. Using the overall mean effect size from each study for 13 displacement and diffusion tests, the forest plots in Figure 5 show the standardized difference in means between the treatment and control or comparison conditions (effect size) with a 95 percent confidence interval plotted around them for all tests. Points plotted to the right of 0 indicate a diffusion of crime control benefits effect; in this case, the test showed a reduction in crime or disorder in the areas surrounding the targeted hot spots. Points to the left of 0 indicate a crime displacement effect. Since the Q statistic which was significant at the p < .05 level (Q = 22699.482, df = 12, p = 0.000), we used a random effects model to estimate the overall mean effect size based on a heterogeneous distribution of effect sizes. The meta-analysis suggests a small but statistically significant overall diffusion of crime control benefits effect (.104) generated by the hot spots policing strategies (p<.001).
Nine tests reported effect sizes that favor diffusion effects over displacement effects. The Philadelphia Drug Corners Crackdown quasi-experiment (.580), Jersey City Displacement and Diffusion Study quasi-experiments (buffers around prostitution site = .395, buffers around drug crime site = .124),9 Oakland Beat Health experiment (.160), Jersey City Problem-Oriented Policing at Violent Places experiment (.049), Lowell Policing Crime and Disorder Hot Spots experiment (.013), and Boston Safe Street Teams quasi-experiment (.009) reported statistically significant diffusion effects. Four tests reported effect sizes that favor displacement effects over diffusion effects. Only the Philadelphia Foot Patrol experiment reported a statistically significant displacement effect (-.057). The forest plots in Figures 6 and 7 present the meta-analyses of the largest and smallest effect sizes for each study, respectively.10 Both meta-analyses estimated overall effect sizes that favored diffusion effects over displacement effects. For the largest effect size meta-analysis, the overall standardize mean difference effect size was small (.136) and statistically significant at the p < .05 level. For the smallest effect size meta-analysis, the overall standardize mean difference effect size was also small (.071) and statistically significant at the p < .05 level. We also examined the impact of research design on displacement and diffusion effect sizes. Consistent with our analyses of main effects, the quasi-experimental designs were associated with a larger within-group diffusion effect size (.140, p <.05) relative to the randomized controlled trial designs (.049, p <.05) (Figure 8).
4.4.2 Program Type as Effect Size Moderator
Our narrative review documented that hot spots policing programs have adopted problem-oriented policing, focused drug enforcement, increased patrol, increased gun searches and seizures, and zero-tolerance policing to control high-activity crime places. Problem-oriented policing programs attempt to change the underlying conditions at hot spots that cause them to generate recurring crime problems (Goldstein 1990). The other hot spots policing interventions represent increased traditional policing activities concentrated at specific places to prevent crime through general deterrence and increased risk of apprehension. There is, of course, some overlap between the enforcement interventions employed by the problem-oriented policing hot spots programs and the actions taken by the increased policing hot spots programs. However, these two general types of programs represent fundamentally different orientations in dealing with the problems of high-activity crime places.
Moderator variables help to explain and understand differences across studies in the outcomes observed. Program type could be an influential moderator of the observed effect sizes in our overall meta-analysis. Figure 9 presents a random effects model examining the two different program types: problem-oriented policing and increased policing.11 Our meta-analysis revealed that problem-oriented policing programs produced a larger overall mean effect size (.232, p <.000) that was twice the size of the increased traditional policing overall mean effect size (.113, p <.000). Table 3 also compares the effects of problem-oriented policing programs relative to increased traditional policing programs for specific crime outcome types. It is important to note here that there are a relatively small number of studies in each of the police program type subcategories within the crime outcome categories; the small number of cases impacts the precision of the estimates and increases the widths of confidence intervals. As Table 3 reveals, the 95% confidence intervals overlap for these two distinct types of police interventions in the violent crime, property crime, and drug offense categories. This suggests that the mean effect sizes for the subcategories may not be dissimilar. Nevertheless, problem-oriented policing interventions generated larger mean effect size point estimates relative to increased policing interventions for all crime outcome categories. The most noteworthy differences were in property crime category (increased policing did not generate a statistically-significant mean effect size while problem-oriented policing did) and the disorder offense category (95% confidence intervals do not overlap).
Finally, we also examined the crime displacement and diffusion of crime control benefits effects reported in evaluations of these two general types of hot spots policing programs. Problem-oriented policing programs produced a small but statistically-significant overall diffusion of benefits effect (.093, p <.05) in areas immediately surrounding the treatment hot spots relative to areas immediately surrounding the control hot spots. While increased policing programs also produced a small diffusion of benefits effect, it was not statistically significant.
4.4.3 Publication Bias
Publication bias presents a strong challenge to any review of evaluation studies (Rothstein 2008). Campbell reviews, such as ours, take a number of steps to reduce publication bias, as represented by the fact that three of the 19 eligible studies in our review came from unpublished sources. Wilson (2009) has argued moreover that there is often little difference in methodological quality between published and unpublished studies suggesting the importance of searching the “grey literature.” Our extensive search procedures, the use of an information retrieval specialist (Phyllis Schultze), and the mobilization of an extensive network of police scholars made it unlikely that relevant unpublished works would remain hidden from this review.
We used the trim-and-fill procedure (Duval and Tweedie 2000) to estimate the effect of potential data censoring, such as publication bias, on the outcome of the meta-analyses. The diagnostic funnel plot is based on the idea that, in the absence of bias, the plot of study effect sizes should be symmetric about the mean effect size. If there is asymmetry, the trim-and-fill procedure imputes the missing studies, adds them to the analysis, and then re-computes the mean effect size.
A visual inspection of the resulting funnel plot indicated some asymmetry with more studies with a large effect and a large standard error to the right of the mean than the left of the mean. The trim-and-fill procedure determined that two studies should be added to create symmetry. The funnel plot with imputed studies is presented in Figure 10. These additional studies only slightly changed the mean effect size estimate. Using a random effects model, the mean random effect decreased from 0.184 (95% CI = 0.115, 0.252) to 0.164 (95% CI = 0.095, 0.233). Indeed, the 95 percent confidence intervals substantially overlap, suggesting that the mean effect sizes are likely to be the same.
5 Conclusion
The results of this systematic review support the assertion that focusing police efforts at high activity crime places can be effective in preventing crime (Braga 2008; Eck 1997, 2002; Skogan and Frydl, 2004; Weisburd and Eck 2004). Our systematic review identified 25 tests of hot spots policing in 19 eligible studies. Twenty of the 25 tests reported noteworthy crime control gains associated with the hot spots policing interventions when treatment conditions were compared to control conditions. A meta-analysis of key reported outcome measures revealed a small but statistically significant mean effect size favoring the effects of hot spots policing in reducing crime in treatment places relative to control places. The extant evaluation research seems to provide fairly robust evidence that hot spots policing is an effective crime prevention strategy.
As this systematic review was in its final stages of approval, three new unpublished randomized controlled trials of hot spots policing were completed. All three experiments reported significant crime control gains and further strengthen the conclusions of this systematic review. 12
Due to data limits, the current state-of-the-art in assessing crime displacement has focused mostly on figuring out if crime simply moved elsewhere (Braga 2008; Weisburd and Green 1995b). To some observers, establishing the absence of a displacement effect is fundamentally impossible because the potential manifestations of displacement are quite diverse (Barr and Pease 1990). In this review, 17 studies measured potential immediate spatial displacement and diffusion effects. When displacement was measured, it was very limited and unintended crime prevention benefits were more likely to be associated with the hot spots policing programs. A meta-analysis of key reported outcome measures in the areas surrounding targeted hot spots revealed a small but statistically significant mean effect size favoring a diffusion of crime control benefits rather than a crime displacement effect. Based on this encouraging evidence, it seems that focusing police efforts on high-activity crime places does not inevitably lead to crime displacement and crime control benefits may diffuse into the areas immediately surrounding the targeted locations (see also Bowers et al. 2011).
Ten of the 19 eligible studies in this reviewed used randomized controlled trials to evaluate the effects of hot spots policing on crime. When research design was considered as an effect size moderator, our meta-analysis reported that the quasi-experimental evaluation generated large overall effect sizes when compared to the randomized controlled trials. While the biases in quasi-experimental research are not clear (e.g. Campbell and Boruch 1975; Wilkinson and Task Force on Statistical Inference 1999), recent reviews in crime and justice suggest that weaker research designs often lead to more positive outcomes (e.g. see Weisburd, Lum, and Petrosino 2001; Welsh et al. 2011). This does not mean that non-experimental studies cannot be of high quality, but only that there is evidence that non-experimental designs in crime and justice are likely to overstate outcomes as contrasted with randomized experiments.
Beyond thinking about the relative crime prevention value of these programs, we need to know more about community reaction to increased levels of police enforcement action. Police effectiveness studies have traditionally paid little attention to the effects of policing practices upon citizen perceptions of police legitimacy (Tyler 2000, 2001). Does the concentration of police enforcement efforts lead citizens to question the fairness of police practices? As suggested by the Kansas City gun quasi-experiment, there is some evidence that residents of areas that are subjected to hot spots policing welcome the concentration of police efforts in problem places (Shaw 1995). The Lowell Policing Crime and Disorder Hot Spots experiment noted that community members in treated hot spot areas noticed the increased police presence and its desirable impacts on local disorder problems (Braga and Bond 2009). The Jersey City Problem-Oriented Policing in Violent Places experiment also reported that community members often perceived that the focused police problem-solving attention improved disorder problems in the treatment hot spots (Braga 1997).
Nonetheless, focused aggressive police enforcement strategies have been criticized as resulting in increased citizen complaints about police misconduct and abuse of force in New York City (Greene 1999). Rosenbaum (2006) cautions that hot spots policing can easily become zero-tolerance and indiscriminate aggressive tactics can drive a wedge between the police and communities. A recent evaluation of the adverse system side effects of Operation Sunrise, described here as the Philadelphia Drug Corners Crackdown, found that initiative strained the local judicial system by generated a high volume of arrests that resulted in a significant increase in fugitive defendants (Goldkamp and Vilcica 2008). Short-term crime gains produced by particular types of hot spots policing initiatives could undermine the long-term stability of specific neighborhoods through the increased involvement of mostly low-income minority men in the criminal justice system. The potential impacts of hot spots policing on legitimacy may depend in good part on the types of strategies used and the context of the hot spots affected. Whatever the impact, we need to know more about the effects of hot spots policing approaches on the communities that the police serve.
In our review, we found that problem-oriented policing interventions generated larger overall effect sizes when compared to the increased policing interventions. While arresting offenders remains a central strategy of the police and a necessary component of the police response to crime hot spots, it seems likely that altering place characteristics and dynamics will produce larger and longer-term crime prevention benefits (Braga and Weisburd 2010). We believe that the problem-oriented policing approach holds great promise in developing tailored responses to very specific recurring problems at crime hot spots. While it is difficult for police agencies to implement the “ideal” version of problem-oriented policing (Braga and Weisburd 2006; Cordner and Reidel 2005; Eck 2006), we believe that even “shallow” problem solving better focuses police crime prevention efforts at crime hot spots. Implementing situational prevention strategies that reduce police reliance on aggressive enforcement strategies may also yield positive benefits for policecommunity relations.
6 Plans for Updating the Review
We plan to update this review every five years in accordance with Campbell Collaboration guidelines.
7 Acknowledgements
Earlier iterations of this systematic review were supported in part by funds from the Smith Richardson Foundation and the U.S. National Academy of Sciences. David B. Wilson deserves special thanks for his analytic support (and patience) in the completing the meta-analysis. We would also like to thank Phyllis Schultze of Rutgers University's Criminal Justice Library, Rosalyn Bocker, and Deborah Braga for their assistance in searching for and locating eligible studies. David Weisburd, Larry Sherman, Mark Lipsey, Anthony Petrosino, Brandon Welsh, Charlotte Gill, Cynthia Lum, and David Farrington also deserve thanks for making helpful comments on earlier iterations of this review. Finally, we would like to thank David Weisburd, Josh Hinkle, and Cody Telep for sharing data from their problem-oriented policing systematic review and Bruce Taylor, Christopher Koper, and Daniel Woods for sharing data from their hot spots policing randomized controlled trial.
Footnotes
9 Studies Included in Systematic Review
Braga, A., & Bond, 
. Policing crime and disorder hot spots: A randomized controlled trial. Criminology, 46 (3): 577 — 608.
Braga, A., Hureau, D., & Papachristos, A. (2011). An ex-post-facto evaluation framework for place-based police interventions. Unpublished manuscript.
Braga, A., Weisburd, D., Waring, E., Mazerolle, L.G., Spelman, W., & Gajewski, F. (1999). Problem-oriented policing in violent crime places: A randomized controlled experiment. Criminology 37, 541-80.
Caeti, T. (1999). Houston's targeted beat program: A quasi-experimental test of police patrol strategies. Ph.D. diss., Sam Houston State University. Ann Arbor, MI: University Microfilms International.
Cohen, J., Gorr, W., & Singh, P. (2003). Estimating intervention effects in varying risk settings: Do police raids reduce illegal drug dealing at nuisance bars? Criminology, 41 (2): 257 — 292.
Criminal Justice Commission. (1998). Beenleigh calls for service project: Evaluation report. Brisbane, Queensland, AUS: Criminal Justice Commission.
DiTella, R., & Schargrodsky, . Do police reduce crime? Estimates using the allocation of police forces after a terrorist attack. American Economic Review 94, 115 — 133.
Hope, T. (1994). Problem-oriented policing and drug market locations: Three case studies. Crime Prevention Studies 2, 5-32.
Lawton, B., Taylor, R., & Luongo, A. (2005). Police officers on drug corners in Philadelphia, drug crime, and violent crime: Intended, diffusion, and displacement impacts. Justice Quarterly 22, 427 — 451.
Mazerolle, L., Price, J., & Roehl, J. (2000). Civil remedies and drug control: a randomized field trial in Oakland, California. Evaluation Review, 24, 212 — 241.
Ratcliffe, J., Taniguchi, T., Groff, E., & Wood, . The Philadelphia foot patrol experiment: A randomized controlled trial of police patrol effectiveness in violentcrime hot spots. Criminology (in press).
Sherman, L., Buerger, M., & Gartin, P. (1989). Beyond dial-a-cop: A randomized test of Repeat Call Policing (RECAP). Washington, DC: Crime Control Institute.
Sherman, L., & Rogan, D. (1995a). Effects of gun seizures on gun violence: ‘Hot spots’ patrol in Kansas City. Justice Quarterly 12, 673-694.
Sherman, L., & Rogan, D. (1995b). Deterrent effects of police raids on crack houses: A randomized controlled experiment. Justice Quarterly 12, 755-82.
Sherman, L., & Weisburd, D. (1995). General deterrent effects of police patrol in crime hot spots: A randomized controlled trial. Justice Quarterly 12, 625-648.
Sviridoff, M., Sadd, S., Curtis, R., & Grinc, R. (1992). The neighborhood effects of street-level drug enforcement: tactical narcotics teams in New York. New York: Vera Institute of Justice.
Taylor, B., Koper, C., & Woods, D. (2011). A randomized controlled trial of different policing strategies at hot spots of violent crime. Journal of Experimental Criminology 7, 149-181.
Weisburd, D., & Green, L. (1995a). Policing drug hot Spots: The Jersey City DMA experiment. Justice Quarterly 12, 711-36.
10 Tables
11 Figures
1
These journals were: Criminology, Criminology & Public Policy, Justice Quarterly, Journal of Research in Crime and Delinquency, Journal of Criminal Justice, Police Quarterly, Policing, Police Practice and Research, British Journal of Criminology, Journal of Quantitative Criminology, Crime & Delinquency, Journal of Criminal Law and Criminology, and Policing and Society. Hand searches covered 1979-2010.
2
Ms. Phyllis Schultze of the Gottfredson Library at the Rutgers University School of Criminal Justice executed the initial abstract search and was consulted throughout on our search strategies. Rosalyn Bocker, a Ph.D. student at the Rutgers School of Criminal Justice, also assisted with the abstract search.
4
”Zero tolerance” is a policy whereby law enforcement officials do not tolerate any disorder especially public order offences such as vagrancy, disorderly conduct, or soliciting for prostitution.
5
The landmark Kansas City Preventive Patrol Experiment had to be stopped and restarted three times before it was implemented properly; the patrol officers did not respect the boundaries of the treatment and control areas (Kelling et al. 1974). Likewise, the design of the Minneapolis Spouse Abuse Experiment was modified to a quasi-experiment when randomization could not be achieved because officers chose to arrest certain offenders on a non-random basis (Berk, Smyth, and Sherman 1988).
6
If t-tests were not reported, we calculated these statistics by dividing the reported coefficient by the reported standard error.
7
Random effects models were used to estimate the overall standardized mean effect sizes. For the largest effect size meta-analysis, Q = 217.994, df = 19, p < 0.000. For the smallest effect size meta-analysis, Q = 182.513, df = 19, p < 0.000.
8
We used a random effects model for this comparison. For the quasi-experiments, Q = 64.257, df = 8, p<0.000. For the randomized controlled trials, Q= 33.581, df = 10, p<0.000. For the overall analysis, the Between Group Q = 86.182, df = 1, p<0.000.
9
The Jersey City Displacement and Diffusion Study quasi-experiment measured separate displacement and diffusion effects for one-block and two-block buffer zones surrounding the targeted prostitution and drug crime hot spots. The Buenos Aires Police Presence after Terror Attack quasi-experiment measured treatment effects on blocks immediately surrounding the block with the protected Jewish center and blocks one removed from the block with the protected Jewish center. For both studies, distinct effect sizes were calculated for each of the two sets of buffer areas.
10
Random effects models were used to estimate the overall standardized mean effect sizes. For the largest effect size meta-analysis, Q = 215.154, df = 18, p = 0.000. For the smallest effect size meta-analysis, Q = 178.851, df = 18, p = 0.000.
11
A random effects model was used because the within-group effect size variation was determined to be heterogeneous for the two program types. For problem-oriented policing programs, Q = 51.718, df = 9, p = 0.000. For increased policing programs, Q = 42.615, df = 9, p = 0.000. The between Q = 89.688, df = 1, p = 0.000.
12
Cody Telep, Renee Mitchell, and David Weisburd completed a hot spots policing patrol experiment in Sacramento, California, that found significant declines in both calls for service and crime incidents in the treatment hot spots relative to the controls as a result of the intervention (randomly rotating police officers for 15 minutes patrol in each treatment hot spot). David Weisburd and Police Foundation colleagues conducted a hot spots policing patrol experiment involving Automated Vehicle Locator (AVL) technology that reported knowledge of AVL increased the amount of patrol delivered in the experimental hot spots, and decreased crime measured weekly. Barak Ariel and Lawrence Sherman led an experiment in the London Underground that randomly allocated either solo or double police patrols to half of hot spots (officers patrolled the platforms for one hour, during hot hours and hot days shifts; 15 minutes at a time, four times per shift). Preliminary analyses suggest that the difference in both crime and calls for service is over 25% lower in the targeted platforms than in the controls.
13
14
15
Part I Index crimes are eight serious crimes used by the U.S. Federal Bureau of Investigation in the Uniform Crime Reports and include murder, forcible rape, robbery, aggravated assault, larceny, burglary, motor vehicle theft, and arson.