Hot spots policing (Sherman and Weisburd 1995), sometimes referred to as place-based policing (Weisburd 2008), covers a range of police responses that share in common a focus of police resources on specific micro-geographic locations. Hot spots policing emerged from empirical observations that crime was highly concentrated in urban areas (Sherman et al. 1989; Sherman and Weisburd 1995) and stable over long periods of time (Spelman 1995; Weisburd et al. 2012). The logic behind it was simply that, if crime was highly concentrated on specific streets in the city, so too should police focus interventions at those places (Sherman and Weisburd 1995; Spelman 1995). In turn, there is ample evidence of the effectiveness of hot spots policing approaches against crime and disorder. A National Academy of Sciences panel concluded that “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, p. 250; see also Weisburd and Eck 2004). A systematic review by Braga et al. (2012) comes to a similar conclusion. Although not every hot spots study has shown statistically significant findings, the vast majority of such studies have (20 of 25 tests from 19 experimental or quasi-experimental evaluations reported noteworthy crime or disorder reductions), suggesting that when police focus on crime hot spots, they can have a significant beneficial impact on crime in these areas. As Braga (2007) concluded, “extant evaluation research seems to provide fairly robust evidence that hot spots policing is an effective crime prevention strategy” (p. 18).

But in recent years, like other “new policing” strategies, hot spots policing has been criticized because of concerns that it may lead to negative community outcomes. By design, hot spots policing disproportionately focuses police resources into a small segment of the jurisdiction, rather than distributing them more evenly across the jurisdiction. If the decision to distribute police resources unequally is viewed as inequitable, this will raise distributive justice concerns and likely harm police legitimacy (Kochel 2011). Furthermore, a number of scholars have argued that intensive police interventions such as hot spots policing may erode police legitimacy due to procedural justice concerns (e.g., see Kochel 2011; Rosenbaum 2006). Rosenbaum (2006) suggests that most police activity in hot spots is enforcement-oriented, and that aggressive enforcement-oriented strategies increase negative contact through increased pedestrian and vehicle stops. These experiences can drive a wedge between police and communities, as the latter can begin to feel like targets rather than partners. This is particularly relevant in high-crime minority communities where perceptions of the police already tend to be more negative (see Gau and Brunson 2010). Some commentators in the media have in turn begun to link police abuse to hot spots policing. As one writer in the Washington DC online paper “The Hill” recently commented, “The epidemic of police brutality - primarily affecting black males - can be linked to the history of a technique called hot spot policing” (Tso 2016).

Since more than 90% of large U.S. police agencies reported engaging in hot spots policing in a 2006 national survey (Willis et al. 2010), it is important to investigate whether communities are negatively impacted, and, if they are, to understand what characteristics of hot spots or policing strategies contribute to them. In this paper, we want to bring rigorous experimental evidence to examine these important concerns. Does hot spots policing lead to lowered evaluations of the police and police legitimacy? Does it lead to more concerns about police abuse of authority? Do different types of hot spots policing impact citizens in different ways? Few prior studies have examined the impacts of hot spots policing on people who live in these areas. We know of only two prior experimental studies. Weisburd et al. (2011) was limited to examining a broken windows approach in a relatively low crime jurisdiction. This study did not find strong evidence that it impacts citizens positively or negatively. Similarly, Ratcliffe et al. (2015) examined foot patrol, problem-oriented policing and offender-focused policing in Philadelphia and found that none of the interventions produced significant changes in perceptions of procedural justice or satisfaction with police. Prior studies have not examined the perceptions of police abuse of authority at crime hot spots.

The purpose of the experiment was to study how a collaborative problem-solving approach (PS) versus directed patrol (DP) versus standard policing practices (SPP) (the control group) differentially impacts residents’ opinions about police. Although crime control effectiveness is central to effective policing (Sherman et al. 1997), it cannot supersede the importance of the effects on procedural justice, legitimacy, police abuse, and residents’ willingness to cooperate with police (Skogan and Frydl 2004). This is the main focus of our experimental field trial described below (see Fig. 1, which provides the conceptual model).

Fig. 1
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Conceptual model

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The impacts of hot spots policing on citizens

While there is a convincing body of evidence that hot spots policing can reduce crime and disorder at crime hot spots, recent critiques of hot spots policing tactics have focused on potential negative impacts on citizen fear, collective efficacy and police legitimacy. These critiques argue that focusing intense police presence on small crime hot spots may have unintended negative consequences for the community or the police themselves (e.g., see Hinkle and Weisburd 2008; Kochel 2011; Rosenbaum 2006). While residents may initially be pleased to have police addressing problems on their street, Rosenbaum (2006) suggests that over time there is a risk that residents may begin to feel like targets of the police rather than partners in crime prevention. If this happens, hot spots policing will adversely impact police–community relations. Kochel (2011: 17) argues in turn that “police must recognize that in hot spots, they are working with populations who are more skeptical and less trusting of the police. Therefore, aggressive or intrusive policing tactics, while effective as short-term crime fighting strategies, may have long-term implications for police legitimacy.”

Implications for long-term crime control

Declining police legitimacy would itself be problematic. However, if the critics of hot spots policing are correct, then the possible backfire effects may also challenge the long-term crime prevention benefits of these strategies. The long-term effectiveness of policing on crime depends on public perceptions of the legitimacy of police actions (Skogan and Frydl 2004; Tyler 1990, 2004). Police need the support and voluntary cooperation of the public to effectively combat crime and maintain social order in public spaces.

Legitimacy here means more than simply popular support. Rather, it is a deeper and more complex notion that takes into account not only public support but also public willingness to recognize and defer to official authority. Legitimacy is the public belief that there is a responsibility and obligation to voluntarily accept and defer to the decisions made by authorities (Tyler 1990; Tyler and Huo 2002). Police legitimacy can increase citizens’ willingness to obey the law, support and cooperate with police, report crime and collaborate with police, and apply informal social control (Fagan and Tyler 2004, 2005; Jackson et al. 2012; Kochel et al. 2013; Lind and Tyler 1988; Murphy et al. 2008; Reisig et al. 2007; Sunshine and Tyler 2003; Tyler 1990). If hot spots policing is negatively affecting perceptions of legitimacy or procedural justice of residents on affected streets, we have reason to question whether the crime control benefits of this approach will be long lasting.

How residents experience and interpret police behaviors affects legitimacy

The primary antecedent of police legitimacy is procedural justice (fairness of the process and decision making) (Fagan and Tyler 2004; Hinds and Murphy 2007; Jackson et al. 2012; Kochel 2012; Kochel et al. 2013; Murphy et al. 2008; Sunshine and Tyler 2003; Tyler 1990; Tyler and Huo 2002; Tyler et al. 2010; Van der Toorn et al. 2011). When individuals believe that police are fair and consistent, respectful, neutral, explain their actions, and listen to residents, they view police authority as more legitimate (Sunshine and Tyler 2003; Tyler 1990; Tyler and Huo 2002). Assessments about procedural justice often derive from encounters with police or hearing about others’ encounters (Tyler 2001; Tyler and Huo 2002). Being involuntarily stopped by police has been associated with more negative views (Brown and Benedict 2002; Jesilow et al. 1995). If individuals believe they are being unfairly targeted, such as for investigatory stops (Epp et al. 2014; Gau 2013), the consequences will be declines in procedural justice and legitimacy.

Accumulated experiences theory explains that, when residents perceive that they repeatedly experience intrusive or negative treatment (e.g., stops, searches, arrests, questioning) of either themselves or others like them (vicariously), this can generate systemic frustration and weaken residents’ attachment to police (Easton 1975). The risk then of increasing time spent conducting vehicle enforcement or pedestrian stops as part of directed patrol efforts in a small geographic area is that residents may interpret repeated stops or seeing more stops as further evidence of discrimination by police, reducing trust and harming police legitimacy.

Even residents who do not feel they have been targeted or stopped without good reason are highly focused on how they are treated during encounters with police, even more so than on the outcome of that encounter, passing judgment about whether they were treated fairly and officers followed proper procedures. Negative contact with police has been found to trigger less favorable views about police fairness and effectiveness (Bradford et al. 2009; Kochel 2012) and reduce confidence in police (Skogan 2006). The group position thesis/social identity theory explains that poor treatment during encounters with police can reinforce residents’ views that hot spot residents are part of the “out-group,” not one represented in the larger collective (Bradford et al. 2014; Smith et al. 1998). This suggests that if officers who make stops in the hot spots or engage residents do not take care to invoke a sense of procedural justice, this can reinforce residents’ feelings of isolation, again harming diffuse support for police. However, the opposite effect may also occur. When residents encounter police and feel that during those interactions they are treated respectfully and fairly, this may promote a view of social acceptance into the in-group and reinforce police legitimacy (Blader and Tyler 2003).

Therefore, a collaborative problem-solving approach to hot spots policing, in which residents are engaged with police to address problems that they care about, may invoke positive and respectful police–citizen interactions, building trust and promoting legitimacy. Police asking the public to tell them about the problems residents are experiencing, and who seek to build on residents’ knowledge and suggestions to jointly craft solutions, should create a sense among residents that they are valued members of the in-group. Xu et al. (2005) reported that citizens who perceived that police were working with them to solve neighborhood problems had more satisfaction with police and reduced citizen fear. These results, coupled with findings by Taylor et al. (2011) that problem-oriented policing had stronger crime impacts than directed patrols in hot spots, suggest that the type of hot spots policing strategy and the nature and quantity of police–citizen interactions that follow from this choice may invoke different outcomes.

The lack of strong empirical evidence

The impact of hot spots policing on residents’ commitment to and feelings about police is important to the long-term wellbeing of communities. Despite the importance of identifying and understanding possible backfire effects of hot spots policing, there is little rigorous empirical evidence to date on the impacts of hot spots policing approaches on citizens who live in targeted areas. Available research tends to be weak and is mixed, particularly when police strategies involve increased presence or enforcement activities.

In some past studies, residents in crime hot spots that are subject to focused police attention welcomed the concentration of police efforts in problem places. For example, a study linked to the Kansas City Gun Project (Shaw 1995; Sherman and Rogan 1995), and studies examining the effects of aggressive traffic enforcement on firearm crimes in Indianapolis (Chermak et al. 2001; McGarrell et al. 2001), found that the community strongly supported the intensive patrols. At the same time, assessments about the quality of services provided by the department were lower in treatment areas than in areas with no change in policing, although assessments about police professionalism and harassment were not impacted. Conversely, Hawdon et al. (2003) found that South Carolina residents who perceived higher levels of police patrols had more favorable assessments of police, including higher levels of trustworthiness and perceived effectiveness, although this study was not an experiment. More directly to the point of the present study, an experiment in Redlands, Ontario, and Colton, CA that examined the impact of an aggressive order maintenance approach in hot spots on public perceptions of police legitimacy (the only study to date to directly measure this effect) found no significant change in residents’ views about police legitimacy (Weisburd et al. 2011).

Studies examining the community impact of hot spots approaches applying something other than an enforcement orientation are even rarer. A recent study by Braga and Bond (2009) examined community reaction to a problem-oriented policing initiative in Lowell, Massachusetts. Interviews with 52 community residents suggested that residents had more interactions with police in the problem-solving treatment locations. While not statistically significant,Footnote 1 the findings show a slightly larger percent improvement in the treatment areas in perceived demeanor of police and the perception that police are willing to work with citizens.

In sum, rigorous empirical evidence is lacking on the community impact of hot spots policing. No prior study has applied an experimental design to examine the effects on public perceptions of different approaches to hot spots policing. No study has comprehensively examined the impact on procedural justice, police abuse, police legitimacy, and cooperation with police, in spite of the importance of these outcomes to community wellbeing and long-term crime control. Yet, drawing from the limited prior research provides optimism that a collaborative PS approach may hold promise to produce minimal concerns about police abuse and positive assessments about procedural justice, which should promote legitimacy and cooperation with police. However, the consequence of a DP approach at crime hot spots may depend on the frequency and intensity of enforcement activities versus merely increasing police presence. There is still much to learn about the best approaches to reducing crime while promoting positive police–community relations within crime hot spots. This knowledge is particularly important because of the strong evidence base for the effectiveness of hot spots policing (Braga et al. 2014; Skogan and Frydl 2004), and its widespread application across police departments in the US (Koper 2014; Telep and Weisburd 2014; Willis et al. 2010).

The study

We sought to design an experimental study that would provide important new information about the impacts of hot spots policing on citizens. We expected that the types of hot spots policing strategies applied would result in different experiences of residents. Beyond crime control impacts, different types of hot spots policing will engage with citizens in different ways.

A key strategy to test was DP at hot spots, since this was the first and most widely implemented of hot spots policing approaches (see Sherman and Weisburd 1995; Telep et al. 2014). In the case of DP, we envisioned that as officers spend more time in hot spots, residents may be exposed to more enforcement activities—be stopped in their vehicles or while walking. Such an outcome may increase the risk of negative contacts with police. Residents might feel targeted or discriminated against, or that police are disrespectful or unjust in interactions with residents. Of course, prior studies implementing DP have not specified or tracked the activities that police perform during the additional patrols, so it remains to be seen how officers behave in the course of intensified patrols. Our study advances past research in this area by recording officer activity during DP, as well as testing its effects.

While hot spots patrols are perhaps the most common form of hot spots policing, PS approaches have been found most promising against crime (Braga et al. 2014; Taylor et al. 2011). In hot spots targeted for collaborative PS, we hypothesized that residents may themselves engage in some of the PS activities or at least see officers taking steps to address a specific ongoing problem or nuisance in the area. This process has the potential to increase positive interactions between the police and the public, including opportunities for police to demonstrate concern about problems in the area. So, one may reason that residents may feel less trustful of police upon receiving DP, but that trust may improve among residents experiencing PS. Consequently, we would anticipate legitimacy and willingness to cooperate with police to potentially decline among residents of hot spots receiving DP and improve among hot spots residents experiencing PS. This conceptual process is mapped in Fig. 1.

Our study site is St. Louis County, MO. We chose St. Louis County because it is part of a large metropolitan area with significant crime problems. In areas of the county patrolled by St Louis County Police Department (SLCPD), the 2012 violent crime rate was 244.6 per 100,000 while the property crime rate was 2063.8. Covering more than 500 square miles, with over 1 million residents, the county is the 34th largest in the U.S. and contains 17% of the state’s population (St Louis County 2013), although the SLCPD provides primary police services to just over 400,000, including to more than 90 municipalities that contract for services. The SLCPD employs just over 800 sworn and 240 civilian personnel and is an internationally accredited, full-service department. Officers have fairly stable geographic assignments, ensuring some continuity across the treatment period.

Methods

Hot spot selection

The goal was to identify stable, ongoing crime hot spots that command staff believed worthy of additional resources, and in which the treatment would be experienced by individuals whom we could survey over time. To identify hot spots, a crime analyst examined Part I and Part II crime incidents between December 2010 and November 2011, first using kernel density with Roberts Cross and Getis Ord GI* to identify spatial clustering of incidents, and then assessing counts at street segments to verify crime concentrations in residential areas over which SLCPD had primary patrol jurisdiction.Footnote 2 We excluded commercial areas due to lack of a stable population to experience and report on the treatment across time. We identified areas with at least 40 addresses to ensure a sufficient population to reliably assess public perceptions.Footnote 3 Precinct commanders vetted potential hot spots prior to treatment assignment. We excluded one hot spot when a property manager refused to permit community surveys. Seventy-one hot spots are included in the study.

Project hot spots average .01 square miles, equivalent to about four city blocks. Two-thirds occur in multi-family housing.Footnote 4 At baseline (2011), sites averaged 31 crime incidents in a year, ranging from 8 to 115 incidents. Calls for service ranged from 73 to 904, with a median of 203 and a mean of 247 (the hot spot with 904 calls is an outlier). Project hot spots account for 0.25% of the residential areas in St. Louis County and 10.6% of the Part I and II crimes in residential areas. Common crime problems included assault, vandalism, burglary, drugs, and larceny. The hot spots we examine are much hotter than those studied by Weisburd et al. (2011), which had a mean of 8.36 calls for service per street segment, and much closer in crime intensity to hot spots examined by hot spots experiments in large urban centers. For example, the Minneapolis, MN, hot spots had an average of 355 calls for service (Sherman and Weisburd 1995); Jersey City, NJ, hot spots averaged 248.4 calls for service (Weisburd and Green 1995) and Lowell, MA, hot spots averaged 150.7 calls for service (Braga and Bond 2009).

Treatment

The experiment was designed to compare PS and DP treatments to SPP. The 5-month treatment period lasted from June through October 2012. Sufficient resources were available to implement treatment in 40 hot spots; thus sites included 20 PS, 20 DP, and 31 control/SPP sites—71 hot spots in total.Footnote 5 Approximately two-thirds of the identified hot spots were located in the vicinity of North County precinct (one of seven precincts), so in order to ensure that sufficient police resources were available to adequately conduct treatment, we first blocked on North County and then we randomly assigned treatment status. To protect treatment integrity, we did not identify the locations of hot spots assigned to SPP to officers. Thus, all identified areas received typical police practices (e.g., responding to calls for service, routine preventive patrol, traffic enforcement), and the 40 treatment sites received the additional assigned police strategy (DP or PS) on top of SPP.

Problem solving

The problem-solving approach derived from routine activities theory and applied the SARA model of problem solving (See Schmerler et al. 2006). Supervisors assigned specific officers to the 20 PS sites. All assigned officers worked in the precinct in which the hot spot was located prior to assignment as the PS officer, but some officers were community policing officers, others were Neighborhood Enforcement Team officers (flexible unit in North County that responded to emerging problems), still others were beat officers. Officers and the crime analyst received 3 days of training in collaborative PS using the SARA model and were offered on-call consultation and a dedicated crime analyst throughout treatment (one crime analyst was assigned full time to the project). The crime analyst initially provided an analyses of incident and calls for service types and counts in each hot spot to the assigned officers and then worked individually with officers per their additional requests (Scanning). Treatment conditions required officers to partner with at least one stakeholder on at least one problem and to tie response strategies to what they learned about the conditions contributing to the identified problem(s). Many officers selected property crimes (45% of problems worked)—burglary, theft of or from vehicles, and larceny, but some focused on violent crimes (18%)—domestic violence, assault, drug and gang problems, quality of life concerns (15%), and repeat address issues (15%)—often problems with juveniles or burglar alarms. Officers’ selection of problems tended to derive from problems with the highest calls for service. Analysis activities included officers conducting resident surveys door-to-door; in-person and video observation of the problem areas at different times of day; Crime Prevention through Environmental Design assessments; reviewing incident reports; interviews and discussion with property managers, landlords, utility companies, a railroad company, maintenance personnel, school personnel, parents, residents, and confidential informants; attending community events to talk informally with residents; reviewing tax records to discern ownership of vacant properties; and reviewing gang databases. Responses included educating residents about the problems and corresponding target-hardening strategies; securing vacant residences; removing abandoned vehicles, trash and overgrowth; intensive follow-up with troubled juveniles; increasing communication with a variety of agencies; identifying and stopping a fencing operation; enforcing ordinances; securing access to utility boxes and air-conditioning units; redirecting students to alternative pathways home from school; coordinating with an alarm company to fix a malfunction; assessing fines for repeat false alarm violations; and other approaches. To ensure treatment integrity, PS officers submitted a written summary update monthly and met monthly with the PI to discuss progress, brainstorm and adjust course. Evaluation of project activities was based on the calls for service and incident data following the treatment period. Paid researcher observers documented activities twice per PS hot spot.

Directed patrol

DP applied a general deterrence approach and aimed to double officers’ time spent at the location. We used automated vehicle location (AVL) data to document time spent at baseline and weekly during the treatment to assess treatment integrity. On average, officers spent 2.25 h per week at each hot spot in the 7 weeks preceding treatment and 3.26 h per week at each hot spot during treatment. Following the Koper Curve (Koper 1995; Telep et al. 2014), efforts were made to target “hot times” by conducting 11- to 15-min patrols each targeted hour (41% of extra patrols lasted 11–15 min and the median length was just over 14 min). The police liason spoke with supervisors in each precinct with DP sites and provided them with Google maps of each DP hot spot in the precinct, with the boundaries clearly outlined and target times for extra patrols. During the first 2 weeks of treatment, research staff, including the PI, rode with beat officers working in the vicinity of the DP hot spots to answer questions about the project and the DP assignment specifically (e.g., that officers could do any activities and that they could rove within the hot spot instead of remaining stationary). Some minor issues such as lack of turn-around areas within the hot spot boundaries were addressed immediately. Throughout the treatment period, at roll call, officers working in the area were reminded by supervisors of the need to conduct the extra patrols. Weekly during treatment, the PI and police liaison discussed specific time spent at each DP hot spot and the police liaison communiciated with supervisors and even specific officers to increase time spent as needed. He also conducted some extra patrols himself for hot spots coming up short. Figure 2 shows that officers did spend more time in DP locations than elsewhere and compared to baseline, although time spent was not doubled.

Fig. 2
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Automated vehicle location data

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Although officers were not assigned to perform specific activities in DP hot spots, we arranged a procedure with dispatchers and officers to record time spent and officer activities. Forty-one 4-hour blocks of systematic social observation by researcher observers assess the reliability of officer activity data (88% match). We did not ask officers to perform specific activities, rather to be visible. Officer-recorded activities show that officers tended to conduct roving (37% of activities) or stationary patrols (16%), sometimes completed reports (13%), and less frequently conducted vehicle enforcement (9%), foot patrol (5%), or pedestrian stops (2%), conversed with residents (6%), sat car to car (6%), and other miscellaneous activities (6%). With the additional time spent at the locations, officers seemed to default to doing “more” of what they typically do.

We think it interesting that, provided with the freedom to determine their own activities, officers conducting DP did not focus on enforcement behaviors. As no prior study has systematically documented what officers actually do during extra patrols, we had been somewhat presumptious with our expectations, based on traditional assumptions about police officer reliance on law enforcement (e.g., see Weisburd and Braga 2006), yet our instructions to officers did not encourage them to increase enforcement actions. Instead, the interactions that DP officers had with citizens favored activities that may promote positive (although perhaps cursory) interactions. While doing DP, officers recorded talking to 247 citizens outside of a traffic or pedestrian stop, and made only 48 vehicle stops, 63 pedestrian stops, 3 arrests, and conducted searches of 6 people. Officers’ activity notes suggested that they spoke to juveniles, property management personnel, and residents in general regarding problems in the area, or just made brief, casual conversation. In some cases, officers initiated contact and at times citizens approached them while conducting stationary or roving patrols. Several of the officers’ recorded activities referenced that citizens made positive remarks (e.g., have a blessed day, we are glad you are here, thanks/appreciation) and only a few records indicated that the officer may have yelled at some kids or provided a negative outcome (e.g., take away fireworks, make them stand at a bus stop, ask to move to a safer place to play). As mentioned, past hot spots policing studies did not track specific activities during DP efforts, so it is not possible to know whether this distribution of activities, while different from the expected enforcement orientation, is atypical in practice.

Standard police practice/control

Officers were not informed about the locations of the SPP hot spots. No special treatment was provided to these locations and policing activity continued as usual, generally consisting of response to calls for service and routine preventative patrols.

Community survey

Using address data provided by SLCPD, we randomly sampled addresses in each hot spot and surveyed adult residents that answered the door.Footnote 6 We attempted to survey the same residents across all three waves, although we permitted address-level substitution and supplemented later waves with additional randomly sampled addresses. Thus, residents were sampled one to three times. Baseline was conducted in March–May 2012. Short-term impact was collected in November 2012–January 2013. Long-term impact was collected in May–July 2013. Table 1 provides the sample characteristics for each wave. As is typical for high crime areas in the U.S., residents surveyed are predominantly minority, generally rent their residences, have low incomes, and a substantial portion have only a high school diploma, GED, or less education, relative to residents of St. Louis County as a whole. Cooperation rates across the three waves ranged from 38 to 45%.Footnote 7 This reflects the portion of residents that we made contact with that participated.

Table 1 Sample population: comparisons across time and at baseline (March 2012–May 2012) by treatment group
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We assessed baseline differences in demographic characteristics of the samples across the three treatment groups (Table 1). On the nine measured demographic characteristics, we identified three significant mean differences across the groups: home ownership, average time living at the address, and race. The relationships here are not necessarily consistent. For example, the problem-solving sites had the highest level of home ownership and the highest percentage of African American respondants. The standard policing condition had residents with the shortest period of residence at that location, but with the highest percentage of white residents. One explanation for the differences observed is that they derive simply from the relatively small samples of treatment sites and the difficulty of achieving equivalence in small samples. There is no reason to suspect any systematic bias in the study because of the random allocation procedure used. Nonetheless, we account for these factors in the models estimated.Footnote 8 However, the substantive results are the same whether the controls are included or excluded from the model.

Variables

We examine the impact of the experimental conditions on four community outcomes: (1) Trust in police and procedural justice—that police act fairly, impartially, and respectfully (∝ = .924); (2) Perceived frequency that police abuse such as stopping people without good reason, using excessive force, and insulting people occurs (∝ = .832); (3) Police legitimacy—that police authority is valid and should be respected and adhered to (∝ = .728); and (4) Willingness to cooperate with police by providing information and reporting crime and suspicious behaviors (∝ = .722). Each outcome draws from multiple indicators (Table 2). Initially, we ran a confirmatory factor analysis in Mplus with all of the indicators. Having found good model fit (CFI = .983, TLI = .981, RMSEA = .027, WRMR = 1.723), factor loadings within .1 of each other, with similar and low rates of missing data (less than 10%), and adequate reliability estimates, we converted the scores to a meaningful scale that allows for comparison across other studies. For each measure, we averaged across non-missing indicators for each case and applied the percent of maximum possible formula (POMP).Footnote 9 Scores range 0 through 100.

$$ \mathrm{POMP}=\frac{\left(\mathrm{Observed}\;\mathrm{minus}\;\mathrm{the}\;\mathrm{Minimum}\;\mathrm{in}\;\mathrm{the}\;\mathrm{scale}\right)}{\left(\mathrm{Maximum}\;\mathrm{minus}\;\mathrm{Minimum}\;\mathrm{scale}\;\mathrm{score}\right)}*100 $$
Table 2 Dependent variables
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Analysis

The analysis examines the relative impact of three treatment conditions on hot spot residents’ perceptions. The analyses are multilevel mixed effect regression models using maximum likelihood estimation and robust standard errors.Footnote 10 Random intercepts account for nesting of the data: repeated measures of people within addresses and addresses within hot spots. We also account for blocking on North County in the sampling design as a random effect per Gelman and Hill (2007:275).Footnote 11 Fixed effects model time (Wave), the treatment (DP vs. PS vs. SPP), and the treatment effect (Treatment × Wave). As the treatment occurred between wave 1 and wave 2, a short-term treatment effect is reflected by wave 2 × treatment and a long-term treatment effect is reflected by wave 3 × treatment, relative to baseline.

In these models, the interaction terms provide the experimental test and are the focus of our inquiry. They reflect an assessment of the change in views among residents of that treatment group relative to the changes observed among control group residents for that same time frame. For example, short-term impact, such as wave 2 × DP, compares the change in views from wave 1 to wave 2 for the specific outcome being tested—procedural justice and trust, legitimacy, police abuse, or cooperation—among DP residents compared to the change in views among SPP residents from wave 1 to wave 2 on that outcome. Additionally, the long-term impact, for example, wave 3 × PS, compares the change in views from wave 1 to wave 3 among PS residents compared to the change in views among SPP residents from wave 1 to wave 3.Footnote 12

In several cases, we find differences at baseline (as reflected by significant values for DP/PS). However, including these main effects in the model controls for any baseline differences between the treatment groups and SPP sites on the outcome and allows us to test the experimental conditions—whether the treatment that residents experienced resulted in different changes in the outcomes relative to control residents.

Post hoc investigatory analyses

Upon completing the analyses, we ran two post hoc investigatory analyses to attempt to validate our explanation of findings. Specifically, we ran two additional multilevel mixed effect regression analyses, testing the short- and long-term treatment effects on satisfaction with treatment during encounters and satisfaction during police stops. Satisfaction with treatment is a POMP score that examines the level of satisfaction with treatment [very satisfied (4) to very dissatisfied (1)] during any encounter with police (call to report crime, make a complaint about a problem, complain about police, stopped by police, other encounter). Satisfaction with police stops is a POMP score reflecting satisfaction with treatment and outcome of the pedestrian or vehicle stop.

Findings

Our main focus in this paper is on community impacts. Given the strong evidence regarding the crime prevention effectiveness of hot spots policing (Braga 2001, 2005; Braga et al. 2014; Koper et al. 2013; Sherman and Weisburd 1995; Sorg et al. 2013; Weisburd and Eck 2004), we focused particular attention in our design to the measurement and assessment of how the community reacted to the experimental conditions. Nonetheless, consistent with the findings of past research, in an analysis of crime outcomes across the conditions, we do find modest but statistically significant differences. An interrupted time series analysis revealed that crime calls for service in DP sites declined an average of 5% (p < .01), while PS sites declined an average of 8% (p < .05). SPP locations remained stable—no significant differences during the treatment period (p > .05) (See Kochel et al. 2015).

Procedural justice

It is important to note that there was an improvement in all of the groups in procedural justice over the study period. Importantly, however, Model 1 (Table 3) shows that the residents receiving DP had overall less improvement in procedural justice in the time immediately following treatment delivery than SPP sites. In the short term, DP abated the improvement of procedural justice and trust that occurred in places experiencing SPP (see Fig. 3). However, this effect was not sustained. The coefficient for the long-term effect among both PS and DP residents is positive, while SPP sites declined slightly following wave 2 (effects are not statistically significant). By wave 3, there is no measurable difference between the groups on procedural justice and trust (based on a post-estimation margins test at wave 3 comparing the values of procedural justice and trust across residents receiving the three treatments), and DP residents overall improved from an average score of 60 at baseline to 65 at wave 3.

Table 3 Multilevel mixed effects models
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Fig. 3
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Predicted margins by treatment for the outcomes of interest

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Frequency of police abuse

Residents across all three conditions (DP, PS, SPP) reported a decline in police abuse over time. However, residents from hot spots receiving DP reported significantly steeper declines at both time points, relative to residents receiving SPP (Model 2). Residents receiving PS did not significantly differ from SPP.

Legitimacy

Since DP residents experienced a negative short-term treatment effect on trust and procedural justice (growth in views about procedural justice was depleted among residents receiving DP), past research would suggest that the effect on police legitimacy would also be negative (Hinds and Murphy 2007; Jackson et al. 2012; Kochel 2012; Kochel et al. 2013; Murphy et al. 2008; Reisig and Lloyd 2009; Sunshine and Tyler 2003; Tyler 2004; Tyler and Huo 2002; Van der Toorn et al. 2011). The coefficient is negative, however, and the effect on legitimacy among DP residents was only marginally significant (p = .061) (Model 3). Although at baseline residents of the three groups did not significantly differ, on average, on their perceptions of police legitimacy, the treatment led to slight short-term, but non-significant, declines in both the PS and DP residents’ perceptions relative to SPP residents. While residents of SPP sites saw improvements in police legitimacy across time (albeit only about 4%), in the time immediately following treatment, PS and DP residents experienced declines in legitimacy by 1 and 4%, respectively. Both PS and DP residents returned to pre-treatment levels of legitimacy by wave 3 (post-estimation margins tests of the difference in PS scores in wave 1 versus wave 3 (69.0 vs. 70.1; p = .774); for DP wave 1 versus wave 3 (70.0 vs. 70.8; p = .712)).

Willingness to cooperate with police

Willingness to cooperate with police was not significantly impacted by the treatments in the short term (Model 4). Although the coefficients for PS and DP residents are negative for the short-term impact—showing less improvement than among SPP residents—neither is statistically significant. However, the long-term effects among both PS and DP residents compared to SPP residents were significant and positive. While SPP residents’ willingness to cooperate declined slightly (2%), but not significantly, between wave 2 and 3, PS and DP residents’ cooperation scores increased by approximately 6 and 3%, respectively, between waves 2 and 3. These improvements between waves 2 and 3 are statistically significant, although small [post-estimation margins test comparing wave 2 to wave 3 for DP (85.2 vs. 87.8) and PS (82.3 vs. 86.9, each p ≤ .001), for SPP sites (87.5 vs. 85.9, p = .593)]. Thus, in spite of small short-term backfire effects on procedural justice among DP residents and moderately significant and small negative short-term consequences for legitimacy among DP residents, the short-term effects on residents’ willingness to cooperate were negligible and the long-term outcomes are promising.

Discussion

The purpose of our research was to investigate the potential backfire effects on public opinion of different approaches to hot spots policing. Critiques raised by Rosenbaum (2006) and Kochel (2011) question whether hot spots policing strategies that are enforcement-oriented, as DP has the potential to be, may feel to hot spot residents as if they are being unfairly targeted and increase negative encounters. The concern, especially with DP efforts, is that residents of high crime, disadvantaged areas, who are already suspicious of police and disproportionately experience police stops, will not welcome additional police presence. The theory of accumulated experience raises concerns that repeatedly experiencing or witnessing police stops may invoke feelings of discrimination that, on top of already disproportionate experiences with police stops and arrests, may trigger declines in police legitimacy, promoting crime in the long term.

Going beyond the number of stops, the group position thesis further cautions that the nature of interactions between residents and police can also be influential. Negative encounters where residents feel disrespected or improperly treated have the potential to generate feelings of isolation and mistrust, and affirm residents’ identity in the “out-group” of society, eroding respect for police authority. However, procedurally just experiences with police that could occur consequent to a stop or when police engage the public in PS may promote legitimacy as residents feel accepted into the majority group that police represent, and are encouraged to participate in crime prevention activities with police. Although negative police experiences tend to be more impactful than positive encounters, we sought to examine whether collaborative PS in hot spots might be enough to promote a sense of procedural justice and police legitimacy.

Effects of DP

Undertaking an experimental approach allowed us to compare the consequences on public opinion of these two hot spots policing approaches relative to SPP. We learned that different approaches in hot spots can have different effects on residents, finding different consequences in the DP versus PS sites, compared to SPP. Assessments of residents’ views immediately after treatment showed that DP in hot spots can have negative consequences. DP residents’ views about procedural justice were initially negatively affected, albeit only modestly.Footnote 13 These results are important because they suggest that DP at hot spots has the potential to reduce police legitimacy, unlike the results found by Weisburd et al. (2011) for broken windows policing at hot spots.

Initial effects may be attributed to two important elements of procedural justice. First, residents were not informed about the DP treatment. Thus, officers were spending more time in the neighborhood and offered no explanation for this change to residents beforehand or during the treatment. That lack of communication may have led residents to question officers’ motives, at least initially. Lack of opportunity for residents to provide input on the strategy (voice) may also have led to procedural justice concerns.

Second, increasingly experiencing pedestrian and vehicle stops might also lead to procedural justice concerns if residents feel targeted or experience negative treatment. In reality, declining portions of sampled residents reported being stopped by police in their car or on foot in their neighborhood—which was true for residents of DP sites (from 35.5% at wave 1 to 21.1% at wave 3), PS sites (from 31.3% at wave 1 to 20.5% at wave 3) and SPP locations (from 29.5% at wave 1 to 18% at wave 3). Furthermore, within DP sites especially, increasing proportions of stopped residents reported police had a good reason for stopping them (36.6% at wave 1, 40% wave 2, and 53.8% wave 3), as can be the case for traffic stops (vs. investigatory stops; Epp et al. 2014). DP residents had the lowest percentage at baseline of residents reporting a good reason, but this improved by 47%, while PS sites remained the same at 44% in all three waves, and SPP sites showed a non-significant decline from 46.6% at wave 1 to 41.2% at wave 3.

Furthermore, while residents of DP sites reported significantly worse treatment at baseline than the SPP residents, assessments of treatment improved among DP residents. A post hoc mixed effects regression analysis (Table 4, Model 5) revealed that DP residents reported non-significant increases in satisfaction with the way they were treated during encounters relative to SPP residents at wave 2, and both DP and PS residents reported significant improvements in satisfaction with treatment by wave 3. Focusing specifically on encounters where police stopped residents, both PS and DP residents reported slight increases in satisfaction over time (DP showed residents show significant improvement over SPP at wave 3, while PS residents’ improvement was moderate compared to SPP at wave 3) (Table 4, Model 6). SPP residents experienced declines in satisfaction during stops. Perhaps, since officers were spending more time in DP locations while making fewer stops, they were able to more positively engage with the public during the stops they did make.

Table 4 Investigatory multilevel mixed effects models
Full size table

Examining the individual components of police abuse, the largest declines among DP residents were for assessments about the frequency that officers use more force than needed and officers using insulting language during police–citizen interactions. On each of these measures, DP residents showed a 17–18% decline across the three waves, with an 11% decline for assessments about stopping people without good reason. One possible explanation for this assessment by residents is that, while officers were spending more time in DP neighborhoods, they were engaged in fairly innocuous behaviors—roving and stationary patrol and preparing reports accounted for two-thirds of activities reported by officers. Therefore, episodes of excessive force, for example, may seem less frequent as the amount of time officers spend in the neighborhood without such an incident increases. In other words, the proportion of force incidents may seem less as the base rate of time spent increases. Additionally, as officers spent more time in neighborhoods, they may have gained an appreciation for the circumstances residents face and a better grasp of the culture of the residents and this understanding may have resulted in less forceful approaches when dealing with residents (Terrill et al. 2003).

These results cannot be explained by accumulated experiences theory. Residents in DP hot spots reported experiencing fewer stops during the treatment time frame than they had previously and even greater declines in police abusive practices than the PS and SPP residents. We and other scholars had anticipated that officers with substantial discretionary time in high crime areas might use that time to stop suspicious vehicles and persons, investigate behaviors, and conduct searches that they otherwise might not have time to do. Indeed, that was the crux of the concerns raised by Chambliss (1994) when he observed police in high crime Washington DC neighborhoods. However, that was not how SLCPD officers conducting DP used their time. They opted primarily to focus on visibility, conducting stationary, roving, and foot patrols, sitting car-to-car or writing reports. Enforcement activities made up less than 15% of recorded activities.

The findings also cannot reasonably be explained by social identity theory, which suggests that encounters involving disrespectful and unfair treatment (failure to deliver procedural justice) convey to residents that they are part of the out-group, which reduces police legitimacy. In fact, as a whole, DP residents reported increasingly that stops were justified, suggesting that officers may have explained why they stopped residents or that the fairness of the stop was inherently apparent to residents. Additionally, DP residents reported improved satisfaction with the way that they were treated during encounters relative to SPP residents.

This raises the question: if the negative effect on procedural justice and trust among DP residents cannot be explained by residents being targeted for aggressive enforcement nor due to negative treatment during encounters with police, why do they initially show concern? We attribute the negative short-term effect on trust and procedural justice to the lack of communication with residents about the strategy— they were not given notice that it would happen nor given a voice to weigh in on whether or how it should happen. As time passed and concerns about the motives of the additional police presence proved benign when residents did not experience more stops or harassing behaviors, their confidence was restored and perceptions of procedural justice and police legitimacy recovered fully. The reasonable criticism then may not be that conducting DP in hot spots can harm procedural justice, trust and legitimacy, but rather that implementing any police strategy in crime hot spots without advising and consulting with residents may not be advisable. Future research should test this presumption.

Effects of PS

Recall that we had projected that a collaborative PS approach might increase residents’ procedural justice assessments, as they spent more time with police and collaborated with them. Braga and Weisburd (2010: 230) explain that, “Situational strategies can provide an opportunity for local residents and business owners to be involved in the prevention effort. Collaboration and cooperation between police and community members can improve relationships and generate mutual feelings of trust” (Skogan 2006). The PS treatment was designed to involve at least one community partner, and we had expected that residents would serve as partners in many of the PS projects. This should provide opportunities to interact positively with police—officers listening to residents’ concerns about the problems they experience and working together to develop and implement solutions. However, in practice, based on the nature of the problems, officers tended to partner with property management, community organizations (e.g., schools), or service providers (e.g., utility companies). Efforts that directly involved residents tended to be specific events: social events such as cook-outs, distributing fliers or going door-to-door educating residents about potential victimization and target-hardening approaches, conducting door-to-door surveys, or one-on-one conversations about specific problems with juveniles, domestic violence, or false alarms. Given this limited community-engagement approach to PS implementation, it is likely that residents were not sufficiently engaged to trigger improvements in procedural justice and trust. However, nor was procedural justice and trust depressed among PS residents.

Conclusions

Our study adds important new knowledge to the application of one of the most important innovations in policing that has developed over the last three decades (Telep and Weisburd 2014; Weisburd and Braga 2006). Contrary to concerns that have been raised in the media about the impacts of hot spots policing on police abuse of authority, we find that perceived abuse declined in DP hot spots, and did not differ significantly in PS hot spots. But the current study shows short-term negative effects on procedural justice and potentially on police legitimacy among DP hot spot residents, relative to the control group. So, hot spots policing critiques are not without some merit. Yet, while these initial negative consequences in the DP sites are important to acknowledge, the size of the effects are small, and, most importantly, they are not sustained in the long term once treatment concludes. Improvements in the way that DP and PS are implemented may be possible to minimize negative short-term consequences; even short-term negative impacts are important.

How can such short-term negative consequences for communities be avoided? Principles of procedural justice are, in our view, key to this process (Tyler 2004). Police agencies should engage residents prior to implementing geographically focused policing strategies and allow residents to provide input on the nature of the crime problems and potential strategies for addressing them. This allows residents a voice, an important element to forming procedural justice judgments. At a minimum, police should explain their planned actions to residents to avoid generating mistrust of officers’ motives. Increasing officer presence with no prior communication to residents to explain this change may lead residents to initially question why they are being targeted for additional police presence. Furthermore, explaining to residents that hot spot locations are selected using data on residents’ calls for service would demonstrate neutrality of the decision-making process and should further promote procedural justice and legitimacy. Last, during police–citizen interactions in the course of implementing PS, DP, or other hot spots policing strategies, officers are advised to deliver polite and respectful treatment, the final element of procedural justice. Adding these steps, which were not intentionally and systematically applied in the current hot spots policing approach, may reduce the initial negative consequences we observe.